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Performance and Algorithms Research

Performance Analysis of AI Hardware and Software

The performance characteristics of AI training and inference can be quite distinct from HPC applications despite possessing similar computational methods (large/small matrix multiplications, stencils, gather/scatter, etc...) albeit at reduced precision (single, half, BFLOAT16).  Where possible, vendors are attempting to create specialized architectures subset of computations used in AI training and inference.  Understanding the interplay between science, AI method, framework, and architecture is essential in not only in quantifying the computational potential for current and future architectures running AI models, but also identifying the bottlenecks and the ultimate limits of today's models.

Research Topics

 

Researchers

  • Samuel Williams
  • Nick Wright
  • Khaled Ibrahim
  • Hai Ah Nam
  • Leonid Oliker
  • Tan Nguyen
  • Nan Ding
  • Steve Farrell
  • Wahid Bhimji

Publications

2022

Yize Chen, Yuanyuan Shi, Daniel Arnold, Sean Peisert, "SAVER: Safe Learning-Based Controller for Real-Time Voltage Regulation", Proceedings of the 2022 IEEE Power Engineering Society (PES) General Meeting, Denver, CO, July 2022,

L. Jin, A. Lazar, C. Brown, V. Garikapati, B. Sun, S. Ravulaparthy, Q. Chen, A. Sim, K. Wu, T. Wenzel, T. Ho, C. A. Spurlock, "What Makes You Hold on to That Old Car? Joint Insights from Machine Learning and Multinomial Logit on Vehicle-level Transaction Decisions", Frontiers in Future Transportation, Connected Mobility and Automation, 2022,

S. Kim, A. Sim, K. Wu, S. Byna, Y. Son, "Design and Implementation of Dynamic I/O Control Scheme for Large Scale Distributed File Systems", Cluster Computing, 2022,

R. Shao, J. Kim A. Sim, K. Wu, "Predicting Slow Connections in Scientific Computing", 5th ACM International Workshop on ​System and Network Telemetry and Analysis (SNTA) 2022, in conjunction with The 31st ACM International Symposium on High-Performance Parallel and Distributed Computing (HPDC), 2022,

J. Bellavita, A. Sim, K. Wu, I. Monga, C. Guok, F. Würthwein, D. Davila, "Studying Scientific Data Lifecycle in On-demand Distributed Storage Caches", 5th ACM International Workshop on ​System and Network Telemetry and Analysis (SNTA) 2022, in conjunction with The 31st ACM International Symposium on High-Performance Parallel and Distributed Computing (HPDC), 2022,

R. Han, A. Sim, K. Wu, I. Monga, C. Guok, F. Würthwein, D. Davila, J. Balcas, H. Newman, "Access Trends of In-network Cache for Scientific Data", 5th ACM International Workshop on ​System and Network Telemetry and Analysis (SNTA), in conjunction with The 31st ACM International Symposium on High-Performance Parallel and Distributed Computing (HPDC), 2022,

J. Kim, M. Cafaro, J. Chou, A. Sim, "SNTA’22: The 5th Workshop on Systems and Network Telemetry and Analytics", In the proceedings of The 31st ACM International Symposium on High-Performance Parallel and Distributed Computing (HPDC'22), 2022,

Jonathan Ajo‐Franklin, Verónica Rodríguez Tribaldos, Avinash Nayak, Feng Cheng, Robert Mellors, Benxin Chi, Todd Wood, Michelle Robertson, Cody Rotermund, Eric Matzel, Dennise C. Templeton, Christina Morency, Kesheng Wu, Bin Dong, Patrick Dobson;, "The Imperial Valley Dark Fiber Project: Toward Seismic Studies Using DAS and Telecom Infrastructure for Geothermal Applications", Seismological Research Letters, June 24, 2022,

B. Dong, A. Popescu, V. Rodriguez Tribaldos, S. Byna, J. Ajo-Franklin and K. Wu, "Real-time and Post-hoc Compression for Data from Distributed Acoustic Sensing", Computers and Geosciences., June 24, 2022,

Runzhou Han, Suren Byna, Houjun Tang, Bin Dong, and Mai Zheng,, "PROV-IO: An I/O-Centric Provenance Framework for Scientific Data on HPC Systems", HPDC 2022, June 23, 2022,

Dan Bonachea, Paul H. Hargrove, An Introduction to GASNet-EX for Chapel Users, 9th Annual Chapel Implementers and Users Workshop (CHIUW 2022), June 10, 2022,

Have you ever typed "export CHPL_COMM=gasnet"? If you’ve used Chapel with multi-locale support on a system without "Cray" in the model name, then you’ve probably used GASNet. Did you ever wonder what GASNet is? What GASNet should mean to you? This talk aims to answer those questions and more. Chapel has system-specific implementations of multi-locale communication for Cray-branded systems including the Cray XC and HPE Cray EX lines. On other systems, Chapel communication uses the GASNet communication library embedded in third-party/gasnet. In this talk, that third-party will introduce itself to you in the first person.

Video Presentation

Daniel Arnold, Sy-Toan Ngo, Ciaran Roberts, Yize Chen, Anna Scaglione, Sean Peisert, "Adam-based Augmented Random Search for Control Policies for Distributed Energy Resource Cyber Attack Mitigation", Proceedings of the 2022 American Control Conference (ACC), June 2022,

Qiang Du, Dan Wang, Tong Zhou, Antonio Gilardi, Mariam Kiran, Bashir Mohammed, Derun Li, and Russell Wilcox, "Experimental beam combining stabilization using machine learning trained while phases drift", Advanced Solid State Lasers 2022, © 2022 Optica Publishing Group, June 1, 2022, Vol. 30,:pp. 12639-, doi: https://doi.org/10.1364/OE.450255

Y. Ma, F. Rusu, K. Wu, A. Sim, "Adaptive Optimization for Sparse Data on Heterogeneous GPUs", 4th Workshop on Scalable Deep Learning over Parallel And Distributed Infrastructures (ScaDL 2022), in conjunction with the 36th IEEE International Parallel & Distributed Processing Symposium, 2022,

K. Wang, S. Lee, J. Balewski, A. Sim, P. Nugent, A. Agrawal, A. Choudhary, K. Wu, W-K. Liao, "Using Multi-resolution Data to Accelerate Neural Network Training in Scientific Applications", 22nd IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGrid 2022), 2022,

M. G. Amankwah, D. Camps, E. W. Bethel, R. Van Beeumen, T. Perciano, "Quantum pixel representations and compression for N-dimensional images", Nature Scientific Reports, May 11, 2022, 12:7712, doi: 10.1038/s41598-022-11024-y

Paul H. Hargrove, Dan Bonachea, Amir Kamil, Colin A. MacLean, Damian Rouson, Daniel Waters, "UPC++ and GASNet: PGAS Support for Exascale Apps and Runtimes (ECP'22)", Poster at Exascale Computing Project (ECP) Annual Meeting 2022, May 5, 2022,

We present UPC++ and GASNet-EX, distributed libraries which together enable one-sided, lightweight communication such as arises in irregular applications, libraries and frameworks running on exascale systems.

UPC++ is a C++ PGAS library, featuring APIs for Remote Procedure Call (RPC) and for Remote Memory Access (RMA) to host and GPU memories.  The combination of these two features yields performant, scalable solutions to problems of interest within ECP.

GASNet-EX is PGAS communication middleware, providing the foundation for UPC++ and Legion, plus numerous non-ECP clients.  GASNet-EX RMA interfaces match or exceed the performance of MPI-RMA across a variety of pre-exascale systems.

 

Samuel Williams, Introduction to the Roofline Model, ECP Annual Meeting, May 2022,

Neil Mehta, Roofline on NVIDIA at NERSC, ECP Annual Meeting, May 2022,

JaeHyuk Kwack, ROOFLINE PERFORMANCE ANALYSIS W/ INTEL ADVISOR ON INTEL CPUS & GPUS, ECP Annual Meeting, May 2022,

Yosep Kim, Alexis Morvan, Long B Nguyen, Ravi K Naik, Christian J\ unger, Larry Chen, John Mark Kreikebaum, David I Santiago, Irfan Siddiqi, "High-fidelity three-qubit iToffoli gate for fixed-frequency superconducting qubits", Nature Physics, 2022, 1--6, doi: 10.1038/s41567-022-01590-3

B. Weinger, J. Kim, A. Sim, M. Nakashima, N. Moustafa, K. Wu, "Enhancing IoT Anomaly Detection Performance for Federated Learning", Digital Communications and Networks, Special Issue on Edge Computation and Intelligence, 2022, doi: 10.1016/j.dcan.2022.02.007

Maximilian Bremer, John Bachan, Cy Chan, Clint Dawson, "Adaptive total variation stable local timestepping for conservation laws", Journal of Computational Physics, April 21, 2022,

S. Zhang, R. Sadre, B. A. Legg, H. Pyles, T. Perciano, E. W. Bethel, D. Baker, O. Rübel, J. J. D. Yoreo, "Rotational dynamics and transition mechanisms of surface-adsorbed proteins", Proceedings of the National Academy of Sciences, April 11, 2022, 119:e202024211, doi: 10.1073/pnas.2020242119

Lipeng Wan, Axel Huebl, Junmin Gu, Franz Poeschel, Ana Gainaru, Ruonan Wang, Jieyang Chen, Xin Liang, Dmitry Ganyushin, Todd Munson, Ian Foster, Jean-Luc Vay, Norbert Podhorszki, Kesheng Wu, Scott Klasky, "Improving I/O Performance for Exascale Applications Through Online Data Layout Reorganization", IEEE Transactions on Parallel and Distributed Systems, 2022, 33:878-890, doi: 10.1109/TPDS.2021.3100784

Houjun Tang, Quincey Koziol, John Ravi, and Suren Byna,, "Transparent Asynchronous Parallel I/O using Background Threads", IEEE Transactions on Parallel and Distributed Systems, April 4, 2022, 33, doi: 10.1109/TPDS.2021.3090322

W. D. Fullmer, R. Porcu, J. Musser, A. S. Almgren, I. Srivastava, "The Divergence of Nearby Trajectories in Soft-Sphere DEM", Particuology, April 1, 2022, 63:1 - 8, doi: 10.1016/j.partic.2021.06.008

M. Avaylon, R. Sadre, Z. Bai, T. Perciano, "Adaptable Deep Learning and Probabilistic Graphical Model System for Semantic Segmentation", Advances in Artificial Intelligence and Machine Learnin, March 31, 2022, 2:288--302, doi: 10.54364/AAIML.2022.1119

John Bachan, Scott B. Baden, Dan Bonachea, Max Grossman, Paul H. Hargrove, Steven Hofmeyr, Mathias Jacquelin, Amir Kamil, Brian van Straalen, Daniel Waters, "UPC++ v1.0 Programmer’s Guide, Revision 2022.3.0", Lawrence Berkeley National Laboratory Tech Report, March 2022, LBNL 2001453, doi: 10.25344/S41C7Q


UPC++ is a C++ library that supports Partitioned Global Address Space (PGAS) programming. It is designed for writing efficient, scalable parallel programs on distributed-memory parallel computers. The key communication facilities in UPC++ are one-sided Remote Memory Access (RMA) and Remote Procedure Call (RPC). The UPC++ control model is single program, multiple-data (SPMD), with each separate constituent process having access to local memory as it would in C++. The PGAS memory model additionally provides one-sided RMA communication to a global address space, which is allocated in shared segments that are distributed over the processes. UPC++ also features Remote Procedure Call (RPC) communication, making it easy to move computation to operate on data that resides on remote processes.

UPC++ was designed to support exascale high-performance computing, and the library interfaces and implementation are focused on maximizing scalability. In UPC++, all communication operations are syntactically explicit, which encourages programmers to consider the costs associated with communication and data movement. Moreover, all communication operations are asynchronous by default, encouraging programmers to seek opportunities for overlapping communication latencies with other useful work. UPC++ provides expressive and composable abstractions designed for efficiently managing aggressive use of asynchrony in programs. Together, these design principles are intended to enable programmers to write applications using UPC++ that perform well even on hundreds of thousands of cores.

Dan Bonachea, Amir Kamil, "UPC++ v1.0 Specification, Revision 2022.3.0", Lawrence Berkeley National Laboratory Tech Report, March 2022, LBNL 2001452, doi: 10.25344/S4530J


UPC++ is a C++ library providing classes and functions that support Partitioned Global Address Space (PGAS) programming. The key communication facilities in UPC++ are one-sided Remote Memory Access (RMA) and Remote Procedure Call (RPC). All communication operations are syntactically explicit and default to non-blocking; asynchrony is managed through the use of futures, promises and continuation callbacks, enabling the programmer to construct a graph of operations to execute asynchronously as high-latency dependencies are satisfied. A global pointer abstraction provides system-wide addressability of shared memory, including host and accelerator memories. The parallelism model is primarily process-based, but the interface is thread-safe and designed to allow efficient and expressive use in multi-threaded applications. The interface is designed for extreme scalability throughout, and deliberately avoids design features that could inhibit scalability.

Adrián P. Diéguez, Margarita Amor, Ramón Doallo, Akira Nukada, Satoshi Matsuoka, "Efficient high-precision integer multiplication on the GPU", The International Journal of High Performance Computing Applications, March 2022, 36:356-369, doi: 10.1177/10943420221077964

George Michelogiannakis, Madeleine Glick, John Shalf, Keren Bergman, Photonics as a Means to Implement Intra-rack Resource Disaggregation, SPIE photonics west, March 2022,

Samuel B. Kachuck, Morgan Whitcomb, Jeremy N. Bassis, Daniel F. Martin, Stephen F. Price, "Simulating ice-shelf extent using damage mechanics", Journal of Glaciology, March 7, 2022, 1-12, doi: 10.1017/jog.2022.12

George Michelogiannakis, Madeleine Glick, John Shalf, Keren Bergman, "Photonics as a means to implement intra-rack resource disaggregation", Proceedings Volume 12027, Metro and Data Center Optical Networks and Short-Reach Links V, March 2022, doi: https://doi.org/10.1117/12.2607317

Paolo Calafiura and others, Artificial Intelligence for High Energy Physics, edited by Paolo Calafiura, David Rousseau, Kazuhiro Terao, (World Scientific: March 1, 2022) doi: 10.1142/12200

Patricia Gonzalez-Guerrero, Meriam Gay Bautista, Darren Lyles, George Michelogiannakis, "Temporal and SFQ Pulse-Streams Encoding for Area-Efficient Superconducting Accelerators", 27th ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS ’22), ACM, February 2022,

Patricia Gonzalez-Guerrero, Meriam Gay Bautista, Darren Lyles, George Michelogiannakis, Temporal and SFQ Pulse-Streams Encoding for Area-Efficient Superconducting Accelerators, 27th ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS ’22), February 2022,

X. Zhu, Y. Liu, P. Ghysels, D. Bindal, X. S. Li, "GPTuneBand: multi-task and multi-fidelity Bayesian optimization for autotuning large-scale high performance computing applications", SIAM PP, February 23, 2022,

George Michelogiannakis, Benjamin Klenk, Brandon Cook, Min Yee Teh, Madeleine Glick, Larry Dennison, Keren Bergman, John Shalf, "A Case For Intra-Rack Resource Disaggregation in HPC", ACM Transactions on Architecture and Code Optimization, February 2022,

Hannah Klion, Alexander Tchekhovskoy, Daniel Kasen, Adithan Kathirgamaraju, Eliot Quataert, Rodrigo Fernandez, "The impact of r-process heating on the dynamics of neutron star merger accretion disc winds and their electromagnetic radiation", Monthly Notices of the RAS, 2022, 510:2968-2979, doi: 10.1093/mnras/stab3583

John Wu, Bin Dong, Alex Sim, Automating Data Management Through Unified Runtime Systems, DOE ASCR Workshop on the Management and Storage of Scientific Data, 2022, doi: 10.2172/1843500

John Wu, Ben Brown, Paolo Calafiura, Quincey Koziol, Dongeun Lee, Alex Sim, Devesh Tiwari, Support for In-Flight Data Analyses in Scientific Workflows, DOE ASCR Workshop on the Management and Storage of Scientific Data, 2022, doi: 10.2172/1843500

A. Pereira, A. Sim, K. Wu, S. Yoo, H. Ito, "Data access pattern analysis for dCache storage system", International Conference on High Performance Computing in Asia-Pacific Region (HPC Asia 2022), 2022,

L. Jin, A. Lazar, C. Brown, Q. Chen, A. Sim, K. Wu, S. Ravulaparthy, V. Garikapati, C. A. Spurlock, What Makes You Hold on to That Old Car? Joint Insights from Machine Learning and Multinomial Logit on Vehicle-level Transaction Decisions, Transportation Research Board 101st Annual Meeting, 2022,

Z. Yao, R. Jambunathan, Y. Zeng, and A. Nonaka, "A Massively Parallel Time-Domain Coupled Electrodynamics-Micromagnetics Solver", International Journal of High Performance Computing Applications, January 10, 2022, accepted,

A. P. Santos, I. Srivastava, L. E. Silbert, J. B. Lechman, G. S. Grest, "Fluctuations and power-law scaling of dry, frictionless granular rheology near the hard-particle limit", arXiv:2201.03680, January 10, 2022,

Bin Dong, Kesheng Wu, Suren Byna, User-Defined Tensor Data Analysis, SpringerBrief, (January 1, 2022)

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C Varadharajan, AP Appling, B Arora, DS Christianson, VC Hendrix, V Kumar, AR Lima, J Müller, S Oliver, M Ombadi, T Perciano, JM Sadler, H Weierbach, JD Willard, Z Xu, J Zwart, "Can machine learning accelerate process understanding and decision-relevant predictions of river water quality?", Hydrological Processes, January 1, 2022, 36, doi: 10.1002/hyp.14565

P Diego-Palazuelos, JR Eskilt, Y Minami, M Tristram, RM Sullivan, AJ Banday, RB Barreiro, HK Eriksen, KM Górski, R Keskitalo, E Komatsu, E Martínez-González, D Scott, P Vielva, IK Wehus, "Cosmic Birefringence from the Planck Data Release 4", Physical review letters, 2022, 128:091302, doi: 10.1103/physrevlett.128.091302

DJ Watts, M Galloway, HT Ihle, KJ Andersen, R Aurlien, R Banerji, A Basyrov, M Bersanelli, S Bertocco, M Brilenkov, M Carbone, LPL Colombo, HK Eriksen, JR Eskilt, MK Foss, C Franceschet, U Fuskeland, S Galeotta, S Gerakakis, E Gjerløw, B Hensley, D Herman, M Iacobellis, M Ieronymaki, JB Jewell, A Karakci, E Keihänen, R Keskitalo, JGS Lunde, G Maggio, D Maino, M Maris, S Paradiso, B Partridge, M Reinecke, M San, NO Stutzer, A-S Suur-Uski, TL Svalheim, D Tavagnacco, H Thommesen, IK Wehus, A Zacchei, From BeyondPlanck to Cosmoglobe: Preliminary WMAP Q-band analysis, 2022,

L Collaboration, E Allys, K Arnold, J Aumont, R Aurlien, S Azzoni, C Baccigalupi, AJ Banday, R Banerji, RB Barreiro, N Bartolo, L Bautista, D Beck, S Beckman, M Bersanelli, F Boulanger, M Brilenkov, M Bucher, E Calabrese, P Campeti, A Carones, FJ Casas, A Catalano, V Chan, K Cheung, Y Chinone, SE Clark, F Columbro, G D Alessandro, PD Bernardis, TD Haan, EDL Hoz, MD Petris, SD Torre, P Diego-Palazuelos, T Dotani, JM Duval, T Elleflot, HK Eriksen, J Errard, T Essinger-Hileman, F Finelli, R Flauger, C Franceschet, U Fuskeland, M Galloway, K Ganga, M Gerbino, M Gervasi, RT Génova-Santos, T Ghigna, S Giardiello, E Gjerløw, J Grain, F Grupp, A Gruppuso, JE Gudmundsson, NW Halverson, P Hargrave, T Hasebe, M Hasegawa, M Hazumi, S Henrot-Versillé, B Hensley, LT Hergt, D Herman, E Hivon, RA Hlozek, AL Hornsby, Y Hoshino, J Hubmayr, K Ichiki, T Iida, H Imada, H Ishino, G Jaehnig, N Katayama, A Kato, R Keskitalo, T Kisner, Y Kobayashi, A Kogut, K Kohri, E Komatsu, K Komatsu, K Konishi, N Krachmalnicoff, CL Kuo, L Lamagna, M Lattanzi, AT Lee, C Leloup, F Levrier, E Linder, G Luzzi, J Macias-Perez, B Maffei, D Maino, S Mandelli, E Martínez-González, S Masi, M Massa, S Matarrese, FT Matsuda, T Matsumura, L Mele, M Migliaccio, Y Minami, A Moggi, J Montgomery, L Montier, G Morgante, B Mot, Y Nagano, T Nagasaki, R Nagata, R Nakano, T Namikawa, F Nati, P Natoli, S Nerval, F Noviello, K Odagiri, S Oguri, H Ohsaki, L Pagano, A Paiella, D Paoletti, A Passerini, G Patanchon, F Piacentini, M Piat, G Polenta, D Poletti, T Prouvé, G Puglisi, D Rambaud, C Raum, S Realini, M Reinecke, M Remazeilles, A Ritacco, G Roudil, JA Rubino-Martin, M Russell, H Sakurai, Y Sakurai, M Sasaki, D Scott, Y Sekimoto, K Shinozaki, M Shiraishi, P Shirron, G Signorelli, F Spinella, S Stever, R Stompor, S Sugiyama, RM Sullivan, A Suzuki, TL Svalheim, E Switzer, R Takaku, H Takakura, Y Takase, A Tartari, Y Terao, J Thermeau, H Thommesen, KL Thompson, M Tomasi, M Tominaga, M Tristram, M Tsuji, M Tsujimoto, L Vacher, P Vielva, N Vittorio, W Wang, K Watanuki, IK Wehus, J Weller, B Westbrook, J Wilms, EJ Wollack, J Yumoto, M Zannoni, Probing Cosmic Inflation with the LiteBIRD Cosmic Microwave Background Polarization Survey, 2022,

KJ Andersen, R Aurlien, R Banerji, M Bersanelli, S Bertocco, M Brilenkov, M Carbone, LPL Colombo, HK Eriksen, MK Foss, C Franceschet, U Fuskeland, S Galeotta, M Galloway, S Gerakakis, E Gjerløw, B Hensley, D Herman, M Iacobellis, M Ieronymaki, HT Ihle, JB Jewell, A Karakci, E Keihänen, R Keskitalo, G Maggio, D Maino, M Maris, S Paradiso, B Partridge, M Reinecke, A-S Suur-Uski, TL Svalheim, D Tavagnacco, H Thommesen, M Tomasi, DJ Watts, IK Wehus, A Zacchei, BeyondPlanck XIV. Intensity foreground sampling, degeneracies and priors, 2022,

D Herman, B Hensley, KJ Andersen, R Aurlien, R Banerji, M Bersanelli, S Bertocco, M Brilenkov, M Carbone, LPL Colombo, HK Eriksen, MK Foss, C Franceschet, U Fuskeland, S Galeotta, M Galloway, S Gerakakis, E Gjerløw, M Iacobellis, M Ieronymaki, HT Ihle, JB Jewell, A Karakci, E Keihänen, R Keskitalo, G Maggio, D Maino, M Maris, S Paradiso, B Partridge, M Reinecke, A-S Suur-Uski, TL Svalheim, D Tavagnacco, H Thommesen, DJ Watts, IK Wehus, A Zacchei, BeyondPlanck XVI. Limits on Large-Scale Polarized Anomalous Microwave Emission from Planck LFI and WMAP, 2022,

TL Svalheim, KJ Andersen, R Aurlien, R Banerji, M Bersanelli, S Bertocco, M Brilenkov, M Carbone, LPL Colombo, HK Eriksen, MK Foss, C Franceschet, U Fuskeland, S Galeotta, M Galloway, S Gerakakis, E Gjerløw, B Hensley, D Herman, M Iacobellis, M Ieronymaki, HT Ihle, JB Jewell, A Karakci, E Keihänen, R Keskitalo, G Maggio, D Maino, M Maris, S Paradiso, B Partridge, M Reinecke, A-S Suur-Uski, D Tavagnacco, H Thommesen, DJ Watts, IK Wehus, A Zacchei, A Zonca, BeyondPlanck X. Bandpass and beam leakage corrections, 2022,

M Galloway, M Reinecke, KJ Andersen, R Aurlien, R Banerji, M Bersanelli, S Bertocco, M Brilenkov, M Carbone, LPL Colombo, HK Eriksen, MK Foss, C Franceschet, U Fuskeland, S Galeotta, S Gerakakis, E Gjerløw, B Hensley, D Herman, M Iacobellis, M Ieronymaki, HT Ihle, JB Jewell, A Karakci, E Keihänen, R Keskitalo, G Maggio, D Maino, M Maris, S Paradiso, B Partridge, A-S Suur-Uski, TL Svalheim, D Tavagnacco, H Thommesen, DJ Watts, IK Wehus, A Zacchei, BeyondPlanck VIII. Efficient Sidelobe Convolution and Correction through Spin Harmonics, 2022,

M Galloway, KJ Andersen, R Aurlien, R Banerji, M Bersanelli, S Bertocco, M Brilenkov, M Carbone, LPL Colombo, HK Eriksen, MK Foss, C Franceschet, U Fuskeland, S Galeotta, S Gerakakis, E Gjerløw, B Hensley, D Herman, M Iacobellis, M Ieronymaki, HT Ihle, JB Jewell, A Karakci, E Keihänen, R Keskitalo, G Maggio, D Maino, M Maris, S Paradiso, B Partridge, M Reinecke, A-S Suur-Uski, TL Svalheim, D Tavagnacco, H Thommesen, DJ Watts, IK Wehus, A Zacchei, BeyondPlanck III. Commander3, 2022,

Hengjie Wang, Robert Planas, Aparna Chandramowlishwaran, Ramin Bostanabad, "Mosaic flows: A transferable deep learning framework for solving PDEs on unseen domains", Computer Methods in Applied Mechanics and Engineering, 2022, 389:114424,

H Weierbach, AR Lima, JD Willard, VC Hendrix, DS Christianson, M Lubich, C Varadharajan, Stream Temperature Predictions for River Basin Management in the Pacific Northwest and Mid-Atlantic Regions Using Machine Learning, Water (Switzerland), 2022, doi: 10.3390/w14071032

Sugeerth Murugesan, Mariam Kiran, Bernd Hamann, Gunther H. Weber, "Netostat: Analyzing Dynamic Flow Patterns in High-Speed Networks", Cluster Computing, 2022, doi: 10.1007/s10586-022-03543-0

E. Wes Bethel, Burlen Loring, Utkarsh Ayatchit, David Camp, P. N. Duque, Nicola Ferrier, Joseph Insley, Junmin Gu, Kress, Patrick O’Leary, David Pugmire, Silvio Rizzi, Thompson, Gunther H. Weber, Brad Whitlock, Matthew Wolf, Kesheng Wu, "The SENSEI Generic In Situ Interface: Tool and Processing Portability at Scale", In Situ Visualization for Computational Science, ( 2022) doi: 10.1007/978-3-030-81627-8_13

E. Wes Bethel, Burlen Loring, Utkarsh Ayachit, P. N. Duque, Nicola Ferrier, Joseph Insley, Junmin Gu, Kress, Patrick O’Leary, Dave Pugmire, Silvio Rizzi, Thompson, Will Usher, Gunther H. Weber, Brad Whitlock, Wolf, Kesheng Wu, "Proximity Portability and In Transit, M-to-N Data Partitioning and Movement in SENSEI", In Situ Visualization for Computational Science, ( 2022) doi: 10.1007/978-3-030-81627-8_20

Savannah Thais, Paolo Calafiura, Grigorios Chachamis, Gage DeZoort, Javier Duarte, Sanmay Ganguly, Michael Kagan, Daniel Murnane, Mark S. Neubauer, Kazuhiro Terao, Graph Neural Networks in Particle Physics: Implementations, Innovations, and Challenges, 2022 Snowmass Summer Study, 2022,

Christopher D. Jones, Kyle Knoepfel, Paolo Calafiura, Charles Leggett, Vakhtang Tsulaia, Evolution of HEP Processing Frameworks, 2022 Snowmass Summer Study, 2022,

Meghna Bhattacharya, others, Portability: A Necessary Approach for Future Scientific Software, 2022 Snowmass Summer Study, 2022,

Sunanda Banerjee, others, Detector and Beamline Simulation for Next-Generation High Energy Physics Experiments, 2022 Snowmass Summer Study, 2022,

Chun-Yi Wang, others, Reconstruction of Large Radius Tracks with the Exa.TrkX pipeline, 20th International Workshop on Advanced Computing and Analysis Techniques in Physics Research: AI Decoded - Towards Sustainable, Diverse, Performant and Effective Scientific Computing, 2022,

Alina Lazar, others, Accelerating the Inference of the Exa.TrkX Pipeline, 20th International Workshop on Advanced Computing and Analysis Techniques in Physics Research: AI Decoded - Towards Sustainable, Diverse, Performant and Effective Scientific Computing, 2022,

Sean Peisert, Unsafe at Any Clock Speed: the Insecurity of Computer System Design, Implementation, and Operation [From the Editors], IEEE Security & Privacy, Pages: 4-9 January 2022, doi: 10.0.4.85/MSEC.2021.3127086

B Faybishenko, R Versteeg, G Pastorello, D Dwivedi, C Varadharajan, D Agarwal, Challenging problems of quality assurance and quality control (QA/QC) of meteorological time series data, Stochastic Environmental Research and Risk Assessment, Pages: 1049--1062 2022, doi: 10.1007/s00477-021-02106-w

C Varadharajan, VC Hendrix, DS Christianson, M Burrus, C Wong, SS Hubbard, DA Agarwal, BASIN-3D: A brokering framework to integrate diverse environmental data, Computers and Geosciences, 2022, doi: 10.1016/j.cageo.2021.105024

MB Simmonds, WJ Riley, DA Agarwal, X Chen, S Cholia, R Crystal-Ornelas, ET Coon, D Dwivedi, VC Hendrix, M Huang, A Jan, Z Kakalia, J Kumar, CD Koven, L Li, M Melara, L Ramakrishnan, DM Ricciuto, AP Walker, W Zhi, Q Zhu, C Varadharajan, Guidelines for Publicly Archiving Terrestrial Model Data to Enhance Usability, Intercomparison, and Synthesis, Data Science Journal, 2022, doi: 10.5334/dsj-2022-003

Melissa L. Graham, Christoffer Fremling, Daniel A. Perley, Rahul Biswas, Christopher A. Phillips, Jesper Sollerman, Peter E. Nugent, Sarafina Nance, Suhail Dhawan, Jakob Nordin, Ariel Goobar, Adam Miller, James D. Neill, Xander J. Hall, Matthew J. Hankins, Dmitry A. Duev, Mansi M. Kasliwal, Mickael Rigault, Eric C. Bellm, David Hale, Przemek Mr\ oz, S. R. Kulkarni, Supernova siblings and their parent galaxies in the Zwicky Transient Facility Bright Transient Survey, Monthly Notices of the RAS, Pages: 241-254 2022, doi: 10.1093/mnras/stab3802

Yuan Qi Ni, Dae-Sik Moon, Maria R. Drout, Abigail Polin, David J. Sand, Santiago Gonz\ alez-Gait\ an, Sang Chul Kim, Youngdae Lee, Hong Soo Park, D. Andrew Howell, Peter E. Nugent, Anthony L. Piro, Peter J. Brown, Llu\ \is Galbany, Jamison Burke, Daichi Hiramatsu, Griffin Hosseinzadeh, Stefano Valenti, Niloufar Afsariardchi, Jennifer E. Andrews, John Antoniadis, Iair Arcavi, Rachael L. Beaton, K. Azalee Bostroem, Raymond G. Carlberg, S. Bradley Cenko, Sang-Mok Cha, Yize Dong, Avishay Gal-Yam, Joshua Haislip, Thomas W. -S. Holoien, Sean D. Johnson, Vladimir Kouprianov, Yongseok Lee, Christopher D. Matzner, Nidia Morrell, Curtis McCully, Giuliano Pignata, Daniel E. Reichart, Jeffrey Rich, Stuart D. Ryder, Nathan Smith, Samuel Wyatt, Sheng Yang, Infant-phase reddening by surface Fe-peak elements in a normal type Ia supernova, Nature Astronomy, 2022, doi: 10.1038/s41550-022-01603-4

S. Dhawan, A. Goobar, M. Smith, J. Johansson, M. Rigault, J. Nordin, R. Biswas, D. Goldstein, P. Nugent, Y. -L. Kim, A. A. Miller, M. J. Graham, M. Medford, M. M. Kasliwal, S. R. Kulkarni, Dmitry A. Duev, E. Bellm, P. Rosnet, R. Riddle, J. Sollerman, The Zwicky Transient Facility Type Ia supernova survey: first data release and results, Monthly Notices of the RAS, Pages: 2228-2241 2022, doi: 10.1093/mnras/stab3093

F Molz, B Faybishenko, D Agarwal, A broad exploration of nonlinear dynamics in microbial systems motivated by chemostat experiments producing deterministic chaos., 2022,

2021

Zhe Bai, Liqian Peng, "Non-intrusive nonlinear model reduction via machine learning approximations to low-dimensional operators", Advanced Modeling and Simulation in Engineering Sciences, 2021, 8:28, doi: 10.1186/s40323-021-00213-5

Melanie E. Moses, Steven Hofmeyr, Judy L Cannon, Akil Andrews, Rebekah Gridley, Monica Hinga, Kirtus Leyba, Abigail Pribisova, Vanessa Surjadidjaja, Humayra Tasnim, Stephanie Forrest, "Spatially distributed infection increases viral load in a computational model of SARS-CoV-2 lung infection", PLOS Computational Biology, December 2021, 17(12), doi: 10.1371/journal.pcbi.1009735

J. T. Clemmer, I. Srivastava, G. S. Grest, J. B. Lechman, "Shear is Not Always Simple: Rate-Dependent Effects of Loading Geometry on Granular Rheology", Physical Review Letters, December 22, 2021, 127:268003, doi: 10.1103/PhysRevLett.127.268003

Y. Cho, J. W. Demmel, X. S. Li, Y. Liu, H. Luo, "Enhancing autotuning capability with a history database", IEEE 14th International Symposium on Embedded Multicore/Many-core Systems-on-Chip (MCSoC), December 20, 2021,

Qiao Kang, Scot Breitenfeld, Kaiyuan Hou, Wei-keng Liao, Robert Ross, and Suren Byna,, "Optimizing Performance of Parallel I/O Accesses to Non-contiguous Blocks in Multiple Array Variables", IEEE BigData 2021 conference, December 19, 2021,

S. Lee, Q. Kang, K. Wang, J. Balewski, A. Sim, A. Agrawal, A. Choudhary, P. Nugent, K. Wu, W-K. Liao, "Asynchronous I/O Strategy for Large-Scale Deep Learning Applications", IEEE International Conference on High Performance Computing, Data & Analytics (HiPC2021), 2021, doi: 10.1109/HiPC53243.2021.00046

J. Bang, C. Kim, K. Wu, A. Sim, S. Byna, H. Sung, H. Eom, "An In-Depth I/O Pattern Analysis in HPC Systems", IEEE International Conference on High Performance Computing, Data & Analytics (HiPC2021), 2021, doi: 10.1109/HiPC53243.2021.00056

I. Srivastava, L. E. Silbert, J. B. Lechman, G. S. Grest, "Flow and Arrest in Stressed Granular Materials", Soft Matter, December 17, 2021, doi: 10.1039/D1SM01344K

A. Lazar, L. Jin, C. Brown, C. A. Spurlock, A. Sim, K. Wu, "Performance of the Gold Standard and Machine Learning in Predicting Vehicle Transactions", the 3rd International Workshop on Big Data Tools, Methods, and Use Cases for Innovative Scientific Discovery (BTSD 2021), 2021, doi: 10.1109/BigData52589.2021.9671286

James R. Clavin, Yue Huang, Xin Wang, Pradeep M. Prakash, Sisi Duan, Jianwu Wang, Sean Peisert, "A Framework for Evaluating BFT", Proceedings of the IEEE International Conference on Parallel and Distributed Systems (ICPADS), IEEE, December 2021,

Andrew Adams, Kay Avila, Elisa Heymann, Mark Krenz, Jason R. Lee, Barton Miller, Sean Peisert, "Guide to Securing Scientific Software", Trusted CI Report, December 14, 2021, doi: 10.5281/zenodo.5777646

Ammar Haydari, Michael Zhang, Chen-Nee Chuah, Jane Macfarlane, Sean Peisert, Adaptive Differential Privacy Mechanism for Aggregated Mobility Dataset, arXiv preprint arXiv:2112.08487, December 10, 2021,

Shen Sheng, Mariam Kiran, Bashir Mohammed, "DynamicDeepFlow: An Approach for Identifying Changes in Network Traffic Flow Using Unsupervised Clustering", (BEST PAPER) 4th International Conference on Machine Learning for Networking (MLN'2021), December 6, 2021,

Andrew Myers, Ann Almgren, Diana Almorim, John Bell, Luca Fedeli, Lixin Ge, Kevin Gott, David Grote, Mark Hogan, Axel Huebl, Revathi Jambunathan, Remi Lehe, Cho Ng, Michael Rowan, Olga Shapoval, Maxence Thevenet, Jean-Luc Vay, Henri Vincenti, Eloise Yang, Neil Zaim, Weiqun Zhang, Yin Zhao, Edoardo Zoni, "Porting WarpX to GPU-accelerated platforms", Parallel Computing, December 1, 2021,

Yize Chen, Yuanyuan Shi, Daniel Arnold, Sean Peisert, SAVER: Safe Learning-Based Controller for Real-Time Voltage Regulation, arXiv preprint arXiv:2111.15152,, November 30, 2021,

Luca Pion-Tonachini, Kristofer Bouchard, Hector Garcia Martin, Sean Peisert, W. Bradley Holtz, Anil Aswani, Dipankar Dwivedi, Haruko Wainwright, Ghanshyam Pilania, Benjamin Nachman, Babetta L. Marrone, Nicola Falco, Prabhat, Daniel Arnold, Alejandro Wolf-Yadlin, Sarah Powers, Sharlee Climer, Quinn Jackson, Ty Carlson, Michael Sohn, Petrus Zwart, Neeraj Kumar, Amy Justice, Claire Tomlin, Daniel Jacobson, Gos Micklem, Georgios V. Gkoutos, Peter J. Bickel, Jean-Baptiste Cazier, Juliane Müller, Bobbie-Jo Webb-Robertson, Rick Stevens, Mark Anderson, Ken Kreutz-Delgado, Michael W. Mahoney, James B. Brown,, Learning from Learning Machines: a New Generation of AI Technology to Meet the Needs of Science, arXiv preprint arXiv:2111.13786, November 27, 2021,

Akel Hashim, Ravi K. Naik, Alexis Morvan, Jean-Loup Ville, Bradley Mitchell, John Mark Kreikebaum, Marc Davis, Ethan Smith, Costin Iancu, Kevin P. O Brien, Ian Hincks, Joel J. Wallman, Joseph Emerson, Irfan Siddiqi, "Randomized Compiling for Scalable Quantum Computing on a Noisy Superconducting Quantum Processor", Physical Review X, 2021, 11:041039, doi: 10.1103/PhysRevX.11.041039

Nikhil Ravi, Anna Scaglione, Sachin Kadam, Reinhard Gentz, Sean Peisert, Brent Lunghino, Emmanuel Levijarvi, Aram Shumavon, Differentially Private K-means Clustering Applied to Meter Data Analysis and Synthesis, arXiv preprint arXiv:2112.03801, November 23, 2021,

Sachin Kadam, Anna Scaglione, Nikhil Ravi, Sean Peisert, Brent Lunghino, Aram Shumavon, Optimum Noise Mechanism for Differentially Private Queries in Discrete Finite Sets, arXiv preprint arXiv:2111.11661, November 23, 2021,

Houjun Tang, Bing Xie, Suren Byna, Phillip Carns, Quincey Koziol, Sudarsun Kannan, Jay Lofstead, and Sarp Oral,, "SCTuner: An Auto-tuner Addressing Dynamic I/O Needs on Supercomputer I/O Sub-systems", 6th International Parallel Data Systems Workshop (PDSW) 2021, held in conjunction with SC21, November 21, 2021,

Cong Xu, Suparna Bhattacharya, Martin Foltin, Suren Byna, and Paolo Faraboschi, "Data-Aware Storage Tiering for Deep Learning", 6th International Parallel Data Systems Workshop (PDSW) 2021, held in conjunction with SC21, November 21, 2021,

Wei Zhang, Suren Byna, Hyogi Sim, Sangkeun Lee, Sudharshan Vazhkudai, and Yong Chen,, "Exploiting User Activeness for Data Retention in HPC Systems", International Conference for High Performance Computing, Networking, Storage and Analysis (SC '21), November 21, 2021, doi: https://doi.org/10.1145/3458817.3476201

Daniel Waters, Colin A. MacLean, Dan Bonachea, Paul H. Hargrove, "Demonstrating UPC++/Kokkos Interoperability in a Heat Conduction Simulation (Extended Abstract)", Parallel Applications Workshop, Alternatives To MPI+X (PAW-ATM), November 2021, doi: 10.25344/S4630V


We describe the replacement of MPI with UPC++ in an existing Kokkos code that simulates heat conduction within a rectangular 3D object, as well as an analysis of the new code’s performance on CUDA accelerators. The key challenges were packing the halos in Kokkos data structures in a way that allowed for UPC++ remote memory access, and streamlining synchronization costs. Additional UPC++ abstractions used included global pointers, distributed objects, remote procedure calls, and futures. We also make use of the device allocator concept to facilitate data management in memory with unique properties, such as GPUs. Our results demonstrate that despite the algorithm’s good semantic match to message passing abstractions, straightforward modifications to use UPC++ communication deliver vastly improved performance and scalability in the common case. We find the one-sided UPC++ version written in a natural way exhibits good performance, whereas the message-passing version written in a straightforward way exhibits performance anomalies. We argue this represents a productivity benefit for one-sided communication models.

Kenneth Rudinger, Craig W Hogle, Ravi K Naik, Akel Hashim, Daniel Lobser, David I Santiago, Matthew D Grace, Erik Nielsen, Timothy Proctor, Stefan Seritan, others, "Experimental Characterization of Crosstalk Errors with Simultaneous Gate Set Tomography", PRX Quantum, 2021, 2:040338, doi: 10.1103/PRXQuantum.2.040338

Amir Kamil, Dan Bonachea, "Optimization of Asynchronous Communication Operations through Eager Notifications", Parallel Applications Workshop, Alternatives To MPI+X (PAW-ATM), November 2021, doi: 10.25344/S42C71


UPC++ is a C++ library implementing the Asynchronous Partitioned Global Address Space (APGAS) model. We propose an enhancement to the completion mechanisms of UPC++ used to synchronize communication operations that is designed to reduce overhead for on-node operations. Our enhancement permits eager delivery of completion notification in cases where the data transfer semantics of an operation happen to complete synchronously, for example due to the use of shared-memory bypass. This semantic relaxation allows removing significant overhead from the critical path of the implementation in such cases. We evaluate our results on three different representative systems using a combination of microbenchmarks and five variations of the the HPCChallenge RandomAccess benchmark implemented in UPC++ and run on a single node to accentuate the impact of locality. We find that in RMA versions of the benchmark written in a straightforward manner (without manually optimizing for locality), the new eager notification mode can provide up to a 25% speedup when synchronizing with promises and up to a 13.5x speedup when synchronizing with conjoined futures. We also evaluate our results using a graph matching application written with UPC++ RMA communication, where we measure overall speedups of as much as 11% in single-node runs of the unmodified application code, due to our transparent enhancements.

Franz Poeschel, Juncheng E, William F. Godoy, Norbert Podhorszki, Scott Klasky, Greg Eisenhauer, Philip E. Davis, Lipeng Wan, Ana Gainaru, Junmin Gu, Fabian Koller, René Widera, Michael Bussmann, Axel Huebl, "Transitioning from file-based HPC workflows to streaming data pipelines with openPMD and ADIOS2", Smoky Mountains Computational Sciences and Engineering Conference (SMC2021), 2021,

Paul H. Hargrove, Dan Bonachea, Colin A. MacLean, Daniel Waters, "GASNet-EX Memory Kinds: Support for Device Memory in PGAS Programming Models", The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC'21) Research Poster, November 2021, doi: 10.25344/S4P306

Lawrence Berkeley National Lab is developing a programming system to support HPC application development using the Partitioned Global Address Space (PGAS) model. This work includes two major components: UPC++ (a C++ template library) and GASNet-EX (a portable, high-performance communication library). This poster describes recent advances in GASNet-EX to efficiently implement Remote Memory Access (RMA) operations to and from memory on accelerator devices such as GPUs. Performance is illustrated via benchmark results from UPC++ and the Legion programming system, both using GASNet-EX as their communications library.

J. Cheung, A. Sim, J. Kim, K. Wu, "Performance Prediction of Large Data Transfers", ACM/IEEE The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC21), ACM Student Research Competition (SRC), 2021,

Khaled Z. Ibrahim, Tan Nguyen, Hai Ah Nam, Wahid Bhimji, Steven Farrell, Leonid Oliker, Michael Rowan, Nicholas J. Wright, Samuel Williams, "Architectural Requirements for Deep Learning Workloads in HPC Environments", (BEST PAPER), Performance Modeling, Benchmarking, and Simulation (PMBS), November 2021,

Katherine A. Yelick, Amir Kamil, Damian Rouson, Dan Bonachea, Paul H. Hargrove, UPC++: An Asynchronous RMA/RPC Library for Distributed C++ Applications (SC21), Tutorial at the International Conference for High Performance Computing, Networking, Storage, and Analysis (SC21), November 15, 2021,

UPC++ is a C++ library supporting Partitioned Global Address Space (PGAS) programming. UPC++ offers low-overhead one-sided Remote Memory Access (RMA) and Remote Procedure Calls (RPC), along with future/promise-based asynchrony to express dependencies between computation and asynchronous data movement. UPC++ supports simple/regular data structures as well as more elaborate distributed applications where communication is fine-grained and/or irregular. UPC++ provides a uniform abstraction for one-sided RMA between host and GPU/accelerator memories anywhere in the system. UPC++'s support for aggressive asynchrony enables applications to effectively overlap communication and reduce latency stalls, while the underlying GASNet-EX communication library delivers efficient low-overhead RMA/RPC on HPC networks.

This tutorial introduces UPC++, covering the memory and execution models and basic algorithm implementations. Participants gain hands-on experience incorporating UPC++ features into application proxy examples. We examine a few UPC++ applications with irregular communication (metagenomic assembler and COVID-19 simulation) and describe how they utilize UPC++ to optimize communication performance.

Devarshi Ghoshal, Ludovico Bianchi, Abdelilah Essiari, Drew Paine, Sarah Poon, Michael Beach, Alpha N'Diaye, Patrick Huck, Lavanya Ramakrishnan, "Science Capsule: Towards Sharing and Reproducibility of Scientific Workflows", 2021 IEEE Workshop on Workflows in Support of Large-Scale Science (WORKS), November 15, 2021, doi: 10.1109/WORKS54523.2021.00014

Workflows are increasingly processing large volumes of data from scientific instruments, experiments and sensors. These workflows often consist of complex data processing and analysis steps that might include a diverse ecosystem of tools and also often involve human-in-the-loop steps. Sharing and reproducing these workflows with collaborators and the larger community is critical but hard to do without the entire context of the workflow including user notes and execution environment. In this paper, we describe Science Capsule, which is a framework to capture, share, and reproduce scientific workflows. Science Capsule captures, manages and represents both computational and human elements of a workflow. It automatically captures and processes events associated with the execution and data life cycle of workflows, and lets users add other types and forms of scientific artifacts. Science Capsule also allows users to create `workflow snapshots' that keep track of the different versions of a workflow and their lineage, allowing scientists to incrementally share and extend workflows between users. Our results show that Science Capsule is capable of processing and organizing events in near real-time for high-throughput experimental and data analysis workflows without incurring any significant performance overheads.

Bashir Mohammed, Mariam Kiran, Bjoern Enders, "NetGraf: An End-to-End Learning Network Monitoring Service", 2021 IEEE Workshop on Innovating the Network for Data-Intensive Science (INDIS), November 15, 2021, doi: 10.1109/INDIS54524.2021.00007

Nikhil Ravi, Anna Scaglione, Sean Peisert, Colored Noise Mechanism for Differentially Private Clustering, arXiv preprint arXiv:2111.07850, November 15, 2021,

V. Dumont, C. Garner, A. Trivedi, C. Jones, V. Ganapati, J. Mueller, T. Perciano, M. Kiran, and M. Day, "HYPPO: A Surrogate-Based Multi-Level Parallelism Tool for Hyperparameter Optimization", 2021 IEEE/ACM Workshop on Machine Learning in High Performance Computing Environments (MLHPC), November 15, 2021,

Tan Nguyen, Erich Strohmaier, John Shalf, "Facilitating CoDesign with Automatic Code Similarity Learning", 7th Workshop on the LLVM Compiler Infrastructure in HPC (LLVM-HPC), November 14, 2021,

Bradley K. Mitchell, Ravi K. Naik, Alexis Morvan, Akel Hashim, John Mark Kreikebaum, Brian Marinelli, Wim Lavrijsen, Kasra Nowrouzi, David I. Santiago, Irfan Siddiqi, "Hardware-Efficient Microwave-Activated Tunable Coupling between Superconducting Qubits", Physical Review Letters, 2021, 127:200502, doi: 10.1103/PhysRevLett.127.200502

S. B. Sayed, Y. Liu, L. J. Gomez, A. C. Yucel, "A butterfly-accelerated volume integral equation solver for broad permittivity and large-scale electromagnetic analysis", arxiv-preprint, November 5, 2021,

B Mohammed, M Kiran; N Krishnaswamy; Keshang, Wu, "Predicting WAN Traffic Volumes using Fourier and Multivariate SARIMA Approach", International Journal of Big Data Intelligence, November 3, 2021,

A. Syal, A. Lazar, J. Kim, A. Sim, K. Wu, "Network traffic performance analysis from passive measurements using gradient boosting machine learning", International Journal of Big Data Intelligence, 2021, 8:13-30, doi: 10.1504/IJBDI.2021.118741

Y. Ma, F. Rusu, K. Wu, A. Sim, Adaptive Elastic Training for Sparse Deep Learning on Heterogeneous Multi-GPU Servers, arXiv preprint arXiv:2110.07029, 2021,

Yize Chen, Daniel Arnold, Yuanyuan Shi, Sean Peisert, Understanding the Safety Requirements for Learning-based Power Systems Operations, arXiv preprint arXiv:2110.04983, October 11, 2021,

M Kiran, B Mohammed, Q Du, D Wang, S Shen, R Wilcox, "Controlling Laser Beam Combining via an Active Reinforcement Learning Algorithm", Advanced Solid State Lasers 2021, Washington, DC United States, October 4, 2021,

Pietro Benedusi, Michael L Minion, Rolf Krause, "An experimental comparison of a space-time multigrid method with PFASST for a reaction-diffusion problem", Computers & Mathematics with Applications, October 1, 2021,

John Bachan, Scott B. Baden, Dan Bonachea, Max Grossman, Paul H. Hargrove, Steven Hofmeyr, Mathias Jacquelin, Amir Kamil, Brian van Straalen, Daniel Waters, "UPC++ v1.0 Programmer’s Guide, Revision 2021.9.0", Lawrence Berkeley National Laboratory Tech Report, September 2021, LBNL 2001424, doi: 10.25344/S4SW2T


UPC++ is a C++ library that supports Partitioned Global Address Space (PGAS) programming. It is designed for writing efficient, scalable parallel programs on distributed-memory parallel computers. The key communication facilities in UPC++ are one-sided Remote Memory Access (RMA) and Remote Procedure Call (RPC). The UPC++ control model is single program, multiple-data (SPMD), with each separate constituent process having access to local memory as it would in C++. The PGAS memory model additionally provides one-sided RMA communication to a global address space, which is allocated in shared segments that are distributed over the processes. UPC++ also features Remote Procedure Call (RPC) communication, making it easy to move computation to operate on data that resides on remote processes.

UPC++ was designed to support exascale high-performance computing, and the library interfaces and implementation are focused on maximizing scalability. In UPC++, all communication operations are syntactically explicit, which encourages programmers to consider the costs associated with communication and data movement. Moreover, all communication operations are asynchronous by default, encouraging programmers to seek opportunities for overlapping communication latencies with other useful work. UPC++ provides expressive and composable abstractions designed for efficiently managing aggressive use of asynchrony in programs. Together, these design principles are intended to enable programmers to write applications using UPC++ that perform well even on hundreds of thousands of cores.

Dan Bonachea, Amir Kamil, "UPC++ v1.0 Specification, Revision 2021.9.0", Lawrence Berkeley National Laboratory Tech Report, September 2021, LBNL 2001425, doi: 10.25344/S4XK53


UPC++ is a C++ library providing classes and functions that support Partitioned Global Address Space (PGAS) programming. The key communication facilities in UPC++ are one-sided Remote Memory Access (RMA) and Remote Procedure Call (RPC). All communication operations are syntactically explicit and default to non-blocking; asynchrony is managed through the use of futures, promises and continuation callbacks, enabling the programmer to construct a graph of operations to execute asynchronously as high-latency dependencies are satisfied. A global pointer abstraction provides system-wide addressability of shared memory, including host and accelerator memories. The parallelism model is primarily process-based, but the interface is thread-safe and designed to allow efficient and expressive use in multi-threaded applications. The interface is designed for extreme scalability throughout, and deliberately avoids design features that could inhibit scalability.

Andrew Adams, Kay Avila, Elisa Heymann, Mark Krenz, Jason R. Lee, Barton Miller, Sean Peisert, "The State of the Scientific Software World: Findings of the 2021 Trusted CI Software Assurance Annual Challenge Interviews", Trusted CI Report, September 29, 2021,

Yilun Xu, Gang Huang, Jan Balewski, Ravi Naik, Alexis Morvan, Bradley Mitchell, Kasra Nowrouzi, David I. Santiago, Irfan Siddiqi, "QubiC: An Open-Source FPGA-Based Control and Measurement System for Superconducting Quantum Information Processors", IEEE Transactions on Quantum Engineering, 2021, 2:1-11, doi: 10.1109/TQE.2021.3116540

H. Luo, J.W. Demmel, Y. Cho, X. S. Li, Y. Liu, "Non-smooth Bayesian optimization in tuning problems", arxiv-preprint, September 21, 2021,

Md Abdul M Faysal, Shaikh Arifuzzaman, Cy Chan, Maximilian Bremer, Doru Popovici, John Shalf, "HyPC-Map: A Hybrid Parallel Community Detection Algorithm Using Information-Theoretic Approach", HPEC, September 20, 2021,

E. Copps, A. Sim (Advisor), K. Wu (Advisor), "Analyzing scientific data sharing patterns with in-network data caching", ACM Richard Tapia Celebration of Diversity in Computing (TAPIA 2021), ACM Student Research Competition (SRC), 2021,

Marco Siracusa, Emanuele Del Sozzo, Marco Rabozzi, Lorenzo Di Tucci, Samuel Williams, Donatella Sciuto, Marco Domenico Santambrogio, "A Comprehensive Methodology to Optimize FPGA Designs via the Roofline Model", Transactions on Computers (TC), September 2021, doi: 10.1109/TC.2021.3111761

Bo Fang, Daoce Wang, Sian Jin, Quincey Koziol, Zhao Zhang, Qiang Guan, Suren Byna, Sriram Krishnamoorthy, and Dingwen Tao,, "Characterizing Impacts of Storage Faults on HPC Applications: A Methodology and Insights", IEEE Cluster 2021, September 1, 2021,

Srivatsan Chakram, Andrew E. Oriani, Ravi K. Naik, Akash V. Dixit, Kevin He, Ankur Agrawal, Hyeokshin Kwon, David I. Schuster, "Seamless High-Q Microwave Cavities for Multimode Circuit Quantum Electrodynamics", Physical Review Letters, 2021, 127:107701, doi: 10.1103/PhysRevLett.127.107701

G Koolstra, N Stevenson, S Barzili, L Burns, K Siva, S Greenfield, W Livingston, A Hashim, RK Naik, JM Kreikebaum, KP O'Brien, DI Santiago, J Dressel, I Siddiqi, "Monitoring fast superconducting qubit dynamics using a neural network", Preprint, August 2021,

Sebastian Götschel, Michael Minion, Daniel Ruprecht, Robert Speck, "Twelve Ways To Fool The Masses When Giving Parallel-In-Time Results Authors", Springer Proceedings in Mathematics & Statistics, August 25, 2021,

Tommaso Buvoli, Michael Minion, "IMEX Runge-Kutta Parareal for Non-diffusive Equations", Springer Proceedings in Mathematics & Statistics, August 25, 2021,

Meriam Gay Bautista, Zhi Jackie Yao, Anastasiia Butko, Mariam Kiran, Mekena Metcalf, "Towards Automated Superconducting Circuit Calibration using Deep Reinforcement Learning", 2021 IEEE Computer Society Annual Symposium on VLSI (ISVLSI), Tampa, FL, USA, IEEE, August 23, 2021, pp. 462-46, doi: 10.1109/ISVLSI51109.2021.00091

Tan Nguyen, Colin MacLean, Marco Siracusa, Douglas Doerfler, Nicholas J. Wright, Samuel Williams, "FPGA‐based HPC accelerators: An evaluation on performance and energy efficiency", CCPE, August 22, 2021, doi: 10.1002/cpe.6570

I. Srivastava, S. A. Roberts, J. T. Clemmer, L. E. Silbert, J. B. Lechman, G. S. Grest, "Jamming of Bidisperse Frictional Spheres", Physical Review Research, August 13, 2021, 3:L032042, doi: 10.1103/PhysRevResearch.3.L032042

Meriam Gay Bautista, Patricia Gonzalez-Guerrero, Darren Lyles, George Michelogiannakis, "Superconducting Shuttle-flux Shift Buffer for Race Logic", 2021 IEEE International Midwest Symposium on Circuits and Systems (MWSCAS), August 2021,

Dan Bonachea, "UPC++ as_eager Working Group Draft, Revision 2020.6.2", Lawrence Berkeley National Laboratory Tech Report, August 9, 2021, LBNL 2001416, doi: 10.25344/S4FK5R

This draft proposes an extension for a new future-based completion variant that can be more effectively streamlined for RMA and atomic access operations that happen to be satisfied at runtime using purely node-local resources. Many such operations are most efficiently performed synchronously using load/store instructions on shared-memory mappings, where the actual access may only require a few CPU instructions. In such cases we believe it’s critical to minimize the overheads imposed by the UPC++ runtime and completion queues, in order to enable efficient operation on hierarchical node hardware using shared-memory bypass.

The new upcxx::{source,operation}_cx::as_eager_future() completion variant accomplishes this goal by relaxing the current restriction that future-returning access operations must return a non-ready future whose completion is deferred until a subsequent explicit invocation of user-level progress. This relaxation allows access operations that are completed synchronously to instead return a ready future, thereby avoiding most or all of the runtime costs associated with deferment of future completion and subsequent mandatory entry into the progress engine.

We additionally propose to make this new as_eager_future() completion variant the new default completion for communication operations that currently default to returning a future. This should encourage use of the streamlined variant, and may provide performance improvements to some codes without source changes. A mechanism is proposed to restore the legacy behavior on-demand for codes that might happen to rely on deferred completion for correctness.

Finally, we propose a new as_eager_promise() completion variant that extends analogous improvements to promise-based completion, and corresponding changes to the default behavior of as_promise().

Nan Ding, Muaaz Awan, Samuel Williams, "Instruction Roofline: An insightful visual performance model for GPUs", CCPE, August 4, 2021, doi: 10.1002/cpe.6591

Suren Byna, Houjun Tang, and Quincey Koziol,, Automatic and Transparent Scientific Data Management with Object Abstractions, PASC 2021, in a Minisymposium on "Data Movement Orchestration on HPC Systems", July 31, 2021,

Nan Ding, Yang Liu, Samuel Williams, Xiaoye S. Li, "A Message-Driven, Multi-GPU Parallel Sparse Triangular Solver", SIAM Conference on Applied and Computational Discrete Algorithms (ACDA21), July 19, 2021,

Charlene Yang, Yunsong Wang, Thorsten Kurth, Steven Farrell, Samuel Williams, "Hierarchical Roofline Performance Analysis for Deep Learning Applications", Intelligent Computing, LNNS, July 15, 2021, doi: 10.1007/978-3-030-80126-7

Jean Sexton, Zarija Lukic, Ann Almgren, Chris Daley, Brian Friesen, Andrew Myers, and Weiqun Zhang, "Nyx: A Massively Parallel AMR Code for Computational Cosmology", The Journal Of Open Source Software, July 10, 2021,

M. Nakashima, A. Sim, Y. Kim, J. Kim, J. Kim, "Automated Feature Selection for Anomaly Detection in Network Traffic Data", ACM Transactions on Management Information Systems (TMIS), 2021, 12:1-28, doi: 10.1145/3446636

Drew Paine, Sarah Poon, Lavanya Ramakrishnan, "Investigating User Experiences with Data Abstractions on High Performance Computing Systems", June 29, 2021, LBNL LBNL-2001374,

Scientific exploration generates expanding volumes of data that commonly require High Performance Computing (HPC) systems to facilitate research. HPC systems are complex ecosystems of hardware and software that frequently are not user friendly. The Usable Data Abstractions (UDA) project set out to build usable software for scientific workflows in HPC environments by undertaking multiple rounds of qualitative user research. Qualitative research investigates how individuals accomplish their work and our interview-based study surfaced a variety of insights about the experiences of working in and with HPC ecosystems. This report examines multiple facets to the experiences of scientists and developers using and supporting HPC systems. We discuss how stakeholders grasp the design and configuration of these systems, the impacts of abstraction layers on their ability to successfully do work, and the varied perceptions of time that shape this work. Examining the adoption of the Cori HPC at NERSC we explore the anticipations and lived experiences of users interacting with this system's novel storage feature, the Burst Buffer. We present lessons learned from across these insights to illustrate just some of the challenges HPC facilities and their stakeholders need to account for when procuring and supporting these essential scientific resources to ensure their usability and utility to a variety of scientific practices.

Thomas M Evans, Andrew Siegel, Erik W Draeger,Jack Deslippe, Marianne M Francois, Timothy C Germann,William E Hart, Daniel F Martin, "A survey of software implementations usedby application codes in the ExascaleComputing Project", The International Journal of HighPerformance Computing Applications, June 25, 2021, doi: https://doi.org/10.1177/10943420211028940

Élie Genois, Jonathan A. Gross, Agustin Di Paolo, Noah J. Stevenson, Gerwin Koolstra, Akel Hashim, Irfan Siddiqi, Alexandre Blais, "Quantum-tailored machine-learning characterization of a superconducting qubit", Preprint, June 24, 2021,

Robin J Dolleman, Debadi Chakraborty, Daniel R Ladiges, Herre SJ van der Zant, John E Sader, Peter G Steeneken, "Squeeze-film effect on atomically thin resonators in the high-pressure limit", Submitted to Nano Letters, June 24, 2021,

Yang Liu, Pieter Ghysels, Lisa Claus, Xiaoye Sherry Li, "Sparse Approximate Multifrontal Factorization with Butterfly Compression for High Frequency Wave Equations", SIAM J. Sci. Comput., June 22, 2021,

E. Copps, H. Zhang, A. Sim, K. Wu, I. Monga, C. Guok, F. Würthwein, D. Davila, E. Fajardo, "Analyzing scientific data sharing patterns with in-network data caching", 4th ACM International Workshop on ​System and Network Telemetry and Analysis (SNTA 2021), 2021, doi: 10.1145/3452411.3464441

Y. Wang, K. Wu, A. Sim, S. Yoo, S. Misawa, "Access Patterns of Disk Cache for Large Scientific Archive", 4th ACM International Workshop on ​System and Network Telemetry and Analysis (SNTA 2021), 2021, doi: 10.1145/3452411.3464444

A. Lazar, A. Sim, K. Wu, "GPU-based Classification for Wireless Intrusion Detection", 4th ACM International Workshop on ​System and Network Telemetry and Analysis (SNTA 2021), 2021, doi: 10.1145/3452411.3464445

Devarshi Ghoshal, Drew Paine, Gilberto Pastorello, Abdelrahman Elbashandy, Dan Gunter, Oluwamayowa Amusat, Lavanya Ramakrishnan, "Experiences with Reproducibility: Case Studies from Scientific Workflows", (P-RECS'21) Proceedings of the 4th International Workshop on Practical Reproducible Evaluation of Computer Systems, ACM, June 21, 2021, doi: 10.1145/3456287.3465478

Reproducible research is becoming essential for science to ensure transparency and for building trust. Additionally, reproducibility provides the cornerstone for sharing of methodology that can improve efficiency. Although several tools and studies focus on computational reproducibility, we need a better understanding about the gaps, issues, and challenges for enabling reproducibility of scientific results beyond the computational stages of a scientific pipeline. In this paper, we present five different case studies that highlight the reproducibility needs and challenges under various system and environmental conditions. Through the case studies, we present our experiences in reproducing different types of data and methods that exist in an experimental or analysis pipeline. We examine the human aspects of reproducibility while highlighting the things that worked, that did not work, and that could have worked better for each of the cases. Our experiences capture a wide range of scenarios and are applicable to a much broader audience who aim to integrate reproducibility in their everyday pipelines.

Ayaz Akram, Venkatesh Akella, Sean Peisert, Jason Lowe-Power,, "Enabling Design Space Exploration for RISC-V Secure Compute Environments", Proceedings of the Fifth Workshop on Computer Architecture Research with RISC-V (CARRV), (co-located with ISCA 2021), June 17, 2021,

Devarshi Ghoshal, Ludovico Bianchi, Abdelilah Essiari, Michael Beach, Drew Paine, Lavanya Ramakrishnan, "Science Capsule - Capturing the Data Life Cycle", Journal of Open Source Software, 2021, 6:2484, doi: 10.21105/joss.02484

E. W. Bethel, C. Heinemann, and T. Perciano, "Performance Tradeoffs in Shared-memory Platform Portable Implementations of a Stencil Kernel", Eurographics Symposium on Parallel Graphics and Visualization, June 14, 2021,

Weiqun Zhang, Andrew Myers, Kevin Gott, Ann Almgren and John Bell, "AMReX: Block-Structured Adaptive Mesh Refinement for Multiphysics Applications", The International Journal of High Performance Computing Applications, June 12, 2021,

C Varadharajan, Z Kakalia, E Alper, EL Brodie, M Burrus, RWH Carroll, D Christianson, W Dong, V Hendrix, M Henderson, S Hubbard, D Johnson, R Versteeg, KH Williams, DA Agarwal, The Colorado East River Community Observatory Data Collection, Hydrological Processes 35(6), 2021, doi: 10.22541/au.161962485.54378235/v1

Bing Xie, Houjun Tang, Suren Byna, Jesse Hanley, Quincey Koziol, Tonglin Li, Sarp Oral,, "Battle of the Defaults: Extracting Performance Characteristics of HDF5 under Production Load", CCGrid 2021, May 31, 2021,

Ciaran Roberts, Sy-Toan Ngo, Alexandre Milesi, Anna Scaglione, Sean Peisert, Daniel Arnold, "Deep Reinforcement Learning for Mitigating Cyber-Physical DER Voltage Unbalance Attacks”", Proceedings of the 2021 American Control Conference (ACC), May 2021, doi: 10.23919/ACC50511.2021.9482815

David McCallen, Houjun Tang, Suiwen Wu, Eric Eckert, Junfei Huang, N Anders Petersson, "Coupling of regional geophysics and local soil-structure models in the EQSIM fault-to-structure earthquake simulation framework", The International Journal of High Performance Computing Applications, May 25, 2021, doi: 10.1177/10943420211019118

Serges Love Teutu Talla, Isabelle Kemajou-Brown, Cy Chan, Bin Wang, "A Binary Multi-Subsystems Transportation Networks Estimation using Mobiliti Data", 2021 American Control Conference (ACC), May 25, 2021,

Maximilian Bremer, John Bachan, Cy Chan, and Clint Dawson, "Speculative Parallel Execution for Local Timestepping", 2021 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation, May 21, 2021,

George Michelogiannakis, SRNoC: A Statically-Scheduled Circuit-Switched Superconducting Race Logic NoC, IEEE International Parallel and Distributed Processing Symposium, May 2021,

Ayaz Akram, Anna Giannakou, Venkatesh Akella, Jason Lowe-Power, Sean Peisert, "Performance Analysis of Scientific Computing Workloads on General Purpose TEEs", Proceedings of the 35th IEEE International Parallel & Distributed Processing Symposium (IPDPS), IEEE, May 2021, doi: 10.1109/IPDPS49936.2021.00115

Y. Ma, F. Ruso, A. Sim, K. Wu, "Adaptive Stochastic Gradient Descent for Deep Learning on Heterogeneous CPU+GPU Architectures", Heterogeneity in Computing Workshop (HCW 2021), in conjunction with the 35th IEEE International Parallel & Distributed Processing Symposium (IPDPS), 2021, doi: 10.1109/IPDPSW52791.2021.00012

Md Taufique Hussain, Oguz Selvitopi, Aydin Buluç, Ariful Azad, "Communication-Avoiding and Memory-Constrained Sparse Matrix-Matrix Multiplication at Extreme Scale", 2021 IEEE International Parallel and Distributed Processing Symposium (IPDPS), May 2021, doi: 10.1109/IPDPS49936.2021.00018

George Michelogiannakis, Darren Lyles, Patricia Gonzalez-Guerrero, Meriam Bautista, Dilip Vasudevan, Anastasiia Butko, "SRNoC: A Statically-Scheduled Circuit-Switched Superconducting Race Logic NoC", May 2021,

L. Fedeli, A. Sainte-Marie, N. Zaim, M. Thevenet, J. L. Vay, A. Myers, F. Quere, and H. Vincenti, "Probing strong-field QED with Doppler-boosted petawatt-class lasers", Physical Review Letters, May 10, 2021,

Tamsin L. Edwards, Sophie Nowicki, Ben Marzeion, Regine Hock, Heiko Goelzer, Hélène Seroussi, Nicolas C. Jourdain, Donald A. Slater, Fiona E. Turner, Christopher J. Smith, Christine M. McKenna, Erika Simon, Ayako Abe-Ouchi, Jonathan M. Gregory, Eric Larour, William H. Lipscomb, Antony J. Payne, Andrew Shepherd, Cécile Agosta, Patrick Alexander, Torsten Albrecht, Brian Anderson, Xylar Asay-Davis, Andy Aschwanden, Alice Barthel, Andrew Bliss, Reinhard Calov, Christopher Chambers, Nicolas Champollion, Youngmin Choi, Richard Cullather, Joshua Cuzzone, Christophe Dumas, Denis Felikson, Xavier Fettweis, Koji Fujita, Benjamin K. Galton-Fenzi, Rupert Gladstone, Nicholas R. Golledge, Ralf Greve, Tore Hattermann, Matthew J. Hoffman, Angelika Humbert, Matthias Huss, Philippe Huybrechts, Walter Immerzeel, Thomas Kleiner, Philip Kraaijenbrink, Sébastien Le clec’h, Victoria Lee, Gunter R. Leguy, Christopher M. Little, Daniel P. Lowry, Jan-Hendrik Malles, Daniel F. Martin, Fabien Maussion, Mathieu Morlighem, James F. O’Neill, Isabel Nias, Frank Pattyn, Tyler Pelle, Stephen F. Price, Aurélien Quiquet, Valentina Radić, Ronja Reese, David R. Rounce, Martin Rückamp, Akiko Sakai, Courtney Shafer, Nicole-Jeanne Schlegel, Sarah Shannon, Robin S. Smith, Fiammetta Straneo, Sainan Sun, Lev Tarasov, Luke D. Trusel, Jonas Van Breedam, Roderik van de Wal, Michiel van den Broeke, Ricarda Winkelmann, Harry Zekollari, Chen Zhao, Tong Zhang, Thomas Zwinger, "Projected land ice contributions to twenty-first-century sea level rise", Nature, May 5, 2021, 593:74-82, doi: 10.1038/s41586-021-03302-y

David McCallen, Anders Petersson, Arthur Rodgers, Arben Pitarka, Mamun Miah, Floriana Petrone, Bjorn Sjogreen, Norman Abrahamson, Houjun Tang, "EQSIM—A multidisciplinary framework for fault-to-structure earthquake simulations on exascale computers part I: Computational models and workflow", Earthquake Spectra, May 1, 2021, 37:707-735, doi: 10.1177/8755293020970982

Sean Peisert, "Trustworthy Scientific Computing", Communications of the ACM (CACM), May 2021, doi: 10.1145/3457191

Giulia Guidi, Marquita Ellis, Daniel Rokhsar, Katherine Yelick, Aydın Buluç, "BELLA: Berkeley Efficient Long-Read to Long-Read Aligner and Overlapper", SIAM Conference on Applied and Computational Discrete Algorithms (ACDA21), 2021, doi: 10.1101/464420

D. A. Agarwal, J. Damerow, C. Varadharajan, D. S. Christianson, G. Z. Pastorello, Y.-W. Cheah, L. Ramakrishnan, "Balancing the needs of consumers and producers for scientific data collections", Ecological Informatics, 2021, 62:101251, doi: 10.1016/j.ecoinf.2021.101251

Douglas Doerfler, Farzad Fatollahi-Fard, Colin MacLean, Tan Nguyen, Samuel Williams, Nicholas J. Wright, Marco Siracusa, "Experiences Porting the SU3_Bench Microbenchmark to the Intel Arria 10 and Xilinx Alveo U280 FPGAs", International Workshop on OpenCL (iWOCL), April 2021, doi: 10.1145/3456669.3456671

J. Kim, A. Sim, J. Kim, K, Wu, J. Hahm, Improving Botnet Detection with Recurrent Neural Network and Transfer Learning, arXiv preprint arXiv:2104.12602, 2021,

T. Groves, N. Ravichandrasekaran, B. Cook, N. Keen, D. Trebotich, N. Wright, B. Alverson, D. Roweth, K. Underwood, "Not All Applications Have Boring Communication Patterns: Profiling Message Matching with BMM", Concurrency and Computation: Practice and Experience, April 26, 2021, doi: 0.1002/cpe.6380

J. Galen Wang, Roseanna N. Zia, "Vitrification is a spontaneous non-equilibrium transition driven by osmotic pressure", Journal of Physics: Condensed Matter, April 23, 2021, doi: 10.1088/1361-648x/abeec0

Sherwood Richers, Don E. Willcox, Nicole M. Ford, and Andrew Myers, "Particle-in-cell simulation of the neutrino fast flavor instabilit", Physical Review D, April 20, 2021,

Jordan Musser, Ann S Almgren, William D Fullmer, Oscar Antepara, John B Bell, Johannes Blaschke, Kevin Gott, Andrew Myers, Roberto Porcu, Deepak Rangarajan, Michele Rosso, Weiqun Zhang, and Madhava Syamlal, "MFIX:Exa: A Path Towards Exascale CFD-DEM Simulations", The International Journal of High Performance Computing Applications, April 16, 2021,

Samuel Williams, Introduction to the Roofline Model, ECP Annual Meeting, April 2021,

Samuel Williams, Roofline Analysis on NVIDIA GPUs, ECP Annual Meeting, April 2021,

Jonathan Madsen, Roofline Model using NSight Compute, ECP Annual Meeting, April 2021,

Khaled Ibrahim, Roofline on GPUs (advanced topics), ECP Annual Meeting, April 2021,

Jonathan Madsen, Roofline Instrumentation with TiMemory, ECP Annual Meeting, April 2021,

Paul H. Hargrove, Dan Bonachea, Max Grossman, Amir Kamil, Colin A. MacLean, Daniel Waters, "UPC++ and GASNet: PGAS Support for Exascale Apps and Runtimes (ECP'21)", Poster at Exascale Computing Project (ECP) Annual Meeting 2021, April 2021,

We present UPC++ and GASNet-EX, which together enable one-sided, lightweight communication such as arises in irregular applications, libraries and frameworks running on exascale systems.

UPC++ is a C++ PGAS library, featuring APIs for Remote Memory Access (RMA) and Remote Procedure Call (RPC).  The combination of these two features yields performant, scalable solutions to problems of interest within ECP.

GASNet-EX is PGAS communication middleware, providing the foundation for UPC++ and Legion, plus numerous non-ECP clients.  GASNet-EX RMA interfaces match or exceed the performance of MPI-RMA across a variety of pre-exascale systems

Marco Pritoni, Drew Paine, Gabriel Fierro, Cory Mosiman, Michael Poplawski, Joel Bender, Jessica Granderson, "Metadata Schemas and Ontologies for Building Energy Applications: A Critical Review and Use Case Analysis", Energies, April 6, 2021, doi: 10.3390/en14072024

Digital and intelligent buildings are critical to realizing efficient building energy operations and a smart grid. With the increasing digitalization of processes throughout the life cycle of buildings, data exchanged between stakeholders and between building systems have grown significantly. However, a lack of semantic interoperability between data in different systems is still prevalent and hinders the development of energy-oriented applications that can be reused across buildings, limiting the scalability of innovative solutions. Addressing this challenge, our review paper systematically reviews metadata schemas and ontologies that are at the foundation of semantic interoperability necessary to move toward improved building energy operations. The review finds 40 schemas that span different phases of the building life cycle, most of which cover commercial building operations and, in particular, control and monitoring systems. The paper’s deeper review and analysis of five popular schemas identify several gaps in their ability to fully facilitate the work of a building modeler attempting to support three use cases: energy audits, automated fault detection and diagnosis, and optimal control. Our findings demonstrate that building modelers focused on energy use cases will find it difficult, labor intensive, and costly to create, sustain, and use semantic models with existing ontologies. This underscores the significant work still to be done to enable interoperable, usable, and maintainable building models. We make three recommendations for future work by the building modeling and energy communities: a centralized repository with a search engine for relevant schemas, the development of more use cases, and better harmonization and standardization of schemas in collaboration with industry to facilitate their adoption by stakeholders addressing varied energy-focused use cases.

Daniel R. Ladiges, Sean P. Carney, Andrew Nonaka, Katherine Klymko, Guy C. Moore, Alejandro L. Garcia, Sachin R. Natesh, Aleksandar Donev, John B. Bell, "A Discrete Ion Stochastic Continuum Overdamped Solvent Algorithm for Modeling Electrolytes", Physical Review Fluids, April 1, 2021, 6(4):044309,

Sean Peisert, Bruce Schneier, Hamed Okhravi, Fabio Massacci, Terry Benzel, Carl Landwehr, Mohammad Mannan, Jelena Mirkovic, Atul Prakash, James Bret Michael, "Perspectives on the SolarWinds Incident", IEEE Security & Privacy, April 2021, 7-13, doi: 10.1109/MSEC.2021.3051235

Fabio Massacci, Trent Jaeger, Sean Peisert, "SolarWinds and the Challenges of Patching: Can We Ever Stop Dancing With the Devil?", IEEE Security & Privacy, April 2021, 14-19, doi: 10.1109/MSEC.2021.3050433

Dan Bonachea, Amir Kamil, "UPC++ v1.0 Specification, Revision 2021.3.0", Lawrence Berkeley National Laboratory Tech Report, March 31, 2021, LBNL 2001388, doi: 10.25344/S4K881

UPC++ is a C++11 library providing classes and functions that support Partitioned Global Address Space (PGAS) programming. The key communication facilities in UPC++ are one-sided Remote Memory Access (RMA) and Remote Procedure Call (RPC). All communication operations are syntactically explicit and default to non-blocking; asynchrony is managed through the use of futures, promises and continuation callbacks, enabling the programmer to construct a graph of operations to execute asynchronously as high-latency dependencies are satisfied. A global pointer abstraction provides system-wide addressability of shared memory, including host and accelerator memories. The parallelism model is primarily process-based, but the interface is thread-safe and designed to allow efficient and expressive use in multi-threaded applications. The interface is designed for extreme scalability throughout, and deliberately avoids design features that could inhibit scalability.

J. Goings, H. Hu, C. Yang, X. Li, "Reinforcement Learning Configuration Interaction", March 31, 2021,

Karol Kowalski, Raymond Bair, Nicholas P. Bauman, Jeffery S. Boschen, Eric J. Bylaska, Jeff Daily, Wibe A. de Jong, Thom Dunning, Niranjan Govind, Robert J. Harrison, Murat Keceli, Kristopher Keipert, Sriram Krishnamoorthy, Suraj Kumar, Erdal Mutlu, Bruce Palmer, Ajay Panyala, Bo Peng, Ryan M. Richard, T. P. Straatsma, Peter Sushko, Edward F. Valeev, Marat Valiev, Hubertus J. J. van Dam, Jonathan M. Waldrop, David B. Williams-Young, Chao Yang, Marcin Zalewski, Theresa L. Windus, "From NWChem to NWChemEx: Evolving with the Computational Chemistry Landscape", Chemical Reviews, March 31, 2021, doi: 10.1021/acs.chemrev.0c00998

Georgios Tzimpragos, Jennifer Volk, Dilip Vasudevan, Nestan Tsiskaridze, George Michelogiannakis, Advait Madhavan, John Shalf, Timothy Sherwood, "Temporal Computing With Superconductors", IEEE MIcro, March 2021, 41:71-79, doi: 10.1109/MM.2021.3066377

Ed Younis, Koushik Sen, Katherine Yelick, Costin Iancu, QFAST: Quantum Synthesis Using a Hierarchical Continuous Circuit Space, Bulletin of the American Physical Society, March 2021,

We present QFAST, a quantum synthesis tool designed to produce short circuits and to scale well in practice. Our contributions are: 1) a novel representation of circuits able to encode placement and topology; 2) a hierarchical approach with an iterative refinement formulation that combines "coarse-grained" fast optimization during circuit structure search with a good, but slower, optimization stage only in the final circuit instantiation. When compared against state-of-the-art techniques, although not always optimal, QFAST can reduce circuits for "time-dependent evolution" algorithms, as used by domain scientists, by 60x in depth. On typical circuits, it provides 4x better depth reduction than the widely used Qiskit and UniversalQ compilers. We also show the composability and tunability of our formulation in terms of circuit depth and running time. For example, we show how to generate shorter circuits by plugging in the best available third party synthesis algorithm at a given hierarchy level. Composability enables portability across chip architectures, which is missing from similar approaches.
QFAST is integrated with Qiskit and available at github.com/bqskit.

Akel Hashim, Ravi Naik, Alexis Morvan, Jean-Loup Ville, Brad Mitchell, John Mark Kreikebaum, Marc Davis, Ethan Smith, Costin Iancu, Kevin O Brien, Ian Hincks, Joel Wallman, Joseph V Emerson, David Ivan Santiago, Irfan Siddiqi, Scalable Quantum Computing on a Noisy Superconducting Quantum Processor via Randomized Compiling, Bulletin of the American Physical Society, 2021,

Coherent errors in quantum hardware severely limit the performance of quantum algorithms in an unpredictable manner, and mitigating their impact is necessary for realizing reliable, large-scale quantum computations. Randomized compiling achieves this goal by converting coherent errors into stochastic noise, dramatically reducing unpredictable errors in quantum algorithms and enabling accurate predictions of aggregate performance via cycle benchmarking estimates. In this work, we demonstrate significant performance gains under randomized compiling for both the four-qubit quantum Fourier transform algorithm and for random circuits of variable depth on a superconducting quantum processor. We also validate solution accuracy using experimentally-measured error rates. Our results demonstrate that randomized compiling can be utilized to maximally-leverage and predict the capabilities of modern-day noisy quantum processors, paving the way forward for scalable quantum computing.

Dan Bonachea, GASNet-EX: A High-Performance, Portable Communication Library for Exascale, Berkeley Lab – CS Seminar, March 10, 2021,

Partitioned Global Address Space (PGAS) models, pioneered by languages such as Unified Parallel C (UPC) and Co-Array Fortran, expose one-sided communication as a key building block for High Performance Computing (HPC) applications. Architectural trends in supercomputing make such programming models increasingly attractive, and newer, more sophisticated models such as UPC++, Legion and Chapel that rely upon similar communication paradigms are gaining popularity.

GASNet-EX is a portable, open-source, high-performance communication library designed to efficiently support the networking requirements of PGAS runtime systems and other alternative models in future exascale machines. The library is an evolution of the popular GASNet communication system, building on 20 years of lessons learned. We describe several features and enhancements that have been introduced to address the needs of modern runtimes and exploit the hardware capabilities of emerging systems. Microbenchmark results demonstrate the RMA performance of GASNet-EX is competitive with several MPI implementations on current systems. GASNet-EX provides communication services that help to deliver speedups in HPC applications written using the UPC++ library, enabling new science on pre-exascale systems. 

Yang Liu, Xin Xing, Han Guo, Eric Michielssen, Pieter Ghysels, Xiaoye Sherry Li, "Butterfly factorization via randomized matrix-vector multiplications", SIAM J. Sci. Comput., March 9, 2021,

George Michelogiannakis, Min Yeh Teh, Madeleine Glick, John Shalf, Keren Bergman, Maximizing The Impact of Emerging Photonic Switches At The System Level, SPIE photonics west, March 2021,

George Michelogiannakis, Min Yeh Teh, Madeleine Glick, John Shalf, Keren Bergman, "Maximizing the impact of emerging photonic switches at the system level", SPIE 11692, Optical Interconnects XXI, 116920Z, March 2021,

Thijs Steel, Daan Camps, Karl Meerbergen, Raf Vandebril, "A Multishift, Multipole Rational QZ Method with Aggressive Early Deflation", SIAM Journal on Matrix Analysis and Applications, February 19, 2021, 42:753-774, doi: 10.1137/19M1249631

In the article “A Rational QZ Method” by D. Camps, K. Meerbergen, and R. Vandebril [SIAM J. Matrix Anal. Appl., 40 (2019), pp. 943--972], we introduced rational QZ (RQZ) methods. Our theoretical examinations revealed that the convergence of the RQZ method is governed by rational subspace iteration, thereby generalizing the classical QZ method, whose convergence relies on polynomial subspace iteration. Moreover the RQZ method operates on a pencil more general than Hessenberg---upper triangular, namely, a Hessenberg pencil, which is a pencil consisting of two Hessenberg matrices. However, the RQZ method can only be made competitive to advanced QZ implementations by using crucial add-ons such as small bulge multishift sweeps, aggressive early deflation, and optimal packing. In this paper we develop these techniques for the RQZ method. In the numerical experiments we compare the results with state-of-the-art routines for the generalized eigenvalue problem and show that the presented method is competitive in terms of speed and accuracy.

Y. Liu, W. M. Sid-Lakhdar, O. Marques, X. Zhu, C. Meng, J. W. Demmel, X. S. Li, "GPTune: multitask learning for autotuning exascale applications", PPoPP, February 17, 2021, doi: 10.1145/3437801.3441621

J-L Vay, Ann Almgren, LD Amorim, John Bell, L Fedeli, L Ge, K Gott, DP Grote, M Hogan, A Huebl, R Jambunathan, R Lehe, A Myers, C Ng, M Rowan, O Shapoval, M Thevenet, H Vincenti, E Yang, N Zaim, W Zhang, Y Zhao and E Zoni, "Modeling of a chain of three plasma accelerator stages with the WarpX electromagnetic PIC code on GPUs", Physics of Plasmas, February 9, 2021,

Donghun Koo, Jaehwan Lee, Jialin Liu, Eun-Kyu Byun, Jae-Hyuck Kwak, Glenn K Lockwood, Soonwook Hwang, Katie Antypas, Kesheng Wu, Hyeonsang Eom, "An empirical study of I/O separation for burst buffers in HPC systems", Journal of Parallel and Distributed Computing, 2021, 148:96-108, doi: 10.1016/j.jpdc.2020.10.007

Tuowen Zhao, Mary Hall, Hans Johansen, Samuel Williams, "Improving Communication by Optimizing On-Node Data Movement with Data Layout", PPoPP, February 2021,

R. Van Beeumen, L. Perisa, D. Kressner, C. Yang, "A Flexible Power Method for Solving Infinite Dimensional Tensor Eigenvalue Problems", January 30, 2021,

Ravi Naik, Brad Mitchell, Akel Hashim, John Mark Kreikebaum, David Santiago, Irfan Siddiqi, Contextual Characterization of the Cross-Resonance Gate on a Multi-Qubit Superconducting Quantum Processor, Bulletin of the American Physical Society, 2021,

Gerwin Koolstra, Noah Stevenson, Karthik Siva, William Livingston, Ravi Naik, John Steinmetz, Debmalya Das, Andrew Jordan, David Santiago, Irfan Siddiqi, Diagnosing Gate Errors in Superconducting Qubits Using Continuous Measurements (Experiment), Bulletin of the American Physical Society, 2021,

Brad Mitchell, Ravi Naik, Alexis Morvan, Akel Hashim, John Mark Kreikebaum, David Santiago, Irfan Siddiqi, Calibration of the Cross-Resonance Gate using Closed-Loop Optimal Control, Bulletin of the American Physical Society, 2021,

Robbie Sadre, Colin Ophus, Anstasiia Butko, Gunther H Weber, "Deep Learning Segmentation of Complex Features in Atomic-Resolution Phase Contrast Transmission Electron Microscopy Images", Microscopy and Microanalysis, 2021, doi: 10.1017/S1431927621000167

Hamish Carr, Oliver Rübel, Gunther H. Weber, James Ahrens, "Optimization and Augmentation for Data Parallel Contour Trees", IEEE Transactions on Visualization and Computer Graphics, 2021, doi: 10.1109/TVCG.2021.3064385

Hamish A. Carr, Gunther H. Weber, Christopher M. Sewell, Oliver R\ ubel, Patricia Fasel, James P. Ahrens, "Scalable Contour Tree Computation by Data Parallel Peak Pruning", Transactions on Visualization and Computer Graphics, 2021, 27:2437--2454, doi: 10.1109/TVCG.2019.2948616

Jan-Tobias Sohns, Gunther H. Weber, Christoph Garth, "Distributed Task-Parallel Topology-Controlled Volume Rendering", Topological Methods in Data Analysis and Visualization VI: Theory, Algorithms, and Applications, (Springer International Publishing: 2021) Pages: 55-69 doi: 10.1007/978-3-030-83500-2_4

M Tristram, AJ Banday, KM Górski, R Keskitalo, CR Lawrence, KJ Andersen, RB Barreiro, J Borrill, LPL Colombo, HK Eriksen, R Fernandez-Cobos, TS Kisner, E Martínez-González, B Partridge, D Scott, TL Svalheim, IK Wehus, Improved limits on the tensor-to-scalar ratio using BICEP and Planck, 2021,

N Aghanim, Y Akrami, M Ashdown, J Aumont, C Baccigalupi, M Ballardini, AJ Banday, RB Barreiro, N Bartolo, S Basak, R Battye, K Benabed, JP Bernard, M Bersanelli, P Bielewicz, JJ Bock, JR Bond, J Borrill, FR Bouchet, F Boulanger, M Bucher, C Burigana, RC Butler, E Calabrese, JF Cardoso, J Carron, A Challinor, HC Chiang, J Chluba, LPL Colombo, C Combet, D Contreras, BP Crill, F Cuttaia, P De Bernardis, G De Zotti, J Delabrouille, JM Delouis, E DI Valentino, JM DIego, O Doré, M Douspis, A Ducout, X Dupac, S Dusini, G Efstathiou, F Elsner, TA Enßlin, HK Eriksen, Y Fantaye, M Farhang, J Fergusson, R Fernandez-Cobos, F Finelli, F Forastieri, M Frailis, AA Fraisse, E Franceschi, A Frolov, S Galeotta, S Galli, K Ganga, RT Génova-Santos, M Gerbino, T Ghosh, J González-Nuevo, KM Górski, S Gratton, A Gruppuso, JE Gudmundsson, J Hamann, W Handley, FK Hansen, D Herranz, SR Hildebrandt, E Hivon, Z Huang, AH Jaffe, WC Jones, A Karakci, E Keihänen, R Keskitalo, K Kiiveri, J Kim, TS Kisner, L Knox, N Krachmalnicoff, M Kunz, H Kurki-Suonio, G Lagache, JM Lamarre, A Lasenby, M Lattanzi, CR Lawrence, M Le Jeune, P Lemos, J Lesgourgues, F Levrier, A Lewis, M Liguori, "Erratum: Planck 2018 results: VI. Cosmological parameters (Astronomy and Astrophysics (2020) 641 (A6) DOI: 10.1051/0004-6361/201833910)", Astronomy and Astrophysics, 2021, 652, doi: 10.1051/0004-6361/201833910e

MG Awan, S Hofmeyr, R Egan, N Ding, A Buluc, J Deslippe, L Oliker, K Yelick, "Accelerating Large Scale de novo Metagenome Assembly Using GPUs", International Conference for High Performance Computing, Networking, Storage and Analysis, SC, January 1, 2021, doi: 10.1145/3458817.3476212

G Puglisi, R Keskitalo, T Kisner, JD Borrill, Simulating Calibration and Beam Systematics for a Future CMB Space Mission with the TOAST Package, Research Notes of the AAS, Pages: 137--137 2021, doi: 10.3847/2515-5172/ac0823

M Tristram, AJ Banday, KM Górski, R Keskitalo, CR Lawrence, KJ Andersen, RB Barreiro, J Borrill, HK Eriksen, R Fernandez-Cobos, TS Kisner, E Martínez-González, B Partridge, D Scott, TL Svalheim, H Thommesen, IK Wehus, "Planck constraints on the tensor-to-scalar ratio", Astronomy and Astrophysics, 2021, 647, doi: 10.1051/0004-6361/202039585

Y Segawa, H Hirose, D Kaneko, M Hasegawa, S Adachi, P Ade, MAOA Faúndez, Y Akiba, K Arnold, J Avva, C Baccigalupi, D Barron, D Beck, S Beckman, F Bianchini, D Boettger, J Borrill, J Carron, S Chapman, K Cheung, Y Chinone, K Crowley, A Cukierman, T De Haan, M Dobbs, R Dunner, HE Bouhargani, T Elleflot, J Errard, G Fabbian, S Feeney, C Feng, T Fujino, N Galitzki, N Goeckner-Wald, J Groh, G Hall, N Halverson, T Hamada, M Hazumi, C Hill, L Howe, Y Inoue, J Ito, G Jaehnig, O Jeong, N Katayama, B Keating, R Keskitalo, S Kikuchi, T Kisner, N Krachmalnicoff, A Kusaka, AT Lee, D Leon, E Linder, LN Lowry, A Mangu, F Matsuda, Y Minami, J Montgomery, M Navaroli, H Nishino, J Peloton, ATP Pham, D Poletti, G Puglisi, C Raum, CL Reichardt, C Ross, M Silva-Feaver, P Siritanasak, R Stompor, A Suzuki, O Tajima, S Takakura, S Takatori, D Tanabe, GP Teply, C Tsai, C Verges, B Westbrook, Y Zhou, "Method for rapid performance validation of large TES bolometer array for POLARBEAR-2A using a coherent millimeter-wave source", AIP Conference Proceedings, 2021, 2319, doi: 10.1063/5.0038197

Ankur K. Gupta, Benjamin C. Gamoke, Krishnan Raghavachari, Interaction–Deletion: A Composite Energy Method for the Optimization of Molecular Systems Selectively Removing Specific Nonbonded Interactions, The Journal of Physical Chemistry A, Pages: 4668-4682 2021, doi: 10.1021/acs.jpca.1c02918

Tonglin Li, Suren Byna, Quincey Koziol, Houjun Tang, Jean Luca Bez, Qiao Kang, "h5bench: HDF5 I/O Kernel Suite for Exercising HPC I/O Patterns", Cray User Group (CUG) 2021, January 1, 2021,

Jean Luca Bez, Houjun Tang, Bing Xie, David Williams-Young, Rob Latham, Rob Ross, Sarp Oral, Suren Byna, "I/O Bottleneck Detection and Tuning: Connecting the Dots using Interactive Log Analysis", 2021 IEEE/ACM Sixth International Parallel Data Systems Workshop (PDSW), January 1, 2021, 15-22, doi: 10.1109/PDSW54622.2021.00008

G Guidi, M Ellis, A Buluç, K Yelick, D Culler, "10 years later: Cloud computing is closing the performance gap", ICPE 2021 - Companion of the ACM/SPEC International Conference on Performance Engineering, January 1, 2021, 41--48, doi: 10.1145/3447545.3451183

R Crystal-Ornelas, C Varadharajan, B Bond-Lamberty, K Boye, M Burrus, S Cholia, M Crow, J Damerow, R Devarakonda, KS Ely, A Goldman, S Heinz, V Hendrix, Z Kakalia, SC Pennington, E Robles, A Rogers, M Simmonds, T Velliquette, H Weierbach, P Weisenhorn, JN Welch, DA Agarwal, A Guide to Using GitHub for Developing and Versioning Data Standards and Reporting Formats, Earth and Space Science, 2021, doi: 10.1029/2021EA001797

JE Damerow, C Varadharajan, K Boye, EL Brodie, M Burrus, KD Chadwick, R Crystal-Ornelas, H Elbashandy, RJ Eloy Alves, KS Ely, AE Goldman, T Haberman, V Hendrix, Z Kakalia, KM Kemner, AB Kersting, N Merino, F O Brien, Z Perzan, E Robles, P Sorensen, JC Stegen, RL Walls, P Weisenhorn, M Zavarin, D Agarwal, Sample identifiers and metadata to support data management and reuse in multidisciplinary ecosystem sciences, Data Science Journal, 2021, doi: 10.5334/dsj-2021-011

Sabrina Amrouche, others, The Tracking Machine Learning challenge : Throughput phase, 2021,

Xiangyang Ju, others, Performance of a geometric deep learning pipeline for HL-LHC particle tracking, Eur. Phys. J. C, Pages: 876 2021, doi: 10.1140/epjc/s10052-021-09675-8

Jeremy Hewes, others, Graph Neural Network for Object Reconstruction in Liquid Argon Time Projection Chambers, EPJ Web Conf., Pages: 03054 2021, doi: 10.1051/epjconf/202125103054

Hannah Klion, Paul C. Duffell, Daniel Kasen, Eliot Quataert, "The effect of jet-ejecta interaction on the viewing angle dependence of kilonova light curves", Monthly Notices of the RAS, 2021, 502:865-875, doi: 10.1093/mnras/stab042

M Ellis, A Buluc, K Yelick, Scaling Generalized N-Body Problems, A Case Study from Genomics, ACM International Conference Proceeding Series, 2021, doi: 10.1145/3472456.3472517

M Norman, V Kellen, S Smallen, B Demeulle, S Strande, E Lazowska, N Alterman, R Fatland, S Stone, A Tan, K Yelick, E Van Dusen, J Mitchell, CloudBank: Managed Services to Simplify Cloud Access for Computer Science Research and Education, ACM International Conference Proceeding Series, 2021, doi: 10.1145/3437359.3465586

G Blelloch, W Dally, M Martonosi, U Vishkin, K Yelick, SPAA 21 panel paper: Architecture-friendly algorithms versus algorithm-friendly architectures, Annual ACM Symposium on Parallelism in Algorithms and Architectures, Pages: 1--7 2021, doi: 10.1145/3409964.3461780

I Nisa, P Pandey, M Ellis, L Oliker, A Buluc, K Yelick, Distributed-memory k-mer counting on GPUs, Proceedings - 2021 IEEE 35th International Parallel and Distributed Processing Symposium, IPDPS 2021, Pages: 527--536 2021, doi: 10.1109/IPDPS49936.2021.00061

M Ellis, A Buluç, K Yelick, Asynchrony versus bulk-synchrony for a generalized N-body problem from genomics, Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPOPP, Pages: 465--466 2021, doi: 10.1145/3437801.3441580

E Younis, K Sen, K Yelick, C Iancu, QFAST: Conflating Search and Numerical Optimization for Scalable Quantum Circuit Synthesis, Proceedings - 2021 IEEE International Conference on Quantum Computing and Engineering, QCE 2021, Pages: 232--243 2021, doi: 10.1109/QCE52317.2021.00041

G Guidi, M Ellis, A Buluç, KA Yelick, DE Culler, 10 Years Later: Cloud Computing is Closing the Performance Gap., ICPE (Companion), Pages: 41--48 2021,

O Selvitopi, B Brock, I Nisa, A Tripathy, K Yelick, A Buluç, "Distributed-memory parallel algorithms for sparse times tall-skinny-dense matrix multiplication", Proceedings of the International Conference on Supercomputing, January 2021, 431--442, doi: 10.1145/3447818.3461472

Nazanin Jafari, Oguz Selvitopi, Cevdet Aykanat, "Fast shared-memory streaming multilevel graph partitioning", Journal of Parallel and Distributed Computing, January 2021, 147:140-151, doi: https://doi.org/10.1016/j.jpdc.2020.09.004

SL Brantley, T Wen, DA Agarwal, JG Catalano, PA Schroeder, K Lehnert, C Varadharajan, J Pett-Ridge, M Engle, AM Castronova, RP Hooper, X Ma, L Jin, K McHenry, E Aronson, AR Shaughnessy, LA Derry, J Richardson, J Bales, EM Pierce, The future low-temperature geochemical data-scape as envisioned by the U.S. geochemical community, Computers and Geosciences, 2021, doi: 10.1016/j.cageo.2021.104933

K Yelick, D Agarwal, D Bard, J Shalf, A Almgren, W Bhimji, B Brown, J Carter, B Jong, D Doerfler, D Donofrio, C Guok, C Iancu, M Kiran, S Li, P Nugent, M Prabhat, L Ramakrishnan, D Vasudevan, N Wright, H Cademartori, K Antypas, K Kincade, 2019 Computing Sciences Strategic Plan, 2021, doi: 10.2172/1827673

J Müller, B Faybishenko, D Agarwal, S Bailey, C Jiang, Y Ryu, C Tull, L Ramakrishnan, Assessing data change in scientific datasets, Concurrency and Computation: Practice and Experience, 2021, doi: 10.1002/cpe.6245

J. Johansson, S. B. Cenko, O. D. Fox, S. Dhawan, A. Goobar, V. Stanishev, N. Butler, W. H. Lee, A. M. Watson, U. C. Fremling, M. M. Kasliwal, P. E. Nugent, T. Petrushevska, J. Sollerman, L. Yan, J. Burke, G. Hosseinzadeh, D. A. Howell, C. McCully, S. Valenti, Near-infrared Supernova Ia Distances: Host Galaxy Extinction and Mass-step Corrections Revisited, Astrophysical Journal, Pages: 237 2021, doi: 10.3847/1538-4357/ac2f9e

C. Ashall, J. Lu, E. Y. Hsiao, P. Hoeflich, M. M. Phillips, L. Galbany, C. R. Burns, C. Contreras, K. Krisciunas, N. Morrell, M. D. Stritzinger, N. B. Suntzeff, F. Taddia, J. Anais, E. Baron, P. J. Brown, L. Busta, A. Campillay, S. Castell\ on, C. Corco, S. Davis, G. Folatelli, F. F\ orster, W. L. Freedman, C. Gonzal\ ez, M. Hamuy, S. Holmbo, R. P. Kirshner, S. Kumar, G. H. Marion, P. Mazzali, T. Morokuma, P. E. Nugent, S. E. Persson, A. L. Piro, M. Roth, F. Salgado, D. J. Sand, J. Seron, M. Shahbandeh, B. J. Shappee, Carnegie Supernova Project: The First Homogeneous Sample of Super-Chandrasekhar-mass/2003fg-like Type Ia Supernovae, Astrophysical Journal, Pages: 205 2021, doi: 10.3847/1538-4357/ac19ac

Steve Schulze, Ofer Yaron, Jesper Sollerman, Giorgos Leloudas, Amit Gal, Angus H. Wright, Ragnhild Lunnan, Avishay Gal-Yam, Eran O. Ofek, Daniel A. Perley, Alexei V. Filippenko, Mansi M. Kasliwal, Shrinivas R. Kulkarni, James D. Neill, Peter E. Nugent, Robert M. Quimby, Mark Sullivan, Nora Linn Strotjohann, Iair Arcavi, Sagi Ben-Ami, Federica Bianco, Joshua S. Bloom, Kishalay De, Morgan Fraser, Christoffer U. Fremling, Assaf Horesh, Joel Johansson, Patrick L. Kelly, Nikola Kne\vzevi\ c, Sladjana Kne\vzevi\ c, Kate Maguire, Anders Nyholm, Sem\ eli Papadogiannakis, Tanja Petrushevska, Adam Rubin, Lin Yan, Yi Yang, Scott M. Adams, Filomena Bufano, Kelsey I. Clubb, Ryan J. Foley, Yoav Green, Jussi Harmanen, Anna Y. Q. Ho, Isobel M. Hook, Griffin Hosseinzadeh, D. Andrew Howell, Albert K. H. Kong, Rubina Kotak, Thomas Matheson, Curtis McCully, Dan Milisavljevic, Yen-Chen Pan, Dovi Poznanski, Isaac Shivvers, Sjoert van Velzen, Kars K. Verbeek, The Palomar Transient Factory Core-collapse Supernova Host-galaxy Sample. I. Host-galaxy Distribution Functions and Environment Dependence of Core-collapse Supernovae, Astrophysical Journal Supplement, Pages: 29 2021, doi: 10.3847/1538-4365/abff5e

Michael S. Medford, Peter Nugent, Danny Goldstein, Frank J. Masci, Igor Andreoni, Ron Beck, Michael W. Coughlin, Dmitry A. Duev, Ashish A. Mahabal, Reed L. Riddle, Removing Atmospheric Fringes from Zwicky Transient Facility i-band Images using Principal Component Analysis, Publications of the ASP, Pages: 064503 2021, doi: 10.1088/1538-3873/abfe9d

Charlotte Ward, Suvi Gezari, Sara Frederick, Erica Hammerstein, Peter Nugent, Sjoert van Velzen, Andrew Drake, Abigail Garc\ \ia-P\ erez, Immaculate Oyoo, Eric C. Bellm, Dmitry A. Duev, Matthew J. Graham, Mansi M. Kasliwal, Stephen Kaye, Ashish A. Mahabal, Frank J. Masci, Ben Rusholme, Maayane T. Soumagnac, Lin Yan, AGNs on the Move: A Search for Off-nuclear AGNs from Recoiling Supermassive Black Holes and Ongoing Galaxy Mergers with the Zwicky Transient Facility, Astrophysical Journal, Pages: 102 2021, doi: 10.3847/1538-4357/abf246

Chelsea E. Harris, Laura Chomiuk, Peter. E. Nugent, Tumbling Dice: Radio Constraints on the Presence of Circumstellar Shells around Type Ia Supernovae with Impact Near Maximum Light, Astrophysical Journal, Pages: 23 2021, doi: 10.3847/1538-4357/abe940

J. Johansson, A. Goobar, S. H. Price, A. Sagu\ es Carracedo, L. Della Bruna, P. E. Nugent, S. Dhawan, E. M\ ortsell, S. Papadogiannakis, R. Amanullah, D. Goldstein, S. B. Cenko, K. De, A. Dugas, M. M. Kasliwal, S. R. Kulkarni, R. Lunnan, Spectroscopy of the first resolved strongly lensed Type Ia supernova iPTF16geu, Monthly Notices of the RAS, Pages: 510-520 2021, doi: 10.1093/mnras/staa3829

Nora L. Strotjohann, Eran O. Ofek, Avishay Gal-Yam, Rachel Bruch, Steve Schulze, Nir Shaviv, Jesper Sollerman, Alexei V. Filippenko, Ofer Yaron, Christoffer Fremling, Jakob Nordin, Erik C. Kool, Dan A. Perley, Anna Y. Q. Ho, Yi Yang, Yuhan Yao, Maayane T. Soumagnac, Melissa L. Graham, Cristina Barbarino, Leonardo Tartaglia, Kishalay De, Daniel A. Goldstein, David O. Cook, Thomas G. Brink, Kirsty Taggart, Lin Yan, Ragnhild Lunnan, Mansi Kasliwal, Shri R. Kulkarni, Peter E. Nugent, Frank J. Masci, Philippe Rosnet, Scott M. Adams, Igor Andreoni, Ashot Bagdasaryan, Eric C. Bellm, Kevin Burdge, Dmitry A. Duev, Alison Dugas, Sara Frederick, Samantha Goldwasser, Matthew Hankins, Ido Irani, Viraj Karambelkar, Thomas Kupfer, Jingyi Liang, James D. Neill, Michael Porter, Reed L. Riddle, Yashvi Sharma, Phil Short, Francesco Taddia, Anastasios Tzanidakis, Jan van Roestel, Richard Walters, Zhuyun Zhuang, Bright, Months-long Stellar Outbursts Announce the Explosion of Interaction-powered Supernovae, Astrophysical Journal, Pages: 99 2021, doi: 10.3847/1538-4357/abd032

S. Yang, J. Sollerman, T. -W. Chen, E. C. Kool, R. Lunnan, S. Schulze, N. Strotjohann, A. Horesh, M. Kasliwal, T. Kupfer, A. A. Mahabal, F. J. Masci, P. Nugent, D. A. Perley, R. Riddle, B. Rusholme, Y. Sharma, Is supernova SN 2020faa an iPTF14hls look-alike?, Astronomy and Astrophysics, Pages: A22 2021, doi: 10.1051/0004-6361/202039440

C. Frohmaier, C. R. Angus, M. Vincenzi, M. Sullivan, M. Smith, P. E. Nugent, S. B. Cenko, A. Gal-Yam, S. R. Kulkarni, N. M. Law, R. M. Quimby, From core collapse to superluminous: the rates of massive stellar explosions from the Palomar Transient Factory, Monthly Notices of the RAS, Pages: 5142-5158 2021, doi: 10.1093/mnras/staa3607

Abigail Polin, Peter Nugent, Daniel Kasen, Nebular Models of Sub-Chandrasekhar Mass Type Ia Supernovae: Clues to the Origin of Ca-rich Transients, Astrophysical Journal, Pages: 65 2021, doi: 10.3847/1538-4357/abcccc

David Schuster, Ravi Naik, Srivatsan Chakram, Technologies for long-lived 3d multimode microwave cavities, 2021,

Alexis Morvan, VV Ramasesh, MS Blok, JM Kreikebaum, K O’Brien, L Chen, BK Mitchell, RK Naik, DI Santiago, I Siddiqi, "Qutrit randomized benchmarking", Physical Review Letters, 2021, 126:210504, doi: 10.1103/PhysRevLett.126.210504

Akash V Dixit, Srivatsan Chakram, Kevin He, Ankur Agrawal, Ravi K Naik, David I Schuster, Aaron Chou, "Searching for dark matter with a superconducting qubit", Physical Review Letters, 2021, 126:141302, doi: 10.1103/PhysRevLett.126.141302

Jean-Loup Ville, Alexis Morvan, Akel Hashim, Ravi K Naik, Bradley Mitchell, John-Mark Kreikebaum, Kevin P O Brien, Joel J Wallman, Ian Hincks, Joseph Emerson, others, Leveraging Randomized Compiling for the QITE Algorithm, arXiv preprint arXiv:2104.08785, 2021,

Kevin He, Srivatsan Chakram, Akash Dixit, Andrew Oriani, Ravi Naik, Nelson Leung, Hyeokshin Kwon, Riju Banerjee, Wen-Long Ma, Liang Jiang, others, State preparation and tomography in 3D multimode circuit QED, Bulletin of the American Physical Society, 2021,

Yilun Xu, Gang Huang, Ravi Naik, Alexis Morvan, Kasra Nowrouzi, Brad Mitchell, David Santiago, Irfan Siddiqi, Automatic two-qubit gate calibration with qubic, Bulletin of the American Physical Society, 2021,

Yilun Xu, Gang Huang, Jan Balewski, Ravi K Naik, Alexis Morvan, Brad Mitchell, Kasra Nowrouzi, David I Santiago, Irfan Siddiqi, Automatic Qubit Characterization and Gate Optimization with QubiC, arXiv preprint arXiv:2104.10866, 2021,

Noah Stevenson, Gerwin Koolstra, Karthik Siva, Ravi Naik, William Livingston, Shiva Lotfallahzadeh Barzili, Justin Dressel, Irfan Siddiqi, Tracking Non-Markovian Quantum Trajectories of a Superconducting Qubit from a Finite-Memory Bath, Bulletin of the American Physical Society, 2021,

John Steinmetz, Debmalya Das, Gerwin Koolstra, Noah Stevenson, Karthik Siva, William Livingston, Ravi Naik, David Santiago, Irfan Siddiqi, Andrew Jordan, Diagnosing Errors in Qubit Gates Using Continuous Measurements (Theory), Bulletin of the American Physical Society, 2021,

Alexis Morvan, Vinay Ramasesh, Machiel Blok, John Mark Kreikebaum, Kevin O Brien, Larry Chen, Ravi Naik, Brad Mitchell, David Santiago, Irfan Siddiqi, Qutrit Randomized Benchmarking on a Transmon Quantum Processor, Bulletin of the American Physical Society, 2021,

Joachim Cohen, Agustin Di Paolo, Larry Chen, Trevor Chistolini, John Mark Kreikebaum, Long Nguyen, Ravi Naik, David Santiago, Irfan Siddiqi, Alexandre Blais, Novel two-qubit gates for the light fluxonium qubit, Bulletin of the American Physical Society, 2021,

Robin Blume-Kohout, Susan Clark, Akel Hashim, Craig Hogle, Daniel Lobser, Ravi Naik, Timothy Proctor, Kenneth Rudinger, David Santiago, Irfan Siddiqi, others, Simultaneous Gate Set Tomography, Bulletin of the American Physical Society, 2021,

2020

Ling Jin, Alina Lazar, James Sears, Annika Todd, Alex Sim, Kesheng Wu, Hung-Chai Yang, C. Anna Spurlock, "Clustering Life Course to Understand the Heterogeneous Effects of Life Events, Gender and Generation on Habitual Travel Modes", IEEE Access, 2020, 1-17, doi: 10.1109/ACCESS.2020.3032328

B. Weinger, J. Kim, A. Sim, M. Nakashima, N. Moustafa, K. Wu, "Enhancing IoT Anomaly Detection Performance for Federated Learning", The 16th IEEE International Conference on Mobility, Sensing and Networking (IEEE MSN 2020), 2020, doi: 10.1109/MSN50589.2020.00045

B. Cho, T. Dayrit, Y. Gao, Z. Wang, T. Hong, A. Sim, K. Wu, "Effective Missing Value Imputation Methods for Building Monitoring Data", The 2nd International Workshop on Big Data Tools, Methods, and Use Cases for Innovative Scientific Discovery (BTSD 2020) in conjunction with IEEE International Conference on Big Data (IEEE BigData 2020), 2020, doi: 10.1109/BigData50022.2020.9378230

C. Yang, J. Brabec, L. Veis, D. B. Williams-Young, K. Kolwaski, "Solving Coupled Cluster Equations by the Newton Krylov Method", Frontiers in Chemistr, December 10, 2020, 8:987, doi: 10.3389/fchem.2020.590184

D. B. Williams-Young, W. A. de Jong, H. J. J. van Dam and C. Yang, "On the Efficient Evaluation of the Exchange Correlation Potential on Graphics Processing Unit Clusters", Frontiers in Chemistry, December 10, 2020, 8:951, doi: 10.3389/fchem.2020.581058

Veronica Rodr\iguez Tribaldos, Nathaniel J Lindsey, Shan Dou, Craig Ulrich, Michelle Robertson, Bin Dong, Vincent Dumont, Kesheng Wu, Inder Monga, Chris Tracy, others, Combining Ambient Noise and Distributed Acoustic Sensing (DAS) Deployed on Dark Fiber Networks for High-resolution Imaging at the Basin Scale, AGU Fall Meeting 2020, 2020,

V. Dumont, V. Rodriguez Tribaldos, J. Ajo-Franklin, K. Wu, "Deep Learning for Surface Wave Identification in Distributed Acoustic Sensing Data", IEEE BigData 2020, December 8, 2020,

J. Kim, A. Sim, J. Kim, K. Wu, "Botnets Detection Using Recurrent Variational Autoencoder", IEEE Global Communications Conference (Globecom 2020), 2020, doi: 10.1109/GLOBECOM42002.2020.9348169

William F.Godoy, Norbert Podhorszki, Ruonan Wang, Chuck Atkins, Greg Eisenhauer, Junmin Gu,Philip Davis,J ong Choi, Kai Germaschewski, Kevin Huck, Axel Huebl, Mark Kim, James Kress, Tahsin Kurc, Qing Liu, Jeremy Logan, Kshitij Mehta, George Ostrouchov, Manish Parashar, Franz Poeschel, David Pugmire, Eric Suchyta, KeichiTakahashi, NickThompson, Seiji Tsutsumi, Lipeng Wan, Matthew Wolf, Kesheng Wu, Scott Klasky, "ADIOS 2: The Adaptable Input Output System. A framework for high-performance data management", SoftwareX, 2020, 12,

Bashir Mohammed, Mariam Kiran, Dan Wang, Qiang Du, Russell Wilcox, "Deep Reinforcement Learning based Control for two-dimensional Coherent Combining", Laser Applications Conference, pp. JTu5A-7. Optical Society of America, 2020., OSA Publishing, December 1, 2020,

Dan Wang, Qiang Du, Tong Zhou, Bashir Mohammed, Mariam Kiran, Derun Li, Russell Wilcox, "Artificial Neural Networks Applied to Stabilization of 81-beam Coherent Combining", Advanced Solid State Lasers, Optical Society of America, December 1, 2020,

Divneet Kaur, Bashir Mohammed, Mariam Kiran, "NetGraf: A Collaborative Network Monitoring Stack for Network Experimental Testbeds", December 1, 2020,

Roel Van Beeumen, Khaled Z. Ibrahim, Gregory D. Kahanamoku-Meyer, Norman Y. Yao, Chao Yang, "Enhancing Scalability of a Matrix-Free Eigensolver for Studying Many-Body Localization", December 1, 2020,

Anastasiia Butko, George Michelogiannakis, Samuel Williams, Costin Iancu, David Donofrio, John Shalf, Jonathan Carter, Irfan Siddiqi, "Understanding Quantum Control Processor Capabilities and Limitations through Circuit Characterization", IEEE Conference on Rebooting Computing (ICRC), December 2020,

I. Monga, C. Guok, J. MacAuley, A. Sim, H. Newman, J. Balcas, P. DeMar, L. Winkler, T. Lehman, X. Yang, "SDN for End-to-end Networked Science at the Exascale", Future Generation Computer Systems, 2020, doi: 10.1016/j.future.2020.04.018

Madeleine Glick, Nathan C. Abrams, Qixiang Cheng, Min Yee Teh, Yu-Han Hung, Oscar Jimenez, Songtao Liu, Yoshitomo Okawachi, Xiang Meng, Leif Johansson, Manya Ghobadi, Larry Dennison, George Michelogiannakis, John Shalf, Alan Liu, John Bowers, Alex Gaeta, Michal Lipson, and Keren Bergman, "PINE: Photonic Integrated Networked Energy efficient datacenters (ENLITENED Program)", Journal of Optical Communications and Networking, 2020, 12:443-456,

B Mohammed, IU Awan, H Ugail, and Y Mohammad., "Failure Prediction using Machine Learning in a Virtualized HPC System and Application", Cluster Computing: The Journal of Networks, Software Tools and Applications, 2020, 471–485,

I. Srivastava, L. E. Silbert, G. S. Grest, J. B. Lechman, "Viscometric Flow of Dense Granular Materials under Controlled Pressure and Shear Stress", Journal of Fluid Mechanics, November 20, 2020, 907:A18, doi: 10.1017/jfm.2020.811

Chris Lawson, Jose Manuel Martí, Tijana Radivojevic, Sai Vamshi R. Jonnalagadda, Reinhard Gentz, Nathan J. Hillson, Sean Peisert, Joonhoon Kim, Blake A. Simons, Christopher J. Petzold, Steven W. Singer, Aindrila Mukhopadhyay, Deepti Tanjore, Josh Dunn, Héctor García Martín,, "Machine Learning for Metabolic Engineering: A Review", Metabolic Engineering, November 19, 2020,

Brett Weinger, Alex Sim (Advisor), John Wu (Advisor), Jinoh Kim (Advisor), "Enhancing IoT Anomaly Detection Performance for Federated Learning", International Conference for High Performance Computing, Networking, Storage and Analysis (SC’20), ACM Student Research Competition (SRC), 2020,

D. Bard, C. Snavely, L. Gerhardt, J. Lee, B. Totzke, K. Antypas, S. Byna, R. Cheema, S. Cholia, M. Day, B. Enders, A. Gaur, A. Greiner, T. Groves, M. Kiran, Q. Koziol, K. Rowland, C. Samuel, A. Selvarajan, A. Sim, D. Skinner, R. Thomas, G. Torok, The Superfacility project: automated pipelines for experiments and HPC, International Conference for High Performance Computing, Networking, Storage, and Analysis (SC20), State of the Practice (SOP), 2020,

B. Enders, D. Bard, C. Snavely, L. Gerhardt, J. Lee, B. Totzke, K. Antypas, S. Byna, R. Cheema, S. Cholia, M. Day, A. Gaur, A. Greiner, T. Groves, M. Kiran, Q. Koziol, K. Rowland, C. Samuel, A. Selvarajan, A. Sim, D. Skinner, R. Thomas, G. Torok, "Cross-facility science with the Superfacility Project at LBNL", 2nd Workshop on Large-scale Experiment-in-the-Loop Computing (XLOOP 2020), in conjunction with the International Conference for High Performance Computing, Networking, Storage, and Analysis (SC 20), 2020, doi: 10.1109/XLOOP51963.2020.00006

Min Yee Teh, Yu-Han Hung, George Michelogiannakis, Shijia Yan, Madeleine Glick, John Shalf, Keren Bergman, "TAGO: rethinking routing design in high performance reconfigurable networks", SC '20: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, November 2020,

Y. Zhao, R. Lehe, A. Myers, M. Thevenet, A. Huebl, C. B. Schroeder, and J.-L. Vay, "Modeling of emittance growth due to Coulomb collisions in plasma-based accelerators", Physics of Plasmas, November 17, 2020,

Tan Nguyen, Samuel Williams, Marco Siracusa, Colin MacLean, Douglas Doerfler, Nicholas J. Wright, "The Performance and Energy Efficiency Potential of FPGAs in Scientific Computing", (BEST PAPER) Performance Modeling, Benchmarking, and Simulation of High Performance Computer Systems (PMBS), November 2020,

Ignacio Losada Carreño, Raksha Ramakrishna, Anna Scaglione, Daniel Arnold, Ciaran Roberts, Sy-Toan Ngo, Sean Peisert, David Pinney, "SODA: An Irradiance-Based Tool to Generate Sub-Minute Solar Power Stochastic Time Series", Proceedings of the IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm), IEEE, November 2020,

Ciaran Roberts Sy-Toan Ngo, Alexandre Milesi, Sean Peisert, Daniel Arnold, Shammya Saha, Anna Scaglione, Nathan Johnson, Anton Kocheturov, Dmitriy Fradkin, "Deep Reinforcement Learning for DER Cyber-Attack Mitigation", Proceedings of the IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm), IEEE, November 2020,

Yunsong Wang, Charlene Yang, Steven Farrell, Yan Zhang, Thorsten Kurth, Samuel Williams, "Time-Based Roofline for Deep Learning Performance Analysis", Deep Learning on Supercomputing (DLonSC), November 2020,

Daan Camps, Roel Van Beeumen, "Approximate quantum circuit synthesis using block encodings", PHYSICAL REVIEW A, November 11, 2020, 102, doi: 10.1103/PhysRevA.102.052411

One of the challenges in quantum computing is the synthesis of unitary operators into quantum circuits with polylogarithmic gate complexity. Exact synthesis of generic unitaries requires an exponential number of gates in general. We propose a novel approximate quantum circuit synthesis technique by relaxing the unitary constraints and interchanging them for ancilla qubits via block encodings. This approach combines smaller block encodings, which are easier to synthesize, into quantum circuits for larger operators. Due to the use of block encodings, our technique is not limited to unitary operators and can be applied for the synthesis of arbitrary operators. We show that operators which can be approximated by a canonical polyadic expression with a polylogarithmic number of terms can be synthesized with polylogarithmic gate complexity with respect to the matrix dimension.

Katherine A. Yelick, Amir Kamil, Dan Bonachea, Paul H Hargrove, UPC++: An Asynchronous RMA/RPC Library for Distributed C++ Applications (SC20), Tutorial at the International Conference for High Performance Computing, Networking, Storage, and Analysis (SC20), November 10, 2020,

UPC++ is a C++ library supporting Partitioned Global Address Space (PGAS) programming. The UPC++ API offers low-overhead one-sided Remote Memory Access (RMA) and Remote Procedure Calls (RPC), along with future/promise-based asynchrony to express dependencies between asynchronous computations and data movement. UPC++ supports simple, regular data structures as well as more elaborate distributed structures where communication is fine-grained, irregular, or both. UPC++'s support for aggressive asynchrony enables the application to overlap communication to reduce communication wait times, and the GASNet communication layer provides efficient low-overhead RMA/RPC on HPC networks.

This tutorial introduces basic concepts and advanced optimization techniques of UPC++. We discuss the UPC++ memory and execution models and examine basic algorithm implementations. Participants gain hands-on experience incorporating UPC++ features into several application examples. We also examine two irregular applications (metagenomic assembler and multifrontal sparse solver) and describe how they leverage UPC++ features to optimize communication performance.

 

Hengjie Wang, Aparna Chandramowlishwaran, "Pencil: a pipelined algorithm for distributed stencils", SC20: International Conference for High Performance Computing, Networking, Storage and Analysis, 2020, 1--16,

Samuel Williams, Introduction to the Roofline Model, Supercomputing (SC), November 2020,

Charlene Yang, Accelerating Large-Scale Excited-State Studies in Materials Science, Supercomputing (SC), November 2020,

J. M. D. Lane, A. P. Thompson, I. Srivastava, G. S. Grest, T. Ao, B. Stoltzfus, K. Austin, H. Fan, D. Morgan, M. D. Knudson, "Scale and Rate in CdS Pressure-Induced Phase Transition", Shock Compression of Condensed Matter - 2019, November 4, 2020, 2272:100016, doi: 10.1063/12.0001041

N Krishnaswamy; M Kiran; B Mohammed; Singh Kunal, "Data-driven Learning to Predict WAN Network Traffic.", SNTA '20: Proceedings of the 3rd International Workshop on Systems and Network Telemetry and Analytics, November 3, 2020, 11-18, doi: 10.1145/3391812.3396268

Marco Siracusa, Marco Rabozzi, Emanuele Del Sozzo, Lorenzo Di Tucci, Samuel Williams, Marco D. Santambrogio, "A CAD-based methodology to optimize HLS code via the Roofline model", International Conference on Computer Aided Design (ICCAD), November 2020, doi: 10.1145/3400302.3415730

T Mallick, M Kiran, B Mohammed, Prasanna Balaprakash, "Dynamic Graph Neural Network for Traffic Forecasting in Wide Area Networks.", Machine Learning Big Data 2020, IEEE, November 2, 2020, 1-10, doi: 10.1109/BigData50022.2020.9512748

M Hocine, M Kiran, A Mercian, and B Mohammed, "Using Machine Learning for Intent-based provisioning in High-Speed Science Networks.", SNTA '20: Proceedings of the 3rd International Workshop on Systems and Network Telemetry and Analytics, November 2, 2020, 27-30, doi: 10.1145/3391812.3396269

Jonathan Blair Ajo-Franklin, Ver\ onica Rodr\ \iguez Tribaldos, Avinash Nayak, Nathaniel J Lindsey, Feng Cheng, Benxin Chi, Bin Dong, Kesheng Wu, Inder Monga, Distributed Acoustic Sensing (DAS) at the Plot to Basin Scale: Connecting Near-Surface Sensing and Seismology with a Common Observational Tool, AGU Fall Meeting 2020, 2020,

Ethan H. Smith, Marc G. Davis, Jeffery M. Larson, Costin Iancu, "LEAP: Scaling Numerical Optimization Based Synthesis Using an Incremental Approach", International Workshop of Quantum Computing Software at Supercomputing, November 2020,

John Bachan, Scott B. Baden, Dan Bonachea, Max Grossman, Paul H. Hargrove, Steven Hofmeyr, Mathias Jacquelin, Amir Kamil, Brian van Straalen, "UPC++ v1.0 Programmer’s Guide, Revision 2020.10.0", Lawrence Berkeley National Laboratory Tech Report, October 2020, LBNL 2001368, doi: 10.25344/S4HG6Q

UPC++ is a C++11 library that provides Partitioned Global Address Space (PGAS) programming. It is designed for writing parallel programs that run efficiently and scale well on distributed-memory parallel computers. The PGAS model is single program, multiple-data (SPMD), with each separate constituent process having access to local memory as it would in C++. However, PGAS also provides access to a global address space, which is allocated in shared segments that are distributed over the processes. UPC++ provides numerous methods for accessing and using global memory. In UPC++, all operations that access remote memory are explicit, which encourages programmers to be aware of the cost of communication and data movement. Moreover, all remote-memory access operations are by default asynchronous, to enable programmers to write code that scales well even on hundreds of thousands of cores. 

Drew Paine, Lavanya Ramakrishnan, "Understanding Interactive and Reproducible Computing With Jupyter Tools at Facilities", LBNL Technical Report, October 31, 2020, LBNL LBNL-2001355,

Increasingly Jupyter tools are being adopted and incorporated into High Performance Computing (HPC) and scientific user facilities. Adopting Jupyter tools enables more interactive and reproducible computational work at facilities across data life cycles. As the volume, variety, and scope of data grow, scientists need to be able to analyze and share results in user friendly ways. Human-centered research highlights design challenges around computational notebooks, and our qualitative user study shifts focus to better characterize how Jupyter tools are being used in HPC and science user facilities today. We conducted twenty-nine interviews, and obtained 103 survey responses from NERSC Jupyter users, to better understand the increasing role of interactive computing tools in DOE sponsored scientific work. We examine a range of issues that emerge using and supporting Jupyter in HPC ecosystems, including: how Jupyter is being used by scientists in HPC and user facility ecosystems; how facilities are purposefully supporting Jupyter in their ecosystems; feedback NERSC users have about the facility’s deployment, and, discuss features NERSC indicated would be helpful. We offer a variety of takeaways for staff supporting Jupyter at facilities, Project Jupyter and related open source communities, and funding agencies supporting interactive computing work.

V. Dumont, V. Rodriguez Tribaldos, J. Ajo-Franklin, K. Wu, "Deep Learning on Real Geophysical Data: A Case Study for Distributed Acoustic Sensing Research", NeurIPS "Machine Learning and the Physical Sciences" workshop, 2020,

Dan Bonachea, Amir Kamil, "UPC++ v1.0 Specification, Revision 2020.10.0", Lawrence Berkeley National Laboratory Tech Report, October 30, 2020, LBNL 2001367, doi: 10.25344/S4CS3F

UPC++ is a C++11 library providing classes and functions that support Partitioned Global Address Space (PGAS) programming. The key communication facilities in UPC++ are one-sided Remote Memory Access (RMA) and Remote Procedure Call (RPC). All communication operations are syntactically explicit and default to non-blocking; asynchrony is managed through the use of futures, promises and continuation callbacks, enabling the programmer to construct a graph of operations to execute asynchronously as high-latency dependencies are satisfied. A global pointer abstraction provides system-wide addressability of shared memory, including host and accelerator memories. The parallelism model is primarily process-based, but the interface is thread-safe and designed to allow efficient and expressive use in multi-threaded applications. The interface is designed for extreme scalability throughout, and deliberately avoids design features that could inhibit scalability.

Ayaz Akram, Anna Giannakou, Venkatesh Akella, Jason Lowe-Power, Sean Peisert, "Performance Analysis of Scientific Computing Workloads on Trusted Execution Environments", arXiv preprint arXiv:2010.13216, October 25, 2020,

J. Hu, J. K. Webb, T. R. Ayres, M. B. Bainbridge, J. D. Barrow, M. A. Barstow, J. C. Berengut, R. F. Carswell, V. Dumont, V. Dzuba, V. V. Flambaum, C. C. Lee, N. Reindl, S. P. Preval, W. -Ü. L. Tchang-Brillet, "Measuring the fine-structure constant on a white dwarf surface; a detailed analysis of Fe V absorption in G191−B2B", Monthly Notices of the Royal Astronomical Society, Volume 500, Issue 1, January 2021, Pages 1466–1475, October 23, 2020, doi: 10.1093/mnras/staa3066

Marc G. Davis, Ethan Smith, Ana Tudor, Koushik Sen, Irfan Siddiqi, Costin Iancu, "Towards Optimal Topology Aware Quantum Circuit Synthesis", 2020 IEEE International Conference on Quantum Computing and Engineering (QCE), Denver, CO, USA, IEEE, October 12, 2020, doi: 10.1109/QCE49297.2020.00036

We present an algorithm for compiling arbitrary unitaries into a sequence of gates native to a quantum processor. As CNOT gates are error-prone for the foreseeable Noisy-Intermediate-Scale Quantum devices era, our A* inspired algorithm minimizes their count while accounting for connectivity. We discuss the formulation of synthesis as a search problem as well as an algorithm to find solutions. For a workload of circuits with complexity appropriate for the NISQ era, we produce solutions well within the best upper bounds published in literature and match or exceed hand tuned implementations, as well as other existing synthesis alternatives. In particular, when comparing against state-of-the-art available synthesis packages we show 2.4× average (up to 5.3×) reduction in CNOT count. We also show how to re-target the algorithm for a different chip topology and native gate set while obtaining similar quality results. We believe that tools like ours can facilitate algorithmic exploration and guide gate set discovery for quantum processor designers, as well as being useful for optimization in the quantum compilation tool-chain.

T. Hernandez, R. Van Beeumen, M. Caprio, C. Yang, "A greedy algorithm for computing eigenvalues of a symmetric matrix with localized eigenvectors", Numerical Linear Algebra and Applications, October 9, 2020, 28:e2341, doi: https://doi.org/10.1002/nla.2341

A. Sim, Statistical Pattern Detection with Locally Exchangeable Measures, International Conference on Advanced Communications and Computation (INFOCOMP 2020), 2020,

Benjamin Nachman, Miroslav Urbanek, Wibe A. de Jong, Christian W. Bauer, "Unfolding quantum computer readout noise", npj Quantum Information, 2020, 6:84, doi: 10.1038/s41534-020-00309-7

Christopher Daley, Hadia Ahmed, Samuel Williams, Nicholas Wright, "A case study of porting HPGMG from CUDA to OpenMP target offload", The International Workshop on OpenMP (IWOMP), September 2020,

Daan Camps, Thomas Mach, Raf Vandebril, David Watkins, "On pole-swapping algorithms for the eigenvalue problem", ETNA - Electronic Transactions on Numerical Analysis, September 18, 2020, 52:480-508, doi: 10.1553/etna_vol52s480

Pole-swapping algorithms, which are generalizations of the QZ algorithm for the generalized eigenvalue problem, are studied. A new modular (and therefore more flexible) convergence theory that applies to all pole-swapping algorithms is developed. A key component of all such algorithms is a procedure that swaps two adjacent eigenvalues in a triangular pencil. An improved swapping routine is developed, and its superiority over existing methods is demonstrated by a backward error analysis and numerical tests. The modularity of the new convergence theory and the generality of the pole-swapping approach shed new light on bi-directional chasing algorithms, optimally packed shifts, and bulge pencils, and allow the design of novel algorithms.

A. P. Santos, D. S. Bolintineanu, G. S. Grest, J. B. Lechman, S. J. Plimpton, I. Srivastava, L. E. Silbert, "Granular Packings with Sliding, Rolling and Twisting Friction", Physical Review E, September 16, 2020, 102:032903, doi: 10.1103/PhysRevE.102.032903

Muaaz G Awan, Jack Deslippe, Aydin Buluc, Oguz Selvitopi, Steven Hofmeyr, Leonid Oliker, Katherine Yelick, "ADEPT: a domain independent sequence alignment strategy for gpu architectures", BMC Bioinformatics, September 2020, 21, doi: https://doi.org/10.1186/s12859-020-03720-1

D. Camps, R. Van Beeumen, C. Yang, "Quantum Fourier Transform Revisited", Numerical Linear Algebra and Applications, September 15, 2020, 28:e2331, doi: https://doi.org/10.1002/nla.2331

Sun, S., Pattyn, F., Simon, E., Albrecht, T., Cornford, S., Calov, R., . . . Zhang, T., "Antarctic ice sheet response to sudden and sustained ice-shelf collapse (ABUMIP)", Journal of Glaciology, September 14, 2020, 1-14, doi: 10.1017/jog.2020.67

Li Zhou, Lihao Yan, Mark A. Caprio, Weiguo Gao, Chao Yang, "Solving the k-sparse Eigenvalue Problem with Reinforcement Learning", September 9, 2020,

K. Klymko, A. Nonaka, J. B. Bell, S. P. Carney, A. L. Garcia, "Low Mach number fluctuating hydrodynamics model for ionic liquids", Physical Review Fluids, September 8, 2020, 5, doi: https://doi.org/10.1103/PhysRevFluids.5.093701

Drew Paine, Devarshi Ghoshal, Lavanya Ramakrishnan, "Experiences with a Flexible User Research Process to Build Data Change Tools", Journal of Open Research Software, September 1, 2020, doi: 10.5334/jors.284

Scientific software development processes are understood to be distinct from commercial software development practices due to uncertain and evolving states of scientific knowledge. Sustaining these software products is a recognized challenge, but under-examined is the usability and usefulness of such tools to their scientific end users. User research is a well-established set of techniques (e.g., interviews, mockups, usability tests) applied in commercial software projects to develop foundational, generative, and evaluative insights about products and the people who use them. Currently these approaches are not commonly applied and discussed in scientific software development work. The use of user research techniques in scientific environments can be challenging due to the nascent, fluid problem spaces of scientific work, varying scope of projects and their user communities, and funding/economic constraints on projects.

In this paper, we reflect on our experiences undertaking a multi-method user research process in the Deduce project. The Deduce project is investigating data change to develop metrics, methods, and tools that will help scientists make decisions around data change. There is a lack of common terminology since the concept of systematically measuring and managing data change is under explored in scientific environments. To bridge this gap we conducted user research that focuses on user practices, needs, and motivations to help us design and develop metrics and tools for data change. This paper contributes reflections and the lessons we have learned from our experiences. We offer key takeaways for scientific software project teams to effectively and flexibly incorporate similar processes into their projects.

Oguz Selvitopi*, Saliya Ekanayake*, Giulia Guidi, Georgios Pavlopoulos, Ariful Azad, Aydın Buluç, "Distributed Many-to-Many Protein Sequence Alignment Using Sparse Matrices", Proceedings of the International Conference for High Performance Computing, Networking, Storage, and Analysis (SC’20)., 2020,

(*:joint first authors)

Miroslav Urbanek, Benjamin Nachman, Wibe A. de Jong, "Error detection on quantum computers improving the accuracy of chemical calculations", Physical Review A, 2020, 102:022427, doi: 10.1103/PhysRevA.102.022427

Patricia Gonzalez-Guerrero, Tommy Tracy II, Xinfei Guo, Rahul Sreekumar, Marzieh Lenjani, Kevin Skadron, Mircea R Stan, "Towards on-node Machine Learning for Ultra-low-power Sensors Using Asynchronous Σ Δ Streams", Journal on Emerging Technologies in Computing Systems (JETC), August 26, 2020, doi: https://doi.org/10.1145/3404975

We propose a novel architecture to enable low-power, complex on-node data processing, for the next generation of sensors for the internet of things (IoT), smartdust, or edge intelligence. Our architecture combines near-analog-memory-computing (NAM) and asynchronous-computing-with-streams (ACS), eliminating the need for ADCs. ACS enables ultra-low power, massive computational resources required to execute on-node complex Machine Learning (ML) algorithms; while NAM addresses the memory-wall that represents a common bottleneck for ML and other complex functions. In ACS an analog value is mapped to an asynchronous stream that can take one of two logic levels (vhvl). This stream-based data representation enables area/power-efficient computing units such as a multiplier implemented as an AND gate yielding savings in power of ∼90% compared to digital approaches. The generation of streams for NAM and ACS in a brute force manner, using analog-to-digital-converters (ADCs) and digital-to-streams-converters, would sky-rocket the power-latency-energy cost making the approach impractical. Our NAM-ACS architecture eliminates expensive conversions, enabling an end-to-end processing on asynchronous streams data-path. We tailor the NAM-ACS architecture for random forest (RaF), an ML algorithm, chosen for its ability to classify using a reduced number of features. Simulations show that our NAM-ACS architecture enables 75% of savings in power compared with a single ADC, obtaining a classification accuracy of 85% using an RaF-inspired algorithm

Miroslav Urbanek, Daan Camps, Roel Van Beeumen, Wibe A. de Jong, "Chemistry on quantum computers with virtual quantum subspace expansion", Journal of Chemical Theory and Computation, 2020, 16:5425–5431, doi: 10.1021/acs.jctc.0c00447

Drew Paine, Devarshi Ghoshal, Lavanya Ramakrishnan, "Investigating Scientific Data Change with User Research Methods", August 20, 2020, LBNL LBNL-2001347,

Scientific datasets are continually expanding and changing due to fluctuations with instruments, quality assessment and quality control processes, and modifications to software pipelines. Datasets include minimal information about these changes or their effects requiring scientists manually assess modifications through a number of labor intensive and ad-hoc steps. The Deduce project is investigating data change to develop metrics, methods, and tools that will help scientists systematically identify and make decisions around data changes. Currently, there is a lack of understanding, and common practices, for identifying and evaluating changes in datasets since systematically measuring and managing data change is under explored in scientific work. We are conducting user research to address this need by exploring scientist's conceptualizations, behaviors, needs, and motivations when dealing with changing datasets. Our user research utilizes multiple methods to produce foundational, generative insights and evaluate research products produced by our team. In this paper, we detail our user research process and outline our findings about data change that emerge from our studies. Our work illustrates how scientific software teams can push beyond just usability testing user interfaces or tools to better probe the underlying ideas they are developing solutions to address.

George Michelogiannakis, Forecasting the future of HPC systems, RIPCON 2020, August 2020,

C. A. Spurlock, A. Gopal, J. Auld, P. Leiby, C. Sheppard, T. Wenzel, S. Belal, A. Duvall, A. Enam, S. Fujita, A. Henao, L. Jin, E. Kontou, A. Lazar, Z. Needell, C. Rames, T. Rashidi, J. Sears, A. Sim, M. Stinson, M. Taylor, A. Todd-Blick, O. Verbas, V. Walker, J. Ward, G. Wong-Parodi, K. Wu, H.-C. Yang, "SMART Mobility, Mobility Decision Science Capstone Report", Vehicle Technologies Office (VTO), Office of Energy Efficiency and Renewable Energy (EERE), US Department of Energy, 2020,

Samuel Williams, The Roofline Model: A Bridge between Computer Science, Applied Math, and Computational Science, SciDAC Meeting, July 2020,

Matthew Li, Nicolas Chan, Viraat Chandra, Krishna Muriki, "Cluster Usage Policy Enforcement Using Slurm Plugins and an HTTP API", Practice and Experience in Advanced Research Computing, New York, NY, USA, Association for Computing Machinery, July 26, 2020, 232–238, doi: 10.1145/3311790.3397341

Managing and limiting cluster resource usage is a critical task for computing clusters with a large number of users. By enforcing usage limits, cluster managers are able to ensure fair availability for all users, bill users accordingly, and prevent the abuse of cluster resources. As this is such a common problem, there are naturally many existing solutions. However, to allow for greater control over usage accounting and submission behavior in Slurm, we present a system composed of: a web API which exposes accounting data; Slurm plugins that communicate with a REST-like HTTP implementation of that API; and client tools that use it to report usage. Key advantages of our system include a customizable resource accounting formula based on job parameters, preemptive blocking of user jobs at submission time, project-level and user-level resource limits, and support for the development of other web and command-line clients that query the extensible web API. We deployed this system on Berkeley Research Computing’s institutional cluster, Savio, allowing us to automatically collect and store accounting data, and thereby easily enforce our cluster usage policy.

John Shalf, George Michelogiannakis, Brian Austin, Taylor Groves, Manya Ghobadi, Larry Dennison, Tom Gray, Yiwen Shen, Min Yee Teh, Madeleine Glick, and Keren Bergman, "Photonic Memory Disaggregation in Datacenters", OSA Advanced Photonics Congress (AP), July 2020,

Bin Dong, Ver\ onica Rodr\ \iguez Tribaldos, Xin Xing, Suren Byna, Jonathan Ajo-Franklin, Kesheng Wu, "DASSA: Parallel DAS Data Storage and Analysis for Subsurface Event Detection", 2020 IEEE International Parallel and Distributed Processing Symposium (IPDPS), July 14, 2020, 254--263,

Gustavo Chavez, Elizaveta Rebrova, Yang Liu, Pieter Ghysels, Xiaoye Sherry Li, "Scalable and memory-efficient kernel ridge regression", 34th IEEE International Parallel and Distributed Processing Symposium, July 14, 2020,

G. Z. Pastorello, C. Trotta, E. Canfora, H. Chu, D. Christianson, Y.-W. Cheah, C. Poindexter, J. Chen, A. Elbashandy, M. Humphrey, P. Isaac, D. Polidori, M. Reichstein, A. Ribeca, C. van Ingen, N. Vuichard, L. Zhang, B. Amiro, C. Ammann, M. A. Arain, J. Ardö, T. Arkebauer, S. K. Arndt, N. Arriga, M. Aubinet, M. Aurela, D. Baldocchi, A. Barr, E. Beamesderfer, L. B. Marchesini, O. Bergeron, J. Beringer, C. Bernhofer, D. Berveiller, D. Billesbach, T. A. Black, P. D. Blanken, G. Bohrer, J. Boike, P. V. Bol stad, D. Bonal, J.-M. Bonnefond, D. R. Bowling, R. Bracho, J. Brodeur, C. Brümmer, N. Buchmann, B. Burban, S. P. Burns, P. Buysse, P. Cale, M. Cavagna, P. Cellier, S. Chen, I. Chini, T. R. Chris tensen, J. Cleverly, A. Collalti, C. Consalvo, B. D. Cook, D. Cook, C. Coursolle, E. Cremonese, P. S. Curtis, E. D’Andrea, H. da Rocha, X. Dai, K. J. Davis, B. D. Cinti, A. de Grandcourt, A. D. Ligne, R. C. D. Oliveira, N. Delpierre, A. R. Desai, C. M. D. Bella, P. di Tommasi, H. Dolman, F. Domingo, G. Dong, S. Dore, P. Duce, E. Dufrêne, A. Dunn, J. Dušek, D. Eamus, U. Eichelmann, H. A. M. ElKhidir, W. Eugster, C. M. Ewenz, B. Ewers, D. Famulari, S. Fares, I. Feigenwinter, A. Feitz, R. Fensholt, G. Fil ippa, M. Fischer, J. Frank, M. Galvagno, M. Gharun, D. Gianelle, B. Gielen, B. Gioli, A. Gitelson, I. Goded, M. Goeckede, A. H. Goldstein, C. M. Gough, M. L. Goulden, A. Graf, A. Griebel, C. Gruening, T. Grünwald, A. Hammerle, S. Han, X. Han, B. U. Hansen, C. Hanson, J. Hatakka, Y. He, M. Hehn, B. Heinesch, N. Hinko-Najera, L. Hörtnagl, L. Hutley, A. Ibrom, H. Ikawa, M. Jackowicz-Korczynski, D. Janouš, W. Jans, R. Jassal, S. Jiang, T. Kato, M. Khomik, J. Klatt, A. Knohl, S. Knox, H. Kobayashi, G. Koerber, O. Kolle, Y. Kosugi, A. Kotani, A. Kowalski, B. Kruijt, J. Kurbatova, W. L. Kutsch, H. Kwon, S. Launiainen, T. Laurila, B. Law, R. Leuning, Y. Li, M. Liddell, J.-M. Limousin, M. Lion, A. J. Liska, A. Lohila, A. López-Ballesteros, E. López-Blanco, B. Loubet, D. Loustau, A. Lucas-Moffat, J. Lüers, S. Ma, C. Macfarlane, V. Magliulo, R. Maier, I. Mammarella, G. Manca, B. Marcolla, H. A. Margolis, S. Mar ras, W. Massman, M. Mastepanov, R. Matamala, J. H. Matthes, F. Mazzenga, H. McCaughey, I. McHugh, A. M. S. McMillan, L. Merbold, W. Meyer, T. Meyers, S. D. Miller, S. Minerbi, U. Moderow, R. K. Monson, L. Montagnani, C. E. Moore, E. Moors, V. Moreaux, C. Moureaux, J. W. Munger, T. Nakai, J. Neirynck, Z. Nesic, G. Nicolini, A. Noormets, M. Northwood, M. Nosetto, Y. Nouvellon, K. Novick, W. Oechel, J. E. Olesen, J.-M. Ourcival, S. A. Papuga, F.-J. Parmentier, E. Paul-Limoges, M. Pavelka, M. Peichl, E. Pendall, R. P. Phillips, K. Pilegaard, N. Pirk, G. Posse, T. Powell, H. Prasse, S. M. Prober, S. Ram bal, U. Rannik, N. Raz-Yaseef, D. Reed, V. R. de Dios, N. Restrepo-Coupe, B. R. Reverter, M. Roland, S. Sabbatini, T. Sachs, S. R. Saleska, E. P. S.-C. nete, Z. M. Sanchez-Mejia, H. P. Schmid, M. Schmidt, K. Schneider, F. Schrader, I. Schroder, R. L. Scott, P. Sedlák, P. Serrano-Ortíz, C. Shao, P. Shi, I. Shironya, L. Siebicke, L. Šigut, R. Silberstein, C. Sirca, D. Spano, R. Steinbrecher, R. M. Stevens, C. Sturtevant, A. Suyker, T. Tagesson, S. Takanashi, Y. Tang, N. Tapper, J. Thom, F. Tiedemann, M. Tomassucci, J.-P. Tuovinen, S. Urbanski, R. Valentini, M. van der Molen, E. van Gorsel, K. van Huissteden, A. Varlagin, J. Verfaillie, T. Vesala, C. Vincke, D. Vitale, N. Vygodskaya, J. P. Walker, E. Walter-Shea, H. Wang, R. Weber, S. Westermann, C. Wille, S. Wofsy, G. Wohlfahrt, S. Wolf, W. Woodgate, Y. Li, R. Zampedri, J. Zhang, G. Zhou, D. Zona, D. Agarwal, S. Biraud, M. Torn, D. Papale, "The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data", Scientific Data, 2020, 7:225, doi: 10.1038/s41597-020-0534-3

Samuel Williams, Introduction to the Roofline Model, NERSC NVIDIA Roofline Hackathon, July 2020,

Yang Liu, Eric Michielssen, "Parallel fast time-domain integral-equation methods for transient electromagnetic analysis", Parallel Algorithms in Computational Science and Engineering, ( July 7, 2020)

Oguz Selvitopi, Seher Acer, Murat Manguoğlu, Cevdet Aykanat, "The Effect of Various Sparsity Structures on Parallelism and Algorithms to Reveal Those Structures", Parallel Algorithms in Computational Science and Engineering, (Birkhäuser, Cham: July 2020) Pages: 35-62 doi: https://doi.org/10.1007/978-3-030-43736-7_2

I. Srivastava, D. S. Bolintineanu, J. B. Lechman, S. A. Roberts, "Controlling Binder Adhesion to Impact Electrode Mesostructure and Transport", ACS Applied Materials & Interfaces, July 2, 2020, 12:34919–3493, doi: 10.1021/acsami.0c08251

Samuel Williams, Introduction to the Roofline Model, NERSC GPU For Science Workshop, July 2020,

Leen Alawieh, Jonathan Goodman, John B. Bell, "Iterative construction of Gaussian process surrogate models for Bayesian inference", Journal of Statistical Planning and Inference, 2020,

J. Galen Wang, Qi Li, Xiaoguang Peng, Gregory B. McKenna, Roseanna N. Zia, "“Dense diffusion” in colloidal glasses: short-ranged long-time self-diffusion as a mechanistic model for relaxation dynamics", Soft Matter, June 30, 2020, doi: 10.1039/D0SM00999G

Sunggon Kim, Alex Sim, Kesheng Wu, Suren Byna, Yongseok Son, Hyeonsang Eom, "Towards hpc i/o performance prediction through large-scale log analysis", Proceedings of the 29th International Symposium on High-Performance Parallel and Distributed Computing (HPDC 2020), 2020, 77--88, doi: 10.1145/3369583.3392678

Gaurav R Ghosal, Dipak Ghosal, Alex Sim, Aditya V Thakur, Kesheng Wu, "A Deep Deterministic Policy Gradient Based Network Scheduler For Deadline-Driven Data Transfers", Proceedings of International Federation for Information Processing (IFIP) Networking Conference (NETWORKING 2020), 2020, 253--261,

Jeeyung Kim, Alex Sim, Jinoh Kim, Kesheng Wu, Jaegyoon Hahm, "Transfer Learning Approach for Botnet Detection Based on Recurrent Variational Autoencoder", ACM International Workshop on ​System and Network Telemetry and Analysis (SNTA 2020), in conjunction with The 29th ACM International Symposium on High-Performance Parallel and Distributed Computing (HPDC 2020), 2020, 41--47, doi: 10.1145/3391812.3396273

Jiwoo Bang, Chungyong Kim, Kesheng Wu, Alex Sim, Suren Byna, Sunggon Kim, Hyeonsang Eom, "HPC Workload Characterization Using Feature Selection and Clustering", ACM International Workshop on ​System and Network Telemetry and Analysis (SNTA 2020), in conjunction with The 29th ACM International Symposium on High-Performance Parallel and Distributed Computing (HPDC 2020), 2020, 33--40, doi: 10.1145/3391812.3396270

Nan Ding, Victor W. Lee, Wei Xue, Weimin Zheng, "APMT: an automatic hardware counter-based performance modeling tool for HPC applications", CCF Transactions on High Performance Computing, June 24, 2020,

M. Nakashima, A. Sim, J. Kim, "Evaluation of Deep Learning Models for Network PerformancePrediction for Scientific Facilities", the 3rd ACM International Workshop on System and Network Telemetry and Analysis (SNTA) 2020, in conjunction with The 29th ACM International Symposium on High-Performance Parallel and Distributed Computing (HPDC), 2020, doi: 10.1145/3391812.3396272

S. Bhandari, A. K. Kukreja, A. Lazar, A. Sim, K. Wu, "Feature Selection and Tree-based Classification for Wireless Intrusion Detection", the 3rd ACM International Workshop on System and Network Telemetry and Analysis (SNTA) 2020, in conjunction with The 29th ACM International Symposium on High-Performance Parallel and Distributed Computing (HPDC), 2020, doi: 10.1145/3391812.3396274

Bin Wang, Dai Wang, Rongxin Yin, Doug Black, Cy Chan, "Predictive management of electric vehicles in a community microgrid", 2020 IEEE Transportation Electrification Conference & Expo (ITEC), June 23, 2020,

E. Motheau, J. Wakefield, "Investigation of finite-volume methods to capture shocks and turbulence spectra in compressible flows", Commun. in Appl. Math. and Comput. Sci, 15-1 (2020), 1--36, June 3, 2020,

Jonathan R Madsen, Muaaz G Awan, Hugo Brunie, Jack Deslippe, Rahul Gayatri, Leonid Oliker, Yunsong Wang, Charlene Yang, Samuel Williams, "TiMemory: Modular Performance Analysis for HPC", International Supercomputing Conference (ISC), June 2020, doi: 10.1007/978-3-030-50743-5_22

Amir Kamil, John Bachan, Scott B. Baden, Dan Bonachea, Rob Egan, Paul Hargrove, Steven Hofmeyr, Mathias Jacquelin, Kathy Yelick, UPC++: An Asynchronous RMA/RPC Library for Distributed C++ Applications (ALCF'20), Argonne Leadership Computing Facility (ALCF) Webinar Series, May 27, 2020,

UPC++ is a C++ library providing classes and functions that support Partitioned Global Address Space (PGAS) programming. The UPC++ API offers low-overhead one-sided RMA communication and Remote Procedure Calls (RPC), along with futures and promises. These constructs enable the programmer to express dependencies between asynchronous computations and data movement. UPC++ supports the implementation of simple, regular data structures as well as more elaborate distributed data structures where communication is fine-grained, irregular, or both. The library’s support for asynchrony enables the application to aggressively overlap and schedule communication and computation to reduce wait times.

UPC++ is highly portable and runs on platforms from laptops to supercomputers, with native implementations for HPC interconnects. As a C++ library, it interoperates smoothly with existing numerical libraries and on-node programming models (e.g., OpenMP, CUDA).

In this webinar, hosted by DOE’s Exascale Computing Project and the ALCF, we will introduce basic concepts and advanced optimization techniques of UPC++. We will discuss the UPC++ memory and execution models and walk through basic algorithm implementations. We will also look at irregular applications and show how they can take advantage of UPC++ features to optimize their performance.

ALCF'20 Event page

ALCF'20 Video recording

Houjun Tang, Suren Byna, Bin Dong, Quincey Koziol, "Parallel Query Service for Object-centric Data Management Systems", 2020 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), IEEE, May 18, 2020, 406-415,

Benjamin Brock, Aydin Buluç, Timothy G Mattson, Scott McMillan, José E Moreira, Roger Pearce, Oguz Selvitopi, Trevor Steil, "Considerations for a Distributed GraphBLAS API", IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), IEEE, May 2020, doi: 10.1109/IPDPSW50202.2020.00048

Oguz Selvitopi, Md Taufique Hussain, Ariful Azad, Aydın Buluç, "Optimizing high performance markov clustering for pre-exascale architectures", IEEE International Parallel and Distributed Processing Symposium (IPDPS), IEEE, May 2020, doi: 10.1109/IPDPS47924.2020.00022

Yu-Hang Tang, Oguz Selvitopi, Doru Thom Popovici, Aydın Buluç, "A high-throughput solver for marginalized graph kernels on GPU", IEEE International Parallel and Distributed Processing Symposium (IPDPS), IEEE, May 2020, doi: 10.1109/IPDPS47924.2020.00080

Qiao Kang, Alex Sim, Peter Nugent, Sunwoo Lee, Wei-keng Liao, Ankit Agrawal, Alok Choudhary, Kesheng Wu, "Predicting Resource Requirement in Intermediate Palomar Transient Factory Workflow", 20th IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGRID 2020), 2020, 619--628, doi: 10.1109/CCGrid49817.2020.00-31

H. Sung, J. Bang, C. Kim, H. Kim, A. Sim, G. K. Lockwood, H. Eom, "BBOS: Efficient HPC Storage Management via Burst Buffer Over-Subscription", the 20th IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGrid 2020), 2020, doi: 10.1109/CCGrid49817.2020.00-79

Shao-Jun Dong, Chao Wang, Yong-Jian Han, Chao Yang and Lixin He, "Stable diagonal stripes in the t–J model at nhbar = 1/8 doping from fPEPS calculations", npj Quantum Materials, May 8, 2020, 5:28, doi: https://doi.org/10.1038/s41535-020-0226-4

S. B. Kachuck, D. F. Martin, J. N. Bassis, S. F. Price, "Rapid viscoelastic deformation slows marine ice sheet instability at Pine Island Glacier", Geophysical Research Letters, May 7, 2020, 47, doi: 10.1029/2019GL086446

S. B. Kachuck, D. F. Martin, J. N. Bassis, S. F. Price, "Rapid viscoelastic deformation slows marine ice sheet instability at Pine Island Glacier", Geophysical Research Letters, May 7, 2020, 47, doi: 10.1029/2019GL086446

Bogdan Copos, Sean Peisert, "Catch Me If You Can: Using Power Analysis to Identify HPC Activity", arXiv:2005.03135 [cs.CR], May 6, 2020,

Daniel F. Martin, Stephen L. Cornford, Esmond G Ng, Effect of Improved Bedrock Geometry on Antarctic Vulnerability to Regional Ice Shelf Collapse, European Geosciences Union 2020 General Assembly, May 5, 2020,

Andrew Wells, James Parkinson, Daniel F Martin, Three-dimensional convection, phase change, and solute transport in mushy sea ice, European Geosciences Union 2020 General Assembly,, May 4, 2020,

H. Masia-Roig, J. A. Smiga, D. Budker, V. Dumont, Z. Grujic, D. Kim, D. F. Jackson Kimball, V. Lebedev, M. Monroy, S. Pustelny, T. Scholtes, P. C. Segura, Y. K. Semertzidis, Y. Chang Shin, J. E. Stalnaker, I. Sulai, A. Weis, A. Wickenbrock, "Analysis method for detecting topological defect dark matter with a global magnetometer network", Physics of the Dark Universe, Volume 28, 100494, May 2020, doi: 10.1016/j.dark.2020.100494

C. T. Kelley, J. Bernholc, E. L. Briggs, S. Hamilton, L. Lin and C. Yang, "Mesh Independence of the Generalized Davidson Algorithm", Journal of Computational Physics, May 1, 2020, 409:109322, doi: https://doi.org/10.1016/j.jcp.2020.109322

Kai-Hsin Liou, Chao Yang and James R.Chelikowsky, "Scalable Implementation of Polynomial Filering for Density Functional Theory Calculation in PARSEC", Computer Physics Communications, April 28, 2020, In press, doi: https://doi.org/10.1016/j.cpc.2020.107330

M. R. Wilczynska, J. K. Webb, M. Bainbridge, S. E. I. Bosman, J. D. Barrow, R. F. Carswell, M. P. Dabrowski, V. Dumont, A. C. Leite, C. Lee, K. Leszczynska, J. Liske, K. Marosek, C. J. A. P. Martins, D. Milakovic, P. Molaro, L. Pasquini, "Four direct measurements of the fine-structure constant 13 billion years ago", Science Advances, Volume 6, No. 17, eaay9672, April 24, 2020, doi: 10.1126/sciadv.aay9672

Christine T. Wolf, Drew Paine, "Sensemaking Practices in the Everyday Work of AI/ML Software Engineering", IEEE/ACM 42nd International Conference on Software Engineering Workshops (ICSEW’20), ACM, April 5, 2020, doi: 10.1145/3387940.3391496

Li Zhou, Chao Yang, Weiguo Gao, Talita Perciano, Karen M. Davies, Nicholas K. Sauter, "Subcellular structure segmentation from cryo-electron tomograms via machine learning", PLOS Journal of Computational Biology, April 2, 2020, submitte, doi: doi: https://doi.org/10.1101/2020.04.09.034025

I. Srivastava, J. B. Lechman, G. S. Grest, L. E. Silbert, "Evolution of Internal Granular Structure at the Flow-Arrest Transition", Granular Matter, March 23, 2020, 22:41, doi: 10.1007/s10035-020-1003-6

Georgios Tzimpragos, Dilip Vasudevan, Nestan Tsiskaridze, George Michelogiannakis, Advait Madhavan, Jennifer Volk, John Shalf, Timothy Sherwood, "A Computational Temporal Logic for Superconducting Accelerators", ASPLOS '20: Proceedings of the Twenty-Fifth International Conference on Architectural Support for Programming Languages and Operating Systems, March 2020,

F. Henneke, L. Lin, C. Vorwerk, C. Draxl, R. Klein and C. Yang, "Fast optical absorption spectra calculations for periodic solid state systems", Communications in Applied Mathematics and Computational Science, March 16, 2020, in press,

John Bachan, Scott B. Baden, Dan Bonachea, Max Grossman, Paul H. Hargrove, Steven Hofmeyr, Mathias Jacquelin, Amir Kamil, Brian van Straalen, "UPC++ v1.0 Programmer’s Guide, Revision 2020.3.0", Lawrence Berkeley National Laboratory Tech Report, March 2020, LBNL 2001269, doi: 10.25344/S4P88Z

UPC++ is a C++11 library that provides Partitioned Global Address Space (PGAS) programming. It is designed for writing parallel programs that run efficiently and scale well on distributed-memory parallel computers. The PGAS model is single program, multiple-data (SPMD), with each separate constituent process having access to local memory as it would in C++. However, PGAS also provides access to a global address space, which is allocated in shared segments that are distributed over the processes. UPC++ provides numerous methods for accessing and using global memory. In UPC++, all operations that access remote memory are explicit, which encourages programmers to be aware of the cost of communication and data movement. Moreover, all remote-memory access operations are by default asynchronous, to enable programmers to write code that scales well even on hundreds of thousands of cores.

John Bachan, Dan Bonachea, Amir Kamil, "UPC++ v1.0 Specification, Revision 2020.3.0", Lawrence Berkeley National Laboratory Tech Report, March 12, 2020, LBNL 2001268, doi: 10.25344/S4T01S

UPC++ is a C++11 library providing classes and functions that support Partitioned Global Address Space (PGAS) programming. The key communication facilities in UPC++ are one-sided Remote Memory Access (RMA) and Remote Procedure Call (RPC). All communication operations are syntactically explicit and default to non-blocking; asynchrony is managed through the use of futures, promises and continuation callbacks, enabling the programmer to construct a graph of operations to execute asynchronously as high-latency dependencies are satisfied. A global pointer abstraction provides system-wide addressability of shared memory, including host and accelerator memories. The parallelism model is primarily process-based, but the interface is thread-safe and designed to allow efficient and expressive use in multi-threaded applications. The interface is designed for extreme scalability throughout, and deliberately avoids design features that could inhibit scalability.

Samuel Williams, Charlene Yang, Yunsong Wang, Roofline Performance Modeling for HPC and Deep Learning Applications, NVIDIA GPU Technology Conference (GTC), March 2020,

Muammar El Khatib, Wibe De Jong, Feature Extraction Using Semi-Supervised Deep Learning., APS March 2020, March 5, 2020,

Features are defined as measurable properties that characterize observed phenomena and represent a key part of machine learning (ML) algorithms. In materials sciences, ML has successfully accelerated atomistic simulations using man-engineered features for tasks such as energy or atomic forces predictions. These features fulfill physics constraints such as rotational and translational invariance, uniqueness and, locality (the sum of local contributions reconstructs a global quantity). However, these ML models are known to perform poorly when operating out of the training set regime because features are not representative of the underlying structure of the data. This could be improved if features are extracted with advanced hybrid architectures e.g. a variational autoencoder that is trained with physics constraints introduced with an external task and a loss function. We will explore how the use of semi-supervised learning techniques can be a powerful tool for the extraction of features for atomistic simulations. All results shown herein can be reproduced with ML4Chem: a free software package for machine learning in chemistry and materials sciences.

Marzieh Lenjani, Patricia Gonzalez, Elaheh Sadredini, Shuangchen Li, Yuan Xie, Ameen Akel, Sean Eilert, Mircea R Stan, Kevin Skadron, "Fulcrum: a simplified control and access mechanism toward flexible and practical in-situ accelerators", International Symposium on High Performance Computer Architecture (HPCA), San Diego, CA, USA, IEEE, February 22, 2020, doi: 10.1109/HPCA47549.2020.00052

In-situ approaches process data very close to the memory cells, in the row buffer of each subarray. This minimizes data movement costs and affords parallelism across subarrays. However, current in-situ approaches are limited to only row-wide bitwise (or few-bit) operations applied uniformly across the row buffer. They impose a significant overhead of multiple row activations for emulating 32-bit addition and multiplications using bitwise operations and cannot support operations with data dependencies or based on predicates. Moreover, with current peripheral logic, communication among subarrays is inefficient, and with typical data layouts, bits in a word are not physically adjacent. The key insight of this work is that in-situ, single-word ALUs outperform in-situ, parallel, row-wide, bitwise ALUs by reducing the number of row activations and enabling new operations and optimizations. Our proposed lightweight access and control mechanism, Fulcrum, sequentially feeds data into the single-word ALU and enables operations with data dependencies and operations based on a predicate. For algorithms that require communication among subarrays, we augment the peripheral logic with broadcasting capabilities and a previously-proposed method for low-cost inter-subarray data movement. The sequential processor also enables overlapping of broadcasting and computation, and reuniting bits that are physically adjacent. In order to realize true subarray-level parallelism, we introduce a lightweight column-selection mechanism through shifting one-hot encoded values. This technique enables independent column selection in each subarray. We integrate Fulcrum with Compress Express Link (CXL), a new interconnect standard. Fulcrum with one memory stack delivers on average (up to) 23.4 (76) speedup over a server-class GPU, NVIDIA P100, with three stacks of HBM2 memory, (ii) 70 (228) times speedup per memory stack over the GPU, and (iii) 19 (178.9) times speedup per memory stack over an ideal model of the GPU, which only accounts for the overhead of data movement.

Ross Gegan, Christina Mao, Dipak Ghosal, Matt Bishop, Sean Peisert, "Anomaly Detection for Science DMZ Using System Performance Data", Proceedings of the 2020 IEEE International Conference on Computing, Networking and Communications (ICNC 2020), Big Island, HI, February 2020, doi: 10.1109/ICNC47757.2020.9049695

Nan Ding, Samuel Williams, Yang Liu, Xiaoye S. Li, "Leveraging One-Sided Communication for Sparse Triangular Solvers", 2020 SIAM Conference on Parallel Processing for Scientific Computing, February 14, 2020,

Levermann, A., Winkelmann, R., Albrecht, T., Goelzer, H., Golledge, N. R., Greve, R., Huybrechts, P., Jordan, J., Leguy, G., Martin, D., Morlighem, M., Pattyn, F., Pollard, D., Quiquet, A., Rodehacke, C., Seroussi, H., Sutter, J., Zhang, T., Van Breedam, J., Calov, R., DeConto, R., Dumas, C., Garbe, J., Gudmundsson, G. H., Hoffman, M. J., Humbert, A., Kleiner, T., Lipscomb, W. H., Meinshausen, M., Ng, E., Nowicki, S. M. J., Perego, M., Price, S. F., Saito, F., Schlegel, N.-J., Sun, S., van de Wal, R. S. W, "Projecting Antarctica’s contribution to future sea level rise from basal ice shelf melt using linear response functions of 16 ice sheet models (LARMIP-2)", Earth System Dynamics, February 14, 2020, 11:35–76, doi: 10.5194/esd-11-35-2020

Drew Paine, Charlotte P. Lee, "Coordinative Entities: Forms of Organizing in Data Intensive Science", Journal of Computer Supported Cooperative Work, February 11, 2020, doi: 10.1007/s10606-020-09372-2

Revathi Jambunathan, Deborah Levin, "A Self-Consistent Open Boundary Condition for Fully Kinetic Plasma Thruster Plume Simulations", IEEE Transactions on Plasma Science, February 7, 2020, doi: 10.1109/TPS.2020.2968887

Amir Kamil, John Bachan, Scott B. Baden, Dan Bonachea, Rob Egan, Paul Hargrove, Steven Hofmeyr, Mathias Jacquelin, Kathy Yelick, UPC++: A PGAS/RPC Library for Asynchronous Exascale Communication in C++ (ECP'20), Tutorial at Exascale Computing Project (ECP) Annual Meeting 2020, February 6, 2020,

UPC++ is a C++ library providing classes and functions that support Partitioned Global Address Space (PGAS) programming. The UPC++ API offers low-overhead one-sided RMA communication and Remote Procedure Calls (RPC), along with futures and promises. These constructs enable the programmer to express dependencies between asynchronous computations and data movement. UPC++ supports the implementation of simple, regular data structures as well as more elaborate distributed data structures where communication is fine-grained, irregular, or both. The library’s support for asynchrony enables the application to aggressively overlap and schedule communication and computation to reduce wait times.

UPC++ is highly portable and runs on platforms from laptops to supercomputers, with native implementations for HPC interconnects. As a C++ library, it interoperates smoothly with existing numerical libraries and on-node programming models (e.g., OpenMP, CUDA).

In this tutorial we will introduce basic concepts and advanced optimization techniques of UPC++. We will discuss the UPC++ memory and execution models and walk through basic algorithm implementations. We will also look at irregular applications and show how they can take advantage of UPC++ features to optimize their performance.

ECP'20 Event page

Brandon Runnels, Vinamra Agrawal, Weiqun Zhang, Ann Almgren, "Massively parallel finite difference elasticity using a block-structured adaptive mesh refinement with a geometric multigrid solver", submitted for publication, 2020,

Samuel Williams, Introduction to the Roofline Model, ECP Annual Meeting, February 2020,

Charlene Yang, Hierarchical Roofline Analysis on GPUs, ECP Annual Meeting, February 2020,

Samuel Williams, Roofline on GPUs (Advanced Topics), ECP Annual Meeting, February 2020,

Charlene Yang, Hierarchical Roofline Analysis on CPUs, ECP Annual Meeting, February 2020,

Jack Deslippe, Guiding Optimization with the Roofline Model, ECP Annual Meeting, February 2020,

Amir Kamil, John Bachan, Dan Bonachea, Paul H. Hargrove, Erich Strohmaier and Daniel Waters, "UPC++: Asynchronous RMA and RPC Communication for Exascale Applications (ECP'20)", Poster at Exascale Computing Project (ECP) Annual Meeting 2020, February 2020,

Nicholas Z. Liu, Daniel R. Ladiges, Jason Nassios, John E. Sader, "Acoustic flows in a slightly rarefied gas", Physical Review Fluids, February 4, 2020, 5:043401,

Paul H. Hargrove, Dan Bonachea, "GASNet-EX: RMA and Active Message Communication for Exascale Programming Models (ECP'20)", Poster at Exascale Computing Project (ECP) Annual Meeting 2020, February 2020,

Suren Byna, M. Scot Breitenfeld, Bin Dong, Quincey Koziol, Elena Pourmal, Dana Robinson, Jerome Soumagne, Houjun Tang, Venkatram Vishwanath, and Richard Warren, "ExaHDF5: Delivering Efficient Parallel I/O on Exascale Computing Systems", Journal of Computer Science and Technology 2020, 35(1): 145-160, February 2, 2020, doi: 10.1007/s11390-020-9822-9

S Abimbola, B Mohammed, M Sibusiso, IU Awan, and Jules Pagna Disso, "A Framework for Distributed Denial of Service Attack Detection and Reactive Countermeasure in Software Defined Network", 2019 7th IEEE International Conference on Future Internet of Things and Cloud (FiCloud), January 30, 2020, doi: 10.1109/FiCloud.2019.00019

Sergi Molins, Cyprien Soulaine, Nikolaos I. Prasianakis, Aida Abbasi, Philippe Poncet, Anthony J. C. Ladd, Vitalii Starchenko, Sophie Roman, David Trebotich, Hamdi Tchelepi, Carl I. Steefel, "Simulation of mineral dissolution at the pore scale with evolving fluid-solid interfaces: review of approaches and benchmark problem set", Computational Geosciences, January 23, 2020, doi: 10.1007/s10596-019-09903-x

Katherine Yelick, Aydın Buluç, Muaaz Awan, Ariful Azad, Benjamin Brock, Rob Egan, Saliya Ekanayake, Marquita Ellis, Evangelos Georganas, Giulia Guidi, Steven Hofmeyr, Oguz Selvitopi, Cristina Teodoropol, Leonid Oliker, "The parallelism motifs of genomic data analysis", Philosophical Transactions of The Royal Society A: Mathematical, Physical and Engineering Sciences, 2020,

F. Alexander, A. Almgren, J. Bell, A. Bhattacharjee, J. Chen, P. Colella, D. Daniel, J. DeSlippe, L. Diachin, E. Draeger, A. Dubey, T. Dunning, T. Evans, I. Foster, M. Francois, T. Germann, M. Gordon, S. Habib, M. Halappanavar, S. Hamilton, W. Hart, Z. Huang, A. Hungerford, D. Kasen, P. Kent, T. Kolev, D. Kothe, A. Kronfeld, Y. Luo, P. Mackenzie, D. McCallen, B. Messer, S. Mniszewski, C. Oehmen, A. Perazzo, D. Perez, D. Richard, W. Rider, R. Rieben, K. Roche, A. Siegel, M. Sprague, C. Steefel, R. Stevens, M. Syamlal, M. Taylor, J. Turner, J.-L. Vay, A. Voter, T. Windus and K. Yelick, "Exascale applications: skin in the game", Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2020,

L. Jin, A. Lazar, J. Sears, A. Todd, A. Sim, K. Wu, C. A. Spurlock, "Life Course as a Contextual System to Investigate the Effects of Life Events, Gender, and Generation on Travel Mode Use", Transportation Research Board (TRB) 99th Annual Meeting, 2020,

James R.G. Parkinson, Daniel F. Martin, Andrew J. Wells, Richard F. Katz, "Modelling binary alloy solidification with adaptive mesh refinement", Journal of Computational Physics: X, January 7, 2020, 5, doi: 10.1016/j.jcpx.2019.100043

R. Van Beeumen, G. D. Kahanamoku-Meyer, N. Y. Yao and C. Yang, "A scalable matrix-free iterative eigensolver for studying many-body localization", HPCAsia2020: Proceedings of the International Conference on High Performance Computing in Asia-Pacific Region, ACM, January 7, 2020, 179-187, doi: 10.1145/3368474.3368497

H. Childs, S. Ahern, J. Ahrens, A. C. Bauer, J. Bennett, E. W. Bethel, P.-T. Bremer, E. Brugger, J. Cottam, M. Dorier, S. Dutta, J. Favre, T. Fogal, S. Frey, C. Garth, B. Geveci, W. F. Godoy, C. D. Hansen, C. Harrison, B. Hentschel, J. Insley, C. Johnson, S. Klasky, A. Knoll, J. Kress, M. Larsen, J. Lofstead, K.-L. Ma, P. Malakar, J. Meredith, K. Moreland, P. Navratil, P. O Leary, M. Parashar, V. Pascucci, J. Patchett, T. Peterka, S. Petruzza, N. Podhorszki, D. Pugmire, M. Rasquin, S. Rizzi, D. H. Rogers, S. Sane, F. Sauer, R. Sisneros, H.-W. Shen, W. Usher, R. Vickery, V. Vishwanath, I. Wald, R. Wang, G. H. Weber, B. Whitlock, M. Wolf, H. Yu, S. B. Ziegler, "A Terminology for In Situ Visualization and Analysis Systems", International Journal of High Performance Computing Applications, 2020, 34:676--691, doi: 10.1177/1094342020935991

Anna-Pia Lohfink, Florian Wetzels, Jonas Lukasczyk, Gunther H. Weber, Christoph Garth, "Fuzzy Contour Trees: Alignment and Joint Layout of Multiple Contour Trees", Computer Graphics Forum (Special Issue, Proceedings Eurographics/IEEE Symposium on Visualization), 2020, 39:343--355, doi: 10.1111/cgf.13985

Sugeerth Murugesan, Kristofer Bouchard, Jesse Brown, Mariam Kiran, Dan Lurie, Bernd Hamann, Gunther H. Weber, "State-based Network Similarity Visualization", Information Visualization, 2020, 19:96--113, doi: 10.1177/1473871619882019

Jonas Lukasczyk, Christoph Garth, Gunther H. Weber, Tim Biedert, Ross Maciejewski, Heike Leitte, "Dynamic Nested Tracking Graphs", IEEE Transactions on Visualization and Computer Graphics (Proceedings IEEE VIS 2019), 2020, 26:249--258, doi: 10.1109/TVCG.2019.2934368

Hamish A. Carr, Julien Tierney, Gunther H. Weber, "Pathological and Test Cases For Reeb Analysis", Topological Methods in Data Analysis and Visualization V: Theory, Algorithms, and Applications", (Springer International Publishing: 2020) Pages: 103--120 doi: 10.1007/978-3-030-43036-8_7

TC-S Collaboration, :, K Abazajian, GE Addison, P Adshead, Z Ahmed, D Akerib, A Ali, SW Allen, D Alonso, M Alvarez, MA Amin, A Anderson, KS Arnold, P Ashton, C Baccigalupi, D Bard, D Barkats, D Barron, PS Barry, JG Bartlett, RB Thakur, N Battaglia, R Bean, C Bebek, AN Bender, BA Benson, F Bianchini, CA Bischoff, L Bleem, JJ Bock, S Bocquet, KK Boddy, JR Bond, J Borrill, FR Bouchet, T Brinckmann, ML Brown, S Bryan, V Buza, K Byrum, CH Caimapo, E Calabrese, V Calafut, R Caldwell, JE Carlstrom, J Carron, T Cecil, A Challinor, CL Chang, Y Chinone, H-MS Cho, A Cooray, W Coulton, TM Crawford, A Crites, A Cukierman, F-Y Cyr-Racine, T de Haan, J Delabrouille, M Devlin, E Di Valentino, M Dierickx, M Dobbs, S Duff, J Dunkley, C Dvorkin, J Eimer, T Elleflot, J Errard, T Essinger-Hileman, G Fabbian, C Feng, S Ferraro, JP Filippini, R Flauger, B Flaugher, AA Fraisse, A Frolov, N Galitzki, PA Gallardo, S Galli, K Ganga, M Gerbino, V Gluscevic, N Goeckner-Wald, D Green, D Grin, E Grohs, R Gualtieri, JE Gudmundsson, I Gullett, N Gupta, S Habib, M Halpern, NW Halverson, S Hanany, K Harrington, M Hasegawa, M Hasselfield, M Hazumi, K Heitmann, S Henderson, B Hensley, C Hill, JC Hill, R Hlozek, S-PP Ho, T Hoang, G Holder, W Holzapfel, J Hood, J Hubmayr, KM Huffenberger, H Hui, K Irwin, O Jeong, BR Johnson, WC Jones, JH Kang, KS Karkare, N Katayama, R Keskitalo, T Kisner, L Knox, BJ Koopman, A Kosowsky, J Kovac, ED Kovetz, S Kuhlmann, C-L Kuo, A Kusaka, A Lähteenmäki, CR Lawrence, AT Lee, A Lewis, D Li, E Linder, M Loverde, A Lowitz, P Lubin, MS Madhavacheril, A Mantz, G Marques, F Matsuda, P Mauskopf, H McCarrick, J McMahon, PD Meerburg, J-B Melin, F Menanteau, J Meyers, M Millea, J Mohr, L Moncelsi, M Monzani, T Mroczkowski, S Mukherjee, J Nagy, T Namikawa, F Nati, T Natoli, L Newburgh, MD Niemack, H Nishino, B Nord, V Novosad, R O Brient, S Padin, S Palladino, B Partridge, D Petravick, E Pierpaoli, L Pogosian, K Prabhu, C Pryke, G Puglisi, B Racine, A Rahlin, MS Rao, M Raveri, CL Reichardt, M Remazeilles, G Rocha, NA Roe, A Roy, JE Ruhl, M Salatino, B Saliwanchik, E Schaan, A Schillaci, B Schmitt, MM Schmittfull, D Scott, N Sehgal, S Shandera, BD Sherwin, E Shirokoff, SM Simon, A Slosar, D Spergel, TS Germaine, ST Staggs, A Stark, GD Starkman, R Stompor, C Stoughton, A Suzuki, O Tajima, GP Teply, K Thompson, B Thorne, P Timbie, M Tomasi, M Tristram, G Tucker, C Umiltà, A van Engelen, EM Vavagiakis, JD Vieira, AG Vieregg, K Wagoner, B Wallisch, G Wang, S Watson, B Westbrook, N Whitehorn, EJ Wollack, WLK Wu, Z Xu, HYE Yang, S Yasini, VG Yefremenko, KW Yoon, E Young, C Yu, A Zonca, CMB-S4: Forecasting Constraints on Primordial Gravitational Waves, 2020,

Petar Hristov, Gunther H. Weber, Hamish A. Carr, Oliver R\ ubel, James P. Ahrens, "Data Parallel Hypersweeps for In Situ Topological Analysis", Proceedings of the 10th IEEE Symposium on Large Data Analysis and Visualization (LDAV), 2020, 12--21, doi: 10.1109/LDAV51489.2020.00008

Y Akrami, M Ashdown, J Aumont, C Baccigalupi, M Ballardini, AJ Banday, RB Barreiro, N Bartolo, S Basak, K Benabed, JP Bernard, M Bersanelli, P Bielewicz, JR Bond, J Borrill, FR Bouchet, C Burigana, E Calabrese, JF Cardoso, B Casaponsa, HC Chiang, C Combet, D Contreras, BP Crill, F Cuttaia, P De Bernardis, A De Rosa, G De Zotti, J Delabrouille, E Di Valentino, JM Diego, O Doré, M Douspis, X Dupac, TA Enßlin, HK Eriksen, R Fernandez-Cobos, F Finelli, M Frailis, E Franceschi, A Frolov, S Galeotta, S Galli, K Ganga, RT Génova-Santos, M Gerbino, J González-Nuevo, KM Górski, A Gruppuso, JE Gudmundsson, W Handley, D Herranz, E Hivon, Z Huang, AH Jaffe, WC Jones, E Keihänen, R Keskitalo, K Kiiveri, J Kim, TS Kisner, N Krachmalnicoff, M Kunz, H Kurki-Suonio, JM Lamarre, M Lattanzi, CR Lawrence, M Le Jeune, F Levrier, M Liguori, PB Lilje, V Lindholm, M López-Caniego, JF Maciás-Pérez, D Maino, N Mandolesi, A Marcos-Caballero, M Maris, PG Martin, E Martínez-González, S Matarrese, N Mauri, JD McEwen, A Mennella, M Migliaccio, D Molinari, A Moneti, L Montier, G Morgante, A Moss, P Natoli, L Pagano, D Paoletti, F Perrotta, V Pettorino, F Piacentini, G Polenta, JP Rachen, M Reinecke, M Remazeilles, "Planck intermediate results: LVI. Detection of the CMB dipole through modulation of the thermal Sunyaev-Zeldovich effect: Eppur si muove II", Astronomy and Astrophysics, 2020, 644, doi: 10.1051/0004-6361/202038053

Y Akrami, M Ashdown, J Aumont, C Baccigalupi, M Ballardini, AJ Banday, RB Barreiro, N Bartolo, S Basak, K Benabed, JP Bernard, M Bersanelli, P Bielewicz, JR Bond, J Borrill, FR Bouchet, C Burigana, E Calabrese, P Carvalho, HC Chiang, BP Crill, F Cuttaia, A De Rosa, G De Zotti, J Delabrouille, JM Delouis, E Di Valentino, JM Diego, X Dupac, S Dusini, G Efstathiou, F Elsner, TA Enßlin, HK Eriksen, R Fernandez-Cobos, F Finelli, AA Fraisse, E Franceschi, A Frolov, S Galeotta, K Ganga, M Gerbino, J González-Nuevo, KM Górski, S Gratton, A Gruppuso, JE Gudmundsson, W Handley, FK Hansen, D Herranz, E Hivon, M Hobson, Z Huang, WC Jones, E Keihänen, R Keskitalo, J Kim, TS Kisner, N Krachmalnicoff, M Kunz, H Kurki-Suonio, JM Lamarre, A Lasenby, M Lattanzi, CR Lawrence, M Le Jeune, F Levrier, PB Lilje, V Lindholm, M López-Caniego, YZ Ma, JF Macías-Pérez, G Maggio, N Mandolesi, A Marcos-Caballero, M Maris, PG Martin, E Martínez-González, S Matarrese, N Mauri, JD McEwen, M Migliaccio, D Molinari, A Moneti, L Montier, G Morgante, P Natoli, D Paoletti, B Partridge, F Perrotta, V Pettorino, F Piacentini, G Polenta, JL Puget, JP Rachen, M Reinecke, M Remazeilles, A Renzi, G Rocha, G Roudier, "Planck intermediate results: LV. Reliability and thermal properties of high-frequency sources in the Second Planck Catalogue of Compact Sources", Astronomy and Astrophysics, 2020, 644, doi: 10.1051/0004-6361/201936794

TL Svalheim, KJ Andersen, R Aurlien, R Banerji, M Bersanelli, S Bertocco, M Brilenkov, M Carbone, LPL Colombo, HK Eriksen, MK Foss, C Franceschet, U Fuskeland, S Galeotta, M Galloway, S Gerakakis, E Gjerløw, B Hensley, D Herman, M Iacobellis, M Ieronymaki, HT Ihle, JB Jewell, A Karakci, E Keihänen, R Keskitalo, G Maggio, D Maino, M Maris, S Paradiso, B Partridge, M Reinecke, A-S Suur-Uski, D Tavagnacco, H Thommesen, DJ Watts, IK Wehus, A Zacchei, BeyondPlanck XV. Polarized foreground emission between 30 and 70 GHz, 2020,

E Gjerløw, HT Ihle, S Galeotta, KJ Andersen, R Aurlien, R Banerji, M Bersanelli, S Bertocco, M Brilenkov, M Carbone, LPL Colombo, HK Eriksen, MK Foss, C Franceschet, U Fuskeland, M Galloway, S Gerakakis, B Hensley, D Herman, M Iacobellis, M Ieronymaki, JB Jewell, A Karakci, E Keihänen, R Keskitalo, G Maggio, D Maino, M Maris, S Paradiso, B Partridge, M Reinecke, A-S Suur-Uski, TL Svalheim, D Tavagnacco, H Thommesen, DJ Watts, IK Wehus, A Zacchei, BeyondPlanck VII. Bayesian estimation of gain and absolute calibration for CMB experiments, 2020,

HT Ihle, M Bersanelli, C Franceschet, E Gjerløw, KJ Andersen, R Aurlien, R Banerji, S Bertocco, M Brilenkov, M Carbone, LPL Colombo, HK Eriksen, JR Eskilt, MK Foss, U Fuskeland, S Galeotta, M Galloway, S Gerakakis, B Hensley, D Herman, M Iacobellis, M Ieronymaki, JB Jewell, A Karakci, E Keihänen, R Keskitalo, G Maggio, D Maino, M Maris, A Mennella, S Paradiso, B Partridge, M Reinecke, M San, A-S Suur-Uski, TL Svalheim, D Tavagnacco, H Thommesen, DJ Watts, IK Wehus, A Zacchei, BeyondPlanck VI. Noise characterization and modelling, 2020,

E Keihänen, A-S Suur-Uski, KJ Andersen, R Aurlien, R Banerji, M Bersanelli, S Bertocco, M Brilenkov, M Carbone, LPL Colombo, HK Eriksen, MK Foss, C Franceschet, U Fuskeland, S Galeotta, M Galloway, S Gerakakis, E Gjerløw, B Hensley, D Herman, M Iacobellis, M Ieronymaki, HT Ihle, JB Jewell, A Karakci, R Keskitalo, G Maggio, D Maino, M Maris, A Mennella, S Paradiso, B Partridge, M Reinecke, TL Svalheim, D Tavagnacco, H Thommesen, M Tomasi, DJ Watts, IK Wehus, A Zacchei, BeyondPlanck II. CMB map-making through Gibbs sampling, 2020,

B Collaboration, KJ Andersen, R Aurlien, R Banerji, M Bersanelli, S Bertocco, M Brilenkov, M Carbone, LPL Colombo, HK Eriksen, JR Eskilt, MK Foss, C Franceschet, U Fuskeland, S Galeotta, M Galloway, S Gerakakis, E Gjerløw, B Hensley, D Herman, M Iacobellis, M Ieronymaki, HT Ihle, JB Jewell, A Karakci, E Keihänen, R Keskitalo, G Maggio, D Maino, M Maris, A Mennella, S Paradiso, B Partridge, M Reinecke, M San, A-S Suur-Uski, TL Svalheim, D Tavagnacco, H Thommesen, DJ Watts, IK Wehus, A Zacchei, BeyondPlanck I. Global Bayesian analysis of the Planck Low Frequency Instrument data, 2020,

A Zeni, G Guidi, M Ellis, N Ding, MD Santambrogio, S Hofmeyr, A Buluc, L Oliker, K Yelick, "LOGAN: High-Performance GPU-Based X-Drop Long-Read Alignment", Proceedings - 2020 IEEE 34th International Parallel and Distributed Processing Symposium, IPDPS 2020, 2020, 462--471, doi: 10.1109/IPDPS47924.2020.00055

Y Akrami, KJ Andersen, M Ashdown, C Baccigalupi, M Ballardini, AJ Banday, RB Barreiro, N Bartolo, S Basak, K Benabed, JP Bernard, M Bersanelli, P Bielewicz, JR Bond, J Borrill, C Burigana, RC Butler, E Calabrese, B Casaponsa, HC Chiang, LPL Colombo, C Combet, BP Crill, F Cuttaia, P De Bernardis, A De Rosa, G De Zotti, J Delabrouille, E DI Valentino, JM DIego, O Doré, M Douspis, X Dupac, HK Eriksen, R Fernandez-Cobos, F Finelli, M Frailis, AA Fraisse, E Franceschi, A Frolov, S Galeotta, S Galli, K Ganga, M Gerbino, T Ghosh, J González-Nuevo, KM Górski, A Gruppuso, JE Gudmundsson, W Handley, G Helou, D Herranz, SR Hildebrandt, E Hivon, Z Huang, AH Jaffe, WC Jones, E Keihänen, R Keskitalo, K Kiiveri, J Kim, TS Kisner, N Krachmalnicoff, M Kunz, H Kurki-Suonio, A Lasenby, M Lattanzi, CR Lawrence, M Le Jeune, F Levrier, M Liguori, PB Lilje, M Lilley, V Lindholm, M López-Caniego, PM Lubin, JF MacÍas-Pérez, D Maino, N Mandolesi, A Marcos-Caballero, M Maris, PG Martin, E Martínez-González, S Matarrese, N Mauri, JD McEwen, PR Meinhold, A Mennella, M Migliaccio, S Mitra, D Molinari, L Montier, G Morgante, A Moss, P Natoli, D Paoletti, B Partridge, G Patanchon, D Pearson, TJ Pearson, "Planck intermediate results: LVII. Joint Planck LFI and HFI data processing", Astronomy and Astrophysics, 2020, 643, doi: 10.1051/0004-6361/202038073

N Aghanim, Y Akrami, MIR Alves, M Ashdown, J Aumont, C Baccigalupi, M Ballardini, AJ Banday, RB Barreiro, N Bartolo, S Basak, K Benabed, JP Bernard, M Bersanelli, P Bielewicz, JJ Bock, JR Bond, J Borrill, FR Bouchet, F Boulanger, A Bracco, M Bucher, C Burigana, E Calabrese, JF Cardoso, J Carron, RR Chary, HC Chiang, LPL Colombo, C Combet, BP Crill, F Cuttaia, P De Bernardis, G De Zotti, J Delabrouille, JM Delouis, E Di Valentino, C Dickinson, JM Diego, O Doré, M Douspis, A Ducout, X Dupac, G Efstathiou, F Elsner, TA Enßlin, HK Eriksen, E Falgarone, Y Fantaye, R Fernandez-Cobos, K Ferrière, F Finelli, F Forastieri, M Frailis, AA Fraisse, E Franceschi, A Frolov, S Galeotta, S Galli, K Ganga, RT Génova-Santos, M Gerbino, T Ghosh, J González-Nuevo, KM Górski, S Gratton, G Green, A Gruppuso, JE Gudmundsson, V Guillet, W Handley, FK Hansen, G Helou, D Herranz, E Hivon, Z Huang, AH Jaffe, WC Jones, E Keihänen, R Keskitalo, K Kiiveri, J Kim, N Krachmalnicoff, M Kunz, H Kurki-Suonio, G Lagache, JM Lamarre, A Lasenby, M Lattanzi, CR Lawrence, M Le Jeune, F Levrier, M Liguori, PB Lilje, V Lindholm, M López-Caniego, PM Lubin, YZ Ma, JF Maciás-Pérez, G Maggio, "Planck 2018 results: XII. Galactic astrophysics using polarized dust emission", Astronomy and Astrophysics, 2020, 641, doi: 10.1051/0004-6361/201833885

Jeeyung Kim, Alex Sim, Jinoh Kim, Kesheng Wu, Botnet Detection Using Recurrent Variational Autoencoder, arXiv preprint arXiv:2004.00234, 2020,

Y Akrami, M Ashdown, J Aumont, C Baccigalupi, M Ballardini, AJ Banday, RB Barreiro, N Bartolo, S Basak, K Benabed, JP Bernard, M Bersanelli, P Bielewicz, JR Bond, J Borrill, FR Bouchet, F Boulanger, A Bracco, M Bucher, C Burigana, E Calabrese, JF Cardoso, J Carron, HC Chiang, C Combet, BP Crill, P De Bernardis, G De Zotti, J Delabrouille, JM Delouis, E Di Valentino, C Dickinson, JM Diego, A Ducout, X Dupac, G Efstathiou, F Elsner, TA Enßlin, E Falgarone, Y Fantaye, K Ferrière, F Finelli, F Forastieri, M Frailis, AA Fraisse, E Franceschi, A Frolov, S Galeotta, S Galli, K Ganga, RT Génova-Santos, T Ghosh, J González-Nuevo, KM Górski, A Gruppuso, JE Gudmundsson, V Guillet, W Handley, FK Hansen, D Herranz, Z Huang, AH Jaffe, WC Jones, E Keihänen, R Keskitalo, K Kiiveri, J Kim, N Krachmalnicoff, M Kunz, H Kurki-Suonio, JM Lamarre, A Lasenby, M Le Jeune, F Levrier, M Liguori, PB Lilje, V Lindholm, M López-Caniego, PM Lubin, YZ Ma, JF Maciás-Pérez, G Maggio, D Maino, N Mandolesi, A Mangilli, PG Martin, E Martínez-González, S Matarrese, JD McEwen, PR Meinhold, A Melchiorri, M Migliaccio, MA Miville-Deschênes, D Molinari, A Moneti, L Montier, G Morgante, P Natoli, L Pagano, D Paoletti, "Planck 2018 results: XI. Polarized dust foregrounds", Astronomy and Astrophysics, 2020, 641, doi: 10.1051/0004-6361/201832618

Jeremy Logan, Mark Ainsworth, Chuck Atkins, Jieyang Chen, Jong Choi, Junmin Gu, James Kress, Greg Eisenhauer, Berk Geveci, William Godoy, others, Extending the Publish/Subscribe Abstraction for High-Performance I/O and Data Management at Extreme Scale, Data Engineering, 2020,

Y Akrami, F Arroja, M Ashdown, J Aumont, C Baccigalupi, M Ballardini, AJ Banday, RB Barreiro, N Bartolo, S Basak, K Benabed, JP Bernard, M Bersanelli, P Bielewicz, JJ Bock, JR Bond, J Borrill, FR Bouchet, F Boulanger, M Bucher, C Burigana, RC Butler, E Calabrese, JF Cardoso, J Carron, A Challinor, HC Chiang, LPL Colombo, C Combet, D Contreras, BP Crill, F Cuttaia, P De Bernardis, G De Zotti, J Delabrouille, JM Delouis, E Di Valentino, JM Diego, S Donzelli, O Doré, M Douspis, A Ducout, X Dupac, S Dusini, G Efstathiou, F Elsner, TA Enßlin, HK Eriksen, Y Fantaye, J Fergusson, R Fernandez-Cobos, F Finelli, F Forastieri, M Frailis, E Franceschi, A Frolov, S Galeotta, S Galli, K Ganga, C Gauthier, RT Génova-Santos, M Gerbino, T Ghosh, J González-Nuevo, KM Górski, S Gratton, A Gruppuso, JE Gudmundsson, J Hamann, W Handley, FK Hansen, D Herranz, E Hivon, DC Hooper, Z Huang, AH Jaffe, WC Jones, E Keihänen, R Keskitalo, K Kiiveri, J Kim, TS Kisner, N Krachmalnicoff, M Kunz, H Kurki-Suonio, G Lagache, JM Lamarre, A Lasenby, M Lattanzi, CR Lawrence, M Le Jeune, J Lesgourgues, F Levrier, A Lewis, M Liguori, PB Lilje, V Lindholm, M López-Caniego, PM Lubin, YZ Ma, "Planck 2018 results: X. Constraints on inflation", Astronomy and Astrophysics, 2020, 641, doi: 10.1051/0004-6361/201833887

N Aghanim, Y Akrami, M Ashdown, J Aumont, C Baccigalupi, M Ballardini, AJ Banday, RB Barreiro, N Bartolo, S Basak, K Benabed, JP Bernard, M Bersanelli, P Bielewicz, JJ Bock, JR Bond, J Borrill, FR Bouchet, F Boulanger, M Bucher, C Burigana, E Calabrese, JF Cardoso, J Carron, A Challinor, HC Chiang, LPL Colombo, C Combet, BP Crill, F Cuttaia, P De Bernardis, G De Zotti, J Delabrouille, E Di Valentino, JM Diego, O Doré, M Douspis, A Ducout, X Dupac, G Efstathiou, F Elsner, TA Enßlin, HK Eriksen, Y Fantaye, R Fernandez-Cobos, F Finelli, F Forastieri, M Frailis, AA Fraisse, E Franceschi, A Frolov, S Galeotta, S Galli, K Ganga, RT Génova-Santos, M Gerbino, T Ghosh, J González-Nuevo, KM Górski, S Gratton, A Gruppuso, JE Gudmundsson, J Hamann, W Handley, FK Hansen, D Herranz, E Hivon, Z Huang, AH Jaffe, WC Jones, A Karakci, E Keihänen, R Keskitalo, K Kiiveri, J Kim, L Knox, N Krachmalnicoff, M Kunz, H Kurki-Suonio, G Lagache, JM Lamarre, A Lasenby, M Lattanzi, CR Lawrence, M Le Jeune, F Levrier, A Lewis, M Liguori, PB Lilje, V Lindholm, M López-Caniego, PM Lubin, YZ Ma, JF Maciás-Pérez, G Maggio, D Maino, N Mandolesi, A Mangilli, A Marcos-Caballero, M Maris, "Planck 2018 results: VIII. Gravitational lensing", Astronomy and Astrophysics, 2020, 641, doi: 10.1051/0004-6361/201833886

Y Akrami, M Ashdown, J Aumont, C Baccigalupi, M Ballardini, AJ Banday, RB Barreiro, N Bartolo, S Basak, K Benabed, M Bersanelli, P Bielewicz, JJ Bock, JR Bond, J Borrill, FR Bouchet, F Boulanger, M Bucher, C Burigana, RC Butler, E Calabrese, JF Cardoso, B Casaponsa, HC Chiang, LPL Colombo, C Combet, D Contreras, BP Crill, P De Bernardis, G De Zotti, J Delabrouille, JM Delouis, E Di Valentino, JM Diego, O Doré, M Douspis, A Ducout, X Dupac, G Efstathiou, F Elsner, TA Enßlin, HK Eriksen, Y Fantaye, R Fernandez-Cobos, F Finelli, M Frailis, AA Fraisse, E Franceschi, A Frolov, S Galeotta, S Galli, K Ganga, RT Génova-Santos, M Gerbino, T Ghosh, J González-Nuevo, KM Górski, A Gruppuso, JE Gudmundsson, J Hamann, W Handley, FK Hansen, D Herranz, E Hivon, Z Huang, AH Jaffe, WC Jones, E Keihänen, R Keskitalo, K Kiiveri, J Kim, N Krachmalnicoff, M Kunz, H Kurki-Suonio, G Lagache, JM Lamarre, A Lasenby, M Lattanzi, CR Lawrence, M Le Jeune, F Levrier, M Liguori, PB Lilje, V Lindholm, M López-Caniego, YZ Ma, JF Maciás-Pérez, G Maggio, D Maino, N Mandolesi, A Mangilli, A Marcos-Caballero, M Maris, PG Martin, E Martínez-González, S Matarrese, N Mauri, JD McEwen, PR Meinhold, A Mennella, "Planck 2018 results: VII. Isotropy and statistics of the CMB", Astronomy and Astrophysics, 2020, 641, doi: 10.1051/0004-6361/201935201

William F Godoy, Norbert Podhorszki, Ruonan Wang, Chuck Atkins, Greg Eisenhauer, Junmin Gu, Philip Davis, Jong Choi, Kai Germaschewski, Kevin Huck, others, ADIOS 2: The Adaptable Input Output System. A framework for high-performance data management, SoftwareX, Pages: 100561 2020,

N Aghanim, Y Akrami, M Ashdown, J Aumont, C Baccigalupi, M Ballardini, AJ Banday, RB Barreiro, N Bartolo, S Basak, R Battye, K Benabed, JP Bernard, M Bersanelli, P Bielewicz, JJ Bock, JR Bond, J Borrill, FR Bouchet, F Boulanger, M Bucher, C Burigana, RC Butler, E Calabrese, JF Cardoso, J Carron, A Challinor, HC Chiang, J Chluba, LPL Colombo, C Combet, D Contreras, BP Crill, F Cuttaia, P De Bernardis, G De Zotti, J Delabrouille, JM Delouis, E Di Valentino, JM Diego, O Doré, M Douspis, A Ducout, X Dupac, S Dusini, G Efstathiou, F Elsner, TA Enßlin, HK Eriksen, Y Fantaye, M Farhang, J Fergusson, R Fernandez-Cobos, F Finelli, F Forastieri, M Frailis, AA Fraisse, E Franceschi, A Frolov, S Galeotta, S Galli, K Ganga, RT Génova-Santos, M Gerbino, T Ghosh, J González-Nuevo, KM Górski, S Gratton, A Gruppuso, JE Gudmundsson, J Hamann, W Handley, FK Hansen, D Herranz, SR Hildebrandt, E Hivon, Z Huang, AH Jaffe, WC Jones, A Karakci, E Keihänen, R Keskitalo, K Kiiveri, J Kim, TS Kisner, L Knox, N Krachmalnicoff, M Kunz, H Kurki-Suonio, G Lagache, JM Lamarre, A Lasenby, M Lattanzi, CR Lawrence, M Le Jeune, P Lemos, J Lesgourgues, F Levrier, A Lewis, M Liguori, "Planck 2018 results: VI. Cosmological parameters", Astronomy and Astrophysics, 2020, 641, doi: 10.1051/0004-6361/201833910

N Aghanim, Y Akrami, M Ashdown, J Aumont, C Baccigalupi, M Ballardini, AJ Banday, RB Barreiro, N Bartolo, S Basak, K Benabed, JP Bernard, M Bersanelli, P Bielewicz, JJ Bock, JR Bond, J Borrill, FR Bouchet, F Boulanger, M Bucher, C Burigana, RC Butler, E Calabrese, JF Cardoso, J Carron, B Casaponsa, A Challinor, HC Chiang, LPL Colombo, C Combet, BP Crill, F Cuttaia, P De Bernardis, A De Rosa, G De Zotti, J Delabrouille, JM Delouis, E Di Valentino, JM Diego, O Doré, M Douspis, A Ducout, X Dupac, S Dusini, G Efstathiou, F Elsner, TA Enßlin, HK Eriksen, Y Fantaye, R Fernandez-Cobos, F Finelli, M Frailis, AA Fraisse, E Franceschi, A Frolov, S Galeotta, S Galli, K Ganga, RT Génova-Santos, M Gerbino, T Ghosh, Y Giraud-Héraud, J González-Nuevo, KM Górski, S Gratton, A Gruppuso, JE Gudmundsson, J Hamann, W Handley, FK Hansen, D Herranz, E Hivon, Z Huang, AH Jaffe, WC Jones, E Keihänen, R Keskitalo, K Kiiveri, J Kim, TS Kisner, N Krachmalnicoff, M Kunz, H Kurki-Suonio, G Lagache, JM Lamarre, A Lasenby, M Lattanzi, CR Lawrence, M Le Jeune, F Levrier, A Lewis, M Liguori, PB Lilje, M Lilley, V Lindholm, M López-Caniego, PM Lubin, YZ Ma, JF Maciás-Pérez, G Maggio, "Planck 2018 results: V. CMB power spectra and likelihoods", Astronomy and Astrophysics, 2020, 641, doi: 10.1051/0004-6361/201936386

Y Akrami, F Arroja, M Ashdown, J Aumont, C Baccigalupi, M Ballardini, AJ Banday, RB Barreiro, N Bartolo, S Basak, K Benabed, JP Bernard, M Bersanelli, P Bielewicz, JR Bond, J Borrill, FR Bouchet, M Bucher, C Burigana, RC Butler, E Calabrese, JF Cardoso, B Casaponsa, A Challinor, HC Chiang, LPL Colombo, C Combet, BP Crill, F Cuttaia, P De Bernardis, A De Rosa, G De Zotti, J Delabrouille, JM Delouis, E Di Valentino, JM Diego, O Doré, M Douspis, A Ducout, X Dupac, S Dusini, G Efstathiou, F Elsner, TA Enßlin, HK Eriksen, Y Fantaye, J Fergusson, R Fernandez-Cobos, F Finelli, M Frailis, AA Fraisse, E Franceschi, A Frolov, S Galeotta, S Galli, K Ganga, RT Génova-Santos, M Gerbino, J González-Nuevo, KM Górski, S Gratton, A Gruppuso, JE Gudmundsson, J Hamann, W Handley, FK Hansen, D Herranz, E Hivon, Z Huang, AH Jaffe, WC Jones, G Jung, E Keihänen, R Keskitalo, K Kiiveri, J Kim, N Krachmalnicoff, M Kunz, H Kurki-Suonio, JM Lamarre, A Lasenby, M Lattanzi, CR Lawrence, M Le Jeune, F Levrier, A Lewis, M Liguori, PB Lilje, V Lindholm, M López-Caniego, YZ Ma, JF Maciás-Pérez, G Maggio, D Maino, N Mandolesi, A Marcos-Caballero, M Maris, PG Martin, E Martínez-González, S Matarrese, "Planck 2018 results: IX. Constraints on primordial non-Gaussianity", Astronomy and Astrophysics, 2020, 641, doi: 10.1051/0004-6361/201935891

Y Akrami, M Ashdown, J Aumont, C Baccigalupi, M Ballardini, AJ Banday, RB Barreiro, N Bartolo, S Basak, K Benabed, M Bersanelli, P Bielewicz, JR Bond, J Borrill, FR Bouchet, F Boulanger, M Bucher, C Burigana, E Calabrese, JF Cardoso, J Carron, B Casaponsa, A Challinor, LPL Colombo, C Combet, BP Crill, F Cuttaia, P De Bernardis, A De Rosa, G De Zotti, J Delabrouille, JM Delouis, E Di Valentino, C Dickinson, JM Diego, S Donzelli, O Doré, A Ducout, X Dupac, G Efstathiou, F Elsner, TA Enßlin, HK Eriksen, E Falgarone, R Fernandez-Cobos, F Finelli, F Forastieri, M Frailis, AA Fraisse, E Franceschi, A Frolov, S Galeotta, S Galli, K Ganga, RT Génova-Santos, M Gerbino, T Ghosh, J González-Nuevo, KM Górski, S Gratton, A Gruppuso, JE Gudmundsson, W Handley, FK Hansen, G Helou, D Herranz, SR Hildebrandt, Z Huang, AH Jaffe, A Karakci, E Keihänen, R Keskitalo, K Kiiveri, J Kim, TS Kisner, N Krachmalnicoff, M Kunz, H Kurki-Suonio, G Lagache, JM Lamarre, A Lasenby, M Lattanzi, CR Lawrence, M Le Jeune, F Levrier, M Liguori, PB Lilje, V Lindholm, M López-Caniego, PM Lubin, YZ Ma, JF Maciás-Pérez, G Maggio, D Maino, N Mandolesi, A Mangilli, A Marcos-Caballero, M Maris, PG Martin, E Martínez-González, "Planck 2018 results: IV. Diffuse component separation", Astronomy and Astrophysics, 2020, 641, doi: 10.1051/0004-6361/201833881

N Aghanim, Y Akrami, M Ashdown, J Aumont, C Baccigalupi, M Ballardini, AJ Banday, RB Barreiro, N Bartolo, S Basak, K Benabed, JP Bernard, M Bersanelli, P Bielewicz, JR Bond, J Borrill, FR Bouchet, F Boulanger, M Bucher, C Burigana, E Calabrese, JF Cardoso, J Carron, A Challinor, HC Chiang, LPL Colombo, C Combet, F Couchot, BP Crill, F Cuttaia, P De Bernardis, A De Rosa, G De Zotti, J Delabrouille, JM Delouis, E Di Valentino, JM Diego, O Doré, M Douspis, A Ducout, X Dupac, G Efstathiou, F Elsner, TA Enßlin, HK Eriksen, E Falgarone, Y Fantaye, F Finelli, M Frailis, AA Fraisse, E Franceschi, A Frolov, S Galeotta, S Galli, K Ganga, RT Génova-Santos, M Gerbino, T Ghosh, J González-Nuevo, KM Górski, S Gratton, A Gruppuso, JE Gudmundsson, W Handley, FK Hansen, S Henrot-Versillé, D Herranz, E Hivon, Z Huang, AH Jaffe, WC Jones, A Karakci, E Keihänen, R Keskitalo, K Kiiveri, J Kim, TS Kisner, N Krachmalnicoff, M Kunz, H Kurki-Suonio, G Lagache, JM Lamarre, A Lasenby, M Lattanzi, CR Lawrence, F Levrier, M Liguori, PB Lilje, V Lindholm, M López-Caniego, YZ Ma, JF Maciás-Pérez, G Maggio, D Maino, N Mandolesi, A Mangilli, PG Martin, E Martínez-González, S Matarrese, N Mauri, "Planck 2018 results: III. High frequency instrument data processing and frequency maps", Astronomy and Astrophysics, 2020, 641, doi: 10.1051/0004-6361/201832909

Y Akrami, F Argüeso, M Ashdown, J Aumont, C Baccigalupi, M Ballardini, AJ Banday, RB Barreiro, N Bartolo, S Basak, K Benabed, JP Bernard, M Bersanelli, P Bielewicz, L Bonavera, JR Bond, J Borrill, FR Bouchet, F Boulanger, M Bucher, C Burigana, RC Butler, E Calabrese, JF Cardoso, LPL Colombo, BP Crill, F Cuttaia, P De Bernardis, A De Rosa, G De Zotti, J Delabrouille, E Di Valentino, C Dickinson, JM Diego, S Donzelli, A Ducout, X Dupac, G Efstathiou, F Elsner, TA Enßlin, HK Eriksen, Y Fantaye, F Finelli, M Frailis, E Franceschi, A Frolov, S Galeotta, S Galli, K Ganga, RT Génova-Santos, M Gerbino, T Ghosh, J González-Nuevo, KM Górski, S Gratton, A Gruppuso, JE Gudmundsson, W Handley, FK Hansen, D Herranz, E Hivon, Z Huang, AH Jaffe, WC Jones, A Karakci, E Keihänen, R Keskitalo, K Kiiveri, J Kim, TS Kisner, N Krachmalnicoff, M Kunz, H Kurki-Suonio, JM Lamarre, A Lasenby, M Lattanzi, CR Lawrence, JP Leahy, F Levrier, M Liguori, PB Lilje, V Lindholm, M López-Caniego, YZ Ma, JF Maciás-Pérez, G Maggio, D Maino, N Mandolesi, A Mangilli, M Maris, PG Martin, E Martínez-González, S Matarrese, N Mauri, JD McEwen, PR Meinhold, A Melchiorri, A Mennella, M Migliaccio, D Molinari, "Planck 2018 results: II. Low Frequency Instrument data processing", Astronomy and Astrophysics, 2020, 641, doi: 10.1051/0004-6361/201833293

N Aghanim, Y Akrami, F Arroja, M Ashdown, J Aumont, C Baccigalupi, M Ballardini, AJ Banday, RB Barreiro, N Bartolo, S Basak, R Battye, K Benabed, JP Bernard, M Bersanelli, P Bielewicz, JJ Bock, JR Bond, J Borrill, FR Bouchet, F Boulanger, M Bucher, C Burigana, RC Butler, E Calabrese, JF Cardoso, J Carron, B Casaponsa, A Challinor, HC Chiang, LPL Colombo, C Combet, D Contreras, BP Crill, F Cuttaia, P De Bernardis, G De Zotti, J Delabrouille, JM Delouis, FX Désert, E Di Valentino, C Dickinson, JM Diego, S Donzelli, O Doré, M Douspis, A Ducout, X Dupac, G Efstathiou, F Elsner, TA Enßlin, HK Eriksen, E Falgarone, Y Fantaye, J Fergusson, R Fernandez-Cobos, F Finelli, F Forastieri, M Frailis, E Franceschi, A Frolov, S Galeotta, S Galli, K Ganga, RT Génova-Santos, M Gerbino, T Ghosh, J González-Nuevo, KM Górski, S Gratton, A Gruppuso, JE Gudmundsson, J Hamann, W Handley, FK Hansen, G Helou, D Herranz, SR Hildebrandt, E Hivon, Z Huang, AH Jaffe, WC Jones, A Karakci, E Keihänen, R Keskitalo, K Kiiveri, J Kim, TS Kisner, L Knox, N Krachmalnicoff, M Kunz, H Kurki-Suonio, G Lagache, JM Lamarre, M Langer, A Lasenby, M Lattanzi, CR Lawrence, M Le Jeune, JP Leahy, "Planck 2018 results: I. Overview and the cosmological legacy of Planck", Astronomy and Astrophysics, 2020, 641, doi: 10.1051/0004-6361/201833880

S Adachi, MAO Aguilar Faúndez, K Arnold, C Baccigalupi, D Barron, D Beck, S Beckman, F Bianchini, D Boettger, J Borrill, J Carron, S Chapman, K Cheung, Y Chinone, K Crowley, A Cukierman, M Dobbs, HE Bouhargani, T Elleflot, J Errard, G Fabbian, C Feng, T Fujino, N Galitzki, N Goeckner-Wald, J Groh, G Hall, N Halverson, T Hamada, M Hasegawa, M Hazumi, CA Hill, L Howe, Y Inoue, G Jaehnig, O Jeong, D Kaneko, N Katayama, B Keating, R Keskitalo, S Kikuchi, T Kisner, N Krachmalnicoff, A Kusaka, AT Lee, D Leon, E Linder, LN Lowry, A Mangu, F Matsuda, Y Minami, M Navaroli, H Nishino, ATP Pham, D Poletti, G Puglisi, CL Reichardt, Y Segawa, M Silva-Feaver, P Siritanasak, N Stebor, R Stompor, A Suzuki, O Tajima, S Takakura, S Takatori, D Tanabe, GP Teply, C Tsai, C Verges, B Westbrook, Y Zhou, "A Measurement of the Degree-scale CMB B-mode Angular Power Spectrum with Polarbear", Astrophysical Journal, 2020, 897, doi: 10.3847/1538-4357/ab8f24

H Sugai, PAR Ade, Y Akiba, D Alonso, K Arnold, J Aumont, J Austermann, C Baccigalupi, AJ Banday, R Banerji, RB Barreiro, S Basak, J Beall, S Beckman, M Bersanelli, J Borrill, F Boulanger, ML Brown, M Bucher, A Buzzelli, E Calabrese, FJ Casas, A Challinor, V Chan, Y Chinone, JF Cliche, F Columbro, A Cukierman, D Curtis, P Danto, P de Bernardis, T de Haan, M De Petris, C Dickinson, M Dobbs, T Dotani, L Duband, A Ducout, S Duff, A Duivenvoorden, JM Duval, K Ebisawa, T Elleflot, H Enokida, HK Eriksen, J Errard, T Essinger-Hileman, F Finelli, R Flauger, C Franceschet, U Fuskeland, K Ganga, JR Gao, R Génova-Santos, T Ghigna, A Gomez, ML Gradziel, J Grain, F Grupp, A Gruppuso, JE Gudmundsson, NW Halverson, P Hargrave, T Hasebe, M Hasegawa, M Hattori, M Hazumi, S Henrot-Versille, D Herranz, C Hill, G Hilton, Y Hirota, E Hivon, R Hlozek, DT Hoang, J Hubmayr, K Ichiki, T Iida, H Imada, K Ishimura, H Ishino, GC Jaehnig, M Jones, T Kaga, S Kashima, Y Kataoka, N Katayama, T Kawasaki, R Keskitalo, A Kibayashi, T Kikuchi, K Kimura, T Kisner, Y Kobayashi, N Kogiso, A Kogut, K Kohri, E Komatsu, K Komatsu, K Konishi, "Updated Design of the CMB Polarization Experiment Satellite LiteBIRD", Journal of Low Temperature Physics, 2020, 199:1107--1117, doi: 10.1007/s10909-019-02329-w

D Kaneko, S Adachi, PAR Ade, M Aguilar Faúndez, Y Akiba, K Arnold, C Baccigalupi, D Barron, D Beck, S Beckman, F Bianchini, D Boettger, J Borrill, J Carron, S Chapman, K Cheung, Y Chinone, K Crowley, A Cukierman, M Dobbs, R Dűnner, H El-Bouhargani, T Elleflot, J Errard, G Fabbian, SM Feeney, C Feng, T Fujino, N Galitzki, A Gilbert, N Goeckner-Wald, J Groh, G Hall, NW Halverson, T Hamada, M Hasegawa, M Hazumi, CA Hill, L Howe, Y Inoue, G Jaehnig, O Jeong, N Katayama, B Keating, R Keskitalo, S Kikuchi, T Kisner, N Krachmalnicoff, A Kusaka, AT Lee, D Leon, E Linder, LN Lowry, A Mangu, F Matsuda, Y Minami, M Navaroli, H Nishino, J Peloton, ATP Pham, D Poletti, G Puglisi, CL Reichardt, C Ross, Y Segawa, M Silva-Feaver, P Siritanasak, N Stebor, R Stompor, A Suzuki, O Tajima, S Takakura, S Takatori, D Tanabe, GP Teply, T Tomaru, C Tsai, C Verges, B Westbrook, Y Zhou, "Deployment of Polarbear-2A", Journal of Low Temperature Physics, 2020, 199:1137--1147, doi: 10.1007/s10909-020-02366-w

T Groves, B Brock, Y Chen, KZ Ibrahim, L Oliker, NJ Wright, S Williams, K Yelick, "Performance Trade-offs in GPU Communication: A Study of Host and Device-initiated Approaches", Proceedings of PMBS 2020: Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems, Held in conjunction with SC 2020: The International Conference for High Performance Computing, Networking, Storage and Analysis, January 2020, 126--137, doi: 10.1109/PMBS51919.2020.00016

Y Chinone, S Adachi, PAR Ade, M Aguilar, Y Akiba, K Arnold, C Baccigalupi, D Barron, D Beck, S Beckman, F Bianchini, D Boettger, J Borrill, H Elbouhargani, J Carron, S Chapman, K Cheung, K Crowley, A Cukierman, R Dünner, M Dobbs, A Ducout, T Elleflot, J Errard, G Fabbian, SM Feeney, C Feng, T Fujino, N Galitzki, A Gilbert, N Goeckner-Wald, J Groh, JC Groh, G Hall, N Halverson, T Hamada, M Hasegawa, M Hazumi, CA Hill, L Howe, Y Inoue, G Jaehnig, AH Jaffe, O Jeong, M Lejeune, D Kaneko, N Katayama, B Keating, R Keskitalo, S Kikuchi, T Kisner, N Krachmalnicoff, A Kusaka, AT Lee, EM Leitch, D Leon, E Linder, LN Lowry, A Mangu, F Matsuda, T Matsumura, Y Minami, J Montgomery, M Navaroli, H Nishino, H Paar, J Peloton, ATP Pham, D Poletti, G Puglisi, CL Reichardt, PL Richards, C Ross, Y Segawa, BD Sherwin, M Silva-Feaver, P Siritanasak, N Stebor, R Stompor, A Suzuki, O Tajima, S Takakura, S Takatori, D Tanabe, GP Teply, T Tomaru, C Tsai, C Tucker, C Verges, B Westbrook, N Whitehorn, A Zahn, Y Zhou, "Results of gravitational lensing and primordial gravitational waves from the POLARBEAR experiment", Journal of Physics: Conference Series, 2020, 1468, doi: 10.1088/1742-6596/1468/1/012007

A Sangodoyin, B Mohammed, lU Awan, "Data driven Machine Learning approach to detect DDoS attack in Software Defined Network", Journal of Concurrency and Computation: Practice and Experience, January 1, 2020,

L Lamagna, JE Gudmundsson, H Imada, P Hargrave, C Franceschet, M De Petris, J Austermann, S Bounissou, F Columbro, P De Bernardis, S Henrot-Versillé, J Hubmayr, G Jaehnig, R Keskitalo, B Maffei, S Masi, T Matsumura, L Montier, B Mot, F Noviello, C O sullivan, A Paiella, G Pisano, S Realini, A Ritacco, G Savini, A Suzuki, N Trappe, B Winter, "The optical design of the Litebird middle and high frequency telescope", Proceedings of SPIE - The International Society for Optical Engineering, 2020, 11443, doi: 10.1117/12.2579233

L Montier, B Mot, P De Bernardis, B Maffei, G Pisano, F Columbro, JE Gudmundsson, S Henrot-Versillé, L Lamagna, J Montgomery, T Prouvé, M Russell, G Savini, S Stever, KL Thompson, M Tsujimoto, C Tucker, B Westbrook, PAR Ade, A Adler, E Allys, K Arnold, D Auguste, J Aumont, R Aurlien, J Austermann, C Baccigalupi, AJ Banday, R Banerji, RB Barreiro, S Basak, J Beall, D Beck, S Beckman, J Bermejo, M Bersanelli, J Bonis, J Borrill, F Boulanger, S Bounissou, M Brilenkov, M Brown, M Bucher, E Calabrese, P Campeti, A Carones, FJ Casas, A Challinor, V Chan, K Cheung, Y Chinone, JF Cliche, L Colombo, J Cubas, A Cukierman, D Curtis, G D alessandro, N Dachlythra, M De Petris, C Dickinson, P Diego-Palazuelos, M Dobbs, T Dotani, L Duband, S Duff, JM Duval, K Ebisawa, T Elleflot, HK Eriksen, J Errard, T Essinger-Hileman, F Finelli, R Flauger, C Franceschet, U Fuskeland, M Galloway, K Ganga, JR Gao, R Genova-Santos, M Gerbino, M Gervasi, T Ghigna, E Gjerløw, ML Gradziel, J Grain, F Grupp, A Gruppuso, T De Haan, NW Halverson, P Hargrave, T Hasebe, M Hasegawa, M Hattori, M Hazumi, D Herman, D Herranz, CA Hill, G Hilton, Y Hirota, E Hivon, Overview of the medium and high frequency telescopes of the LiteBIRD space mission, Proceedings of SPIE - The International Society for Optical Engineering, 2020, doi: 10.1117/12.2562243

M Hazumi, PAR Ade, A Adler, E Allys, K Arnold, D Auguste, J Aumont, R Aurlien, J Austermann, C Baccigalupi, AJ Banday, R Banjeri, RB Barreiro, S Basak, J Beall, D Beck, S Beckman, J Bermejo, P De Bernardis, M Bersanelli, J Bonis, J Borrill, F Boulanger, S Bounissou, M Brilenkov, M Brown, M Bucher, E Calabrese, P Campeti, A Carones, FJ Casas, A Challinor, V Chan, K Cheung, Y Chinone, JF Cliche, L Colombo, F Columbro, J Cubas, A Cukierman, D Curtis, G D alessandro, N Dachlythra, M De Petris, C Dickinson, P Diego-Palazuelos, M Dobbs, T Dotani, L Duband, S Duff, JM Duval, K Ebisawa, T Elleflot, HK Eriksen, J Errard, T Essinger-Hileman, F Finelli, R Flauger, C Franceschet, U Fuskeland, M Galloway, K Ganga, JR Gao, R Genova-Santos, M Gerbino, M Gervasi, T Ghigna, E Gjerløw, ML Gradziel, J Grain, F Grupp, A Gruppuso, JE Gudmundsson, T De Haan, NW Halverson, P Hargrave, T Hasebe, M Hasegawa, M Hattori, S Henrot-Versillé, D Herman, D Herranz, CA Hill, G Hilton, Y Hirota, E Hivon, RA Hlozek, Y Hoshino, E De La Hoz, J Hubmayr, K Ichiki, T Iida, H Imada, K Ishimura, H Ishino, G Jaehnig, T Kaga, S Kashima, N Katayama, A Kato, LiteBIRD satellite: JAXA s new strategic L-class mission for all-sky surveys of cosmic microwave background polarization, Proceedings of SPIE - The International Society for Optical Engineering, 2020, doi: 10.1117/12.2563050

D Beck, PAR Ade, M Aguilar, Y Akiba, A Ali, K Arnold, P Ashton, C Baccigalupi, D Barron, S Beckman, AN Bender, F Bianchini, D Boettger, J Borrill, J Carron, S Chapman, Y Chinone, G Coppi, K Crowley, A Cukierman, TDE Haan, M Dobbs, R Dünner, T Elleflot, J Errard, G Fabbian, SM Feeney, C Feng, G Fuller, N Galitzki, A Gilbert, N Goeckner-Wald, J Groh, NW Halverson, T Hamada, M Hasegawa, M Hazumi, CA Hill, W Holzapfel, L Howe, Y Inoue, J Ito, G Jaehnig, A Jaffe, O Jeong, D Kaneko, N Katayama, B Keating, R Keskitalo, T Kisner, N Krachmalnicoff, A Kusaka, MLE Jeune, AT Lee, D Leon, E Linder, L Lowry, A Madurowicz, D Mak, F Matsuda, T Matsumara, A May, NJ Miller, Y Minami, J Montgomery, M Navaroli, H Nishino, T Okamura, J Peloton, A Pham, L Piccirillo, D Plambeck, D Poletti, G Puglisi, C Raum, G Rebeiz, CL Reichardt, PL Richards, H Roberts, C Ross, KM Rotermund, Y Segawa, B Sherwin, M Silva-Feaver, P Siritanasak, L Steinmetz, R Stompor, A Suzuki, J Suzuki, O Tajima, S Takakura, S Takatori, D Tanabe, R Tat, GP Teply, A Tikhomirov, T Tomaru, C Tsai, C Vergès, "Latest results, current data-analysis and upcoming upgrades of the polarbear/simons array experiments", Proceedings of the 53rd Rencontres de Moriond on Cosmology 2018, 2020, 125--132,

Y Sekimoto, PAR Ade, A Adler, E Allys, K Arnold, D Auguste, J Aumont, R Aurlien, J Austermann, C Baccigalupi, AJ Banday, R Banerji, RB Barreiro, S Basak, J Beall, D Beck, S Beckman, J Bermejo, P De Bernardis, M Bersanelli, J Bonis, J Borrill, F Boulanger, S Bounissou, M Brilenkov, M Brown, M Bucher, E Calabrese, P Campeti, A Carones, FJ Casas, A Challinor, V Chan, K Cheung, Y Chinone, JF Cliche, L Colombo, F Columbro, J Cubas, A Cukierman, D Curtis, G D Alessandro, N Dachlythra, M De Petris, C Dickinson, P Diego-Palazuelos, M Dobbs, T Dotani, L Duband, S Duff, JM Duval, K Ebisawa, T Elleflot, HK Eriksen, J Errard, T Essinger-Hileman, F Finelli, R Flauger, C Franceschet, U Fuskeland, M Galloway, K Ganga, JR Gao, R Genova-Santos, M Gerbino, M Gervasi, T Ghigna, E Gjerløw, ML Gradziel, J Grain, F Grupp, A Gruppuso, JE Gudmundsson, T De Haan, NW Halverson, P Hargrave, T Hasebe, M Hasegawa, M Hattori, M Hazumi, S Henrot-Versille, D Herman, D Herranz, CA Hill, G Hilton, Y Hirota, E Hivon, RA Hlozek, Y Hoshino, E De La Hoz, J Hubmayr, K Ichiki, T Iida, H Imada, K Ishimura, H Ishino, G Jaehnig, T Kaga, S Kashima, N Katayama, Concept design of low frequency telescope for CMB B-mode polarization satellite LiteBIRD, Proceedings of SPIE - The International Society for Optical Engineering, 2020, doi: 10.1117/12.2561841

G Guidi, O Selvitopi, M Ellis, L Oliker, K Yelick, A Buluc, "Parallel String Graph Construction and Transitive Reduction for De Novo Genome Assembly", January 1, 2020,

S Schaal, I Ahmed, JA Haigh, L Hutin, B Bertrand, S Barraud, M Vinet, C-M Lee, N Stelmashenko, JWA Robinson, JY Qiu, S Hacohen-Gourgy, I Siddiqi, MF Gonzalez-Zalba, JJL Morton, "Fast Gate-Based Readout of Silicon Quantum Dots Using Josephson Parametric Amplification.", Physical review letters, 2020, 124:067701, doi: 10.1103/physrevlett.124.067701

NA Hatch, Galaxy cluster illuminates the cosmic dark ages., Nature, Pages: 36--37 2020, doi: 10.1051/0004-6361/201628897

E Flurin, LS Martin, S Hacohen-Gourgy, I Siddiqi, "Using a Recurrent Neural Network to Reconstruct Quantum Dynamics of a Superconducting Qubit from Physical Observations", Physical Review X, 2020, 10, doi: 10.1103/PhysRevX.10.011006

LS Martin, WP Livingston, S Hacohen-Gourgy, HM Wiseman, I Siddiqi, "Implementation of a canonical phase measurement with quantum feedback", Nature Physics, 2020, 16:1046--1049, doi: 10.1038/s41567-020-0939-0

Anna Giannakou, Dipankar Dwivedi, Sean Peisert, "A Machine Learning Approach for Packet Loss Prediction in ScienceFlows", Future Generation Computer Systems, January 2020, 102:190-197, doi: 10.1016/j.future.2019.07.053

E. Wes Bethel, David Camp, Talita Perciano, Colleen Heinemann, "Performance Analysis of Traditional and Data-Parallel Primitive Implementations of Visualization and Analysis Kernels", Berkeley, CA, USA, 94720, 2020,

Stefano Marchesini, Anuradha Trivedi, Pablo Enfedaque, Talita Perciano, Dilworth Parkinson, "Sparse Matrix-Based HPC Tomography", Computational Science -- ICCS 2020, Cham, Springer International Publishing, 2020, 248--261, doi: 10.1007/978-3-030-50371-0_18

Talita Perciano, Colleen Heinemann, David Camp, Brenton Lessley, E Wes Bethel, "Shared-Memory Parallel Probabilistic Graphical Modeling Optimization: Comparison of Threads, OpenMP, and Data-Parallel Primitives", High Performance Computing, Cham, Springer International Publishing, 2020, 127--145, doi: 10.1007/978-3-030-50743-5_7

H Chang, J J Donatelli, P Enfedaque, G Freychet, M Haranczyk, A Hexemer, Z Hu, O Jain, H Krishnan, D Kumar, X Li, L Lin, M MacNeil, S Marchesini, X Mo, M Noack, K Pande, R Pandolfi, D Parkinson, D M Pelt, T Perciano, D A Shapiro, D Ushizima, C Yang, P H Zwart, J A Sethian, "Building Mathematics, Algorithms, and Software for Experimental Facilities", Handbook on Big Data and Machine Learning in the Physical Sciences, ( 2020) Pages: 189--240 doi: 10.1142/9789811204579_0012

Nicholas Choma, others, Track Seeding and Labelling with Embedded-space Graph Neural Networks, 2020,

Xiangyang Ju, others, Graph Neural Networks for Particle Reconstruction in High Energy Physics detectors, 33rd Annual Conference on Neural Information Processing Systems, 2020,

Philippe Canal, Elizabeth Sexton-Kennedy, Jonathan Madsen, Soon Yung Jun, Guilherme Lima, Paolo Calafiura, Yunsong Wang, Seth Johnson, Geant Exascale Pilot Project, EPJ Web Conf., Pages: 09015 2020, doi: 10.1051/epjconf/202024509015

Miha Muskinja, Paolo Calafiura, Charles Leggett, Illya Shapoval, Vakho Tsulaia, Raythena: a vertically integrated scheduler for ATLAS applications on heterogeneous distributed resources, EPJ Web Conf., Pages: 05042 2020, doi: 10.1051/epjconf/202024505042

Masahiko Saito, Paolo Calafiura, Heather Gray, Wim Lavrijsen, Lucy Linder, Yasuyuki Okumura, Ryu Sawada, Alex Smith, Junichi Tanaka, Koji Terashi, Quantum annealing algorithms for track pattern recognition, EPJ Web Conf., Pages: 10006 2020, doi: 10.1051/epjconf/202024510006

Frederic Bapst, Wahid Bhimji, Paolo Calafiura, Heather Gray, Wim Lavrijsen, Lucy Linder, Alex Smith, A pattern recognition algorithm for quantum annealers, Comput. Softw. Big Sci., Pages: 1 2020, doi: 10.1007/s41781-019-0032-5

J Corbino, J Castillo, "High-order mimetic finite-difference operators satisfying the extended Gauss divergence theorem", Journal of Computational and Applied Mathematics, 2020, doi: 10.1016/j.cam.2019.06.042

We present high-order mimetic finite-difference operators that satisfy the extended Gauss theorem. These operators have the same order of accuracy in the interior and at the boundary, no free parameters and optimal bandwidth. They are defined over staggered grids, using weighted inner products with a diagonal norm. We present several examples to demonstrate that mimetic finite-difference schemes using these operators produce excellent results.

A Boada, J Corbino, J Castillo, "High-order mimetic difference simulation of unsaturated flow using Richards equation", Mathematics in Applied Sciences and Engineering, 2020, doi: 10.5206/mase/10874

The vadose zone is the portion of the subsurface above the water table and its pore space usually contains air and water. Due to the presence of infiltration, erosion, plant growth, microbiota, contaminant transport, aquifer recharge, and discharge to surface water, it is crucial to predict the transport rate of water and other substances within this zone. However, ow in the vadose zone has many complications as the parameters that control it are extremely sensitive to the saturation of the media, leading to a nonlinear problem. This ow is referred as unsaturated ow and is governed by Richards equation. Analytical solutions for this equation exists only for simplified cases, so most practical situations require a numerical solution. Nevertheless, the nonlinear nature of Richards equation introduces challenges that causes numerical solutions for this problem to be computationally expensive and, in some cases, unreliable. High-order mimetic finite difference operators are discrete analogs of the continuous differential operators and have been extensively used in the fields of fluid and solid mechanics. In this work, we present a numerical approach involving high-order mimetic operators along with a Newton root- finding algorithm for the treatment of the nonlinear component. Fully-implicit time discretization scheme is used to deal with the problem's stiffness.

A Tripathy, K Yelick, A Buluc, Reducing communication in graph neural network training, International Conference for High Performance Computing, Networking, Storage and Analysis, SC, 2020, doi: 10.1109/SC41405.2020.00074

MG Awan, J Deslippe, A Buluc, O Selvitopi, S Hofmeyr, L Oliker, K Yelick, ADEPT: a domain independent sequence alignment strategy for gpu architectures., BMC bioinformatics, Pages: 406 2020, doi: 10.1186/s12859-020-03720-1

S Hofmeyr, R Egan, E Georganas, AC Copeland, R Riley, A Clum, E Eloe-Fadrosh, S Roux, E Goltsman, A Buluç, D Rokhsar, L Oliker, K Yelick, Terabase-scale metagenome coassembly with MetaHipMer., Scientific reports, Pages: 10689 2020, doi: 10.1038/s41598-020-67416-5

F Peverelli, LD Tucci, MD Santambrogio, N Ding, S Hofmeyr, A Buluc, L Oliker, K Yelick, GPU accelerated partial order multiple sequence alignment for long reads self-correction, Proceedings - 2020 IEEE 34th International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2020, Pages: 174--182 2020, doi: 10.1109/IPDPSW50202.2020.00039

K Yelick, A Buluç, M Awan, A Azad, B Brock, R Egan, S Ekanayake, M Ellis, E Georganas, G Guidi, S Hofmeyr, O Selvitopi, C Teodoropol, L Oliker, The parallelism motifs of genomic data analysis., Philosophical transactions. Series A, Mathematical, physical, and engineering sciences, Pages: 20190394 2020, doi: 10.1098/rsta.2019.0394

F Alexander, A Almgren, J Bell, A Bhattacharjee, J Chen, P Colella, D Daniel, J DeSlippe, L Diachin, E Draeger, A Dubey, T Dunning, T Evans, I Foster, M Francois, T Germann, M Gordon, S Habib, M Halappanavar, S Hamilton, W Hart, Z Henry Huang, A Hungerford, D Kasen, PRC Kent, T Kolev, DB Kothe, A Kronfeld, Y Luo, P Mackenzie, D McCallen, B Messer, S Mniszewski, C Oehmen, A Perazzo, D Perez, D Richards, WJ Rider, R Rieben, K Roche, A Siegel, M Sprague, C Steefel, R Stevens, M Syamlal, M Taylor, J Turner, J-L Vay, AF Voter, TL Windus, K Yelick, Exascale applications: skin in the game., Philosophical transactions. Series A, Mathematical, physical, and engineering sciences, Pages: 20190056 2020, doi: 10.1098/rsta.2019.0056

MM Lee, AD Johnson, KA Yelick, JT Chayes, The Road for Recovery: Aligning COVID-19 efforts and building a more resilient future., IEEE Data Eng. Bull., Pages: 133--140 2020,

GD Hager, MD Hill, KA Yelick, Opportunities and Challenges for Next Generation Computing., CoRR, 2020,

A Zeni, G Guidi, M Ellis, N Ding, MD Santambrogio, SA Hofmeyr, A Buluç, L Oliker, KA Yelick, LOGAN: High-Performance GPU-Based X-Drop Long-Read Alignment., IPDPS, Pages: 462--471 2020,

JM Kreikebaum, KP O Brien, A Morvan, I Siddiqi, "Improving wafer-scale Josephson junction resistance variation in superconducting quantum coherent circuits", Superconductor Science and Technology, 2020, 33, doi: 10.1088/1361-6668/ab8617

Eran O. Ofek, Maayane Soumagnac, Guy Nir, Avishay Gal-Yam, Peter Nugent, Frank Masci, Shri R. Kulkarni, A catalogue of over 10 million variable source candidates in ZTF Data Release 1, Monthly Notices of the RAS, Pages: 5782-5790 2020, doi: 10.1093/mnras/staa2814

M. Smith, C. B. D Andrea, M. Sullivan, A. M\ oller, R. C. Nichol, R. C. Thomas, A. G. Kim, M. Sako, F. J. Castander, A. V. Filippenko, R. J. Foley, L. Galbany, S. Gonz\ alez-Gait\ an, E. Kasai, R. P. Kirshner, C. Lidman, D. Scolnic, D. Brout, T. M. Davis, R. R. Gupta, S. R. Hinton, R. Kessler, J. Lasker, E. Macaulay, R. C. Wolf, B. Zhang, J. Asorey, A. Avelino, B. A. Bassett, J. Calcino, D. Carollo, R. Casas, P. Challis, M. Childress, A. Clocchiatti, S. Crawford, C. Frohmaier, K. Glazebrook, D. A. Goldstein, M. L. Graham, J. K. Hoormann, K. Kuehn, G. F. Lewis, K. S. Mandel, E. Morganson, D. Muthukrishna, P. Nugent, Y. -C. Pan, M. Pursiainen, R. Sharp, N. E. Sommer, E. Swann, B. P. Thomas, B. E. Tucker, S. A. Uddin, P. Wiseman, W. Zheng, T. M. C. Abbott, J. Annis, S. Avila, K. Bechtol, G. M. Bernstein, E. Bertin, D. Brooks, D. L. Burke, A. Carnero Rosell, M. Carrasco Kind, J. Carretero, C. E. Cunha, L. N. da Costa, C. Davis, J. De Vicente, H. T. Diehl, T. F. Eifler, J. Estrada, J. Frieman, J. Garc\ \ia-Bellido, E. Gaztanaga, D. W. Gerdes, D. Gruen, R. A. Gruendl, J. Gschwend, G. Gutierrez, W. G. Hartley, D. L. Hollowood, K. Honscheid, B. Hoyle, D. J. James, M. W. G. Johnson, M. D. Johnson, N. Kuropatkin, T. S. Li, M. Lima, M. A. G. Maia, M. March, J. L. Marshall, P. Martini, F. Menanteau, C. J. Miller, R. Miquel, E. Neilsen, R. L. C. Ogando, A. A. Plazas, A. K. Romer, E. Sanchez, V. Scarpine, M. Schubnell, S. Serrano, I. Sevilla-Noarbe, M. Soares-Santos, F. Sobreira, E. Suchyta, G. Tarle, D. L. Tucker, W. Wester, First Cosmology Results using Supernovae Ia from the Dark Energy Survey: Survey Overview, Performance, and Supernova Spectroscopy, Astronomical Journal, Pages: 267 2020, doi: 10.3847/1538-3881/abc01b

Mattia Bulla, Adam A. Miller, Yuhan Yao, Luc Dessart, Suhail Dhawan, Semeli Papadogiannakis, Rahul Biswas, Ariel Goobar, S. R. Kulkarni, Jakob Nordin, Peter Nugent, Abigail Polin, Jesper Sollerman, Eric C. Bellm, Michael W. Coughlin, Richard Dekany, V. Zach Golkhou, Matthew J. Graham, Mansi M. Kasliwal, Thomas Kupfer, Russ R. Laher, Frank J. Masci, Michael Porter, Ben Rusholme, David L. Shupe, ZTF Early Observations of Type Ia Supernovae. III. Early-time Colors As a Test for Explosion Models and Multiple Populations, Astrophysical Journal, Pages: 48 2020, doi: 10.3847/1538-4357/abb13c

A. A. Miller, Y. Yao, M. Bulla, C. Pankow, E. C. Bellm, S. B. Cenko, R. Dekany, C. Fremling, M. J. Graham, T. Kupfer, R. R. Laher, A. A. Mahabal, F. J. Masci, P. E. Nugent, R. Riddle, B. Rusholme, R. M. Smith, D. L. Shupe, J. van Roestel, S. R. Kulkarni, ZTF Early Observations of Type Ia Supernovae. II. First Light, the Initial Rise, and Time to Reach Maximum Brightness, Astrophysical Journal, Pages: 47 2020, doi: 10.3847/1538-4357/abb13b

Maayane T. Soumagnac, Noam Ganot, Ido Irani, Avishay Gal-yam, Eran O. Ofek, Eli Waxman, Jonathan Morag, Ofer Yaron, Steve Schulze, Yi Yang, Adam Rubin, S. Bradley Cenko, Jesper Sollerman, Daniel A. Perley, Christoffer Fremling, Peter Nugent, James D. Neill, Emir Karamehmetoglu, Eric C. Bellm, Rachel J. Bruch, Rick Burruss, Virginia Cunningham, Richard Dekany, V. Zach Golkhou, Matthew J. Graham, Mansi M. Kasliwal, Nicholas P. Konidaris, Shrinivas R. Kulkarni, Thomas Kupfer, Russ R. Laher, Frank J. Masci, Reed Riddle, Mickael Rigault, Ben Rusholme, Jan van Roestel, Barak Zackay, SN 2018fif: The Explosion of a Large Red Supergiant Discovered in Its Infancy by the Zwicky Transient Facility, Astrophysical Journal, Pages: 6 2020, doi: 10.3847/1538-4357/abb247

E. Pian, P. A. Mazzali, T. J. Moriya, A. Rubin, A. Gal-Yam, I. Arcavi, S. Ben-Ami, N. Blagorodnova, F. Bufano, A. V. Filippenko, M. Kasliwal, S. R. Kulkarni, R. Lunnan, I. Manulis, T. Matheson, P. E. Nugent, E. Ofek, D. A. Perley, S. J. Prentice, O. Yaron, PTF11rka: an interacting supernova at the crossroads of stripped-envelope and H-poor superluminous stellar core collapses, Monthly Notices of the RAS, Pages: 3542-3556 2020, doi: 10.1093/mnras/staa2191

E. Y. Hsiao, P. Hoeflich, C. Ashall, J. Lu, C. Contreras, C. R. Burns, M. M. Phillips, L. Galbany, J. P. Anderson, C. Baltay, E. Baron, S. Castell\ on, S. Davis, Wendy L. Freedman, C. Gall, C. Gonzalez, M. L. Graham, M. Hamuy, T. W. -S. Holoien, E. Karamehmetoglu, K. Krisciunas, S. Kumar, H. Kuncarayakti, N. Morrell, T. J. Moriya, P. E. Nugent, S. Perlmutter, S. E. Persson, A. L. Piro, D. Rabinowitz, M. Roth, M. Shahbandeh, B. J. Shappee, M. D. Stritzinger, N. B. Suntzeff, F. Taddia, S. A. Uddin, Carnegie Supernova Project II: The Slowest Rising Type Ia Supernova LSQ14fmg and Clues to the Origin of Super-Chandrasekhar/03fg-like Events, Astrophysical Journal, Pages: 140 2020, doi: 10.3847/1538-4357/abaf4c

N. Blagorodnova, V. Karambelkar, S. M. Adams, M. M. Kasliwal, C. S. Kochanek, S. Dong, H. Campbell, S. Hodgkin, J. E. Jencson, J. Johansson, S. Koz\lowski, R. R. Laher, F. Masci, P. Nugent, U. Rebbapragada, Progenitor, precursor, and evolution of the dusty remnant of the stellar merger M31-LRN-2015, Monthly Notices of the RAS, Pages: 5503-5517 2020, doi: 10.1093/mnras/staa1872

Maayane T. Soumagnac, Eran O. Ofek, Jingyi Liang, Avishay Gal-yam, Peter Nugent, Yi Yang, S. Bradley Cenko, Jesper Sollerman, Daniel A. Perley, Igor Andreoni, Cristina Barbarino, Kevin B. Burdge, Rachel J. Bruch, Kishalay De, Alison Dugas, Christoffer Fremling, Melissa L. Graham, Matthew J. Hankins, Nora Linn Strotjohann, Shane Moran, James D. Neill, Steve Schulze, David L. Shupe, Brigitta M. Sip\Hocz, Kirsty Taggart, Leonardo Tartaglia, Richard Walters, Lin Yan, Yuhan Yao, Ofer Yaron, Eric C. Bellm, Chris Cannella, Richard Dekany, Dmitry A. Duev, Michael Feeney, Sara Frederick, Matthew J. Graham, Russ R. Laher, Frank J. Masci, Mansi M. Kasliwal, Marek Kowalski, Thomas Kupfer, Adam A. Miller, Mickael Rigault, Ben Rusholme, Early Ultraviolet Observations of Type IIn Supernovae Constrain the Asphericity of Their Circumstellar Material, Astrophysical Journal, Pages: 51 2020, doi: 10.3847/1538-4357/ab94be

Kaylan J. Burleigh, Martin Landriau, Arjun Dey, Dustin Lang, David J. Schlegel, Peter E. Nugent, Robert Blum, Joseph R. Findlay, Douglas P. Finkbeiner, David Herrera, Klaus Honscheid, St\ ephanie Juneau, Ian McGreer, Aaron M. Meisner, John Moustakas, Adam D. Myers, Anna Patej, Edward F. Schlafly, Francisco Valdes, Alistair R. Walker, Benjamin A. Weaver, Christophe Y\ eche, DECaLS Team, MzLS Team, BASS Team, Dynamic Observing and Tiling Strategies for the DESI Legacy Surveys, Astronomical Journal, Pages: 61 2020, doi: 10.3847/1538-3881/ab93b9

C. P. Guti\ errez, M. Sullivan, L. Martinez, M. C. Bersten, C. Inserra, M. Smith, J. P. Anderson, Y. -C. Pan, A. Pastorello, L. Galbany, P. Nugent, C. R. Angus, C. Barbarino, D. Carollo, T. -W. Chen, T. M. Davis, M. Della Valle, R. J. Foley, M. Fraser, C. Frohmaier, S. Gonz\ alez-Gait\ an, M. Gromadzki, E. Kankare, R. Kokotanekova, J. Kollmeier, G. F. Lewis, M. R. Magee, K. Maguire, A. M\ oller, N. Morrell, M. Nicholl, M. Pursiainen, J. Sollerman, N. E. Sommer, E. Swann, B. E. Tucker, P. Wiseman, M. Aguena, S. Allam, S. Avila, E. Bertin, D. Brooks, E. Buckley-Geer, D. L. Burke, A. Carnero Rosell, M. Carrasco Kind, J. Carretero, M. Costanzi, L. N. da Costa, J. De Vicente, S. Desai, H. T. Diehl, P. Doel, T. F. Eifler, B. Flaugher, P. Fosalba, J. Frieman, J. Garc\ \ia-Bellido, D. W. Gerdes, D. Gruen, R. A. Gruendl, J. Gschwend, G. Gutierrez, S. R. Hinton, D. L. Hollowood, K. Honscheid, D. J. James, K. Kuehn, N. Kuropatkin, O. Lahav, M. Lima, M. A. G. Maia, M. March, F. Menanteau, R. Miquel, E. Morganson, A. Palmese, F. Paz-Chinch\ on, A. A. Plazas, M. Sako, E. Sanchez, V. Scarpine, M. Schubnell, S. Serrano, I. Sevilla-Noarbe, M. Soares-Santos, E. Suchyta, M. E. C. Swanson, G. Tarle, D. Thomas, T. N. Varga, A. R. Walker, R. Wilkinson, DES Collaboration, DES16C3cje: A low-luminosity, long-lived supernova, Monthly Notices of the RAS, Pages: 95-110 2020, doi: 10.1093/mnras/staa1452

A. A. Miller, M. R. Magee, A. Polin, K. Maguire, E. Zimmerman, Y. Yao, J. Sollerman, S. Schulze, D. A. Perley, M. Kromer, S. Dhawan, M. Bulla, I. Andreoni, E. C. Bellm, K. De, R. Dekany, A. Delacroix, C. Fremling, A. Gal-Yam, D. A. Goldstein, V. Z. Golkhou, A. Goobar, M. J. Graham, I. Irani, M. M. Kasliwal, S. Kaye, Y. -L. Kim, R. R. Laher, A. A. Mahabal, F. J. Masci, P. E. Nugent, E. Ofek, E. S. Phinney, S. J. Prentice, R. Riddle, M. Rigault, B. Rusholme, T. Schweyer, D. L. Shupe, M. T. Soumagnac, G. Terreran, R. Walters, L. Yan, J. Zolkower, S. R. Kulkarni, The Spectacular Ultraviolet Flash from the Peculiar Type Ia Supernova 2019yvq, Astrophysical Journal, Pages: 56 2020, doi: 10.3847/1538-4357/ab9e05

Michael S. Medford, Jessica R. Lu, William A. Dawson, Casey Y. Lam, Nathan R. Golovich, Edward F. Schlafly, Peter Nugent, Gravitational Microlensing Event Statistics for the Zwicky Transient Facility, Astrophysical Journal, Pages: 144 2020, doi: 10.3847/1538-4357/ab9a4f

M. Pursiainen, C. P. Guti\ errez, P. Wiseman, M. Childress, M. Smith, C. Frohmaier, C. Angus, N. Castro Segura, L. Kelsey, M. Sullivan, L. Galbany, P. Nugent, B. A. Bassett, D. Brout, D. Carollo, C. B. D Andrea, T. M. Davis, R. J. Foley, M. Grayling, S. R. Hinton, C. Inserra, R. Kessler, G. F. Lewis, C. Lidman, E. Macaulay, M. March, A. M\ oller, T. M\ uller, D. Scolnic, N. E. Sommer, E. Swann, B. P. Thomas, B. E. Tucker, M. Vincenzi, T. M. C. Abbott, S. Allam, J. Annis, S. Avila, E. Bertin, D. Brooks, E. Buckley-Geer, D. L. Burke, A. Carnero Rosell, M. Carrasco Kind, L. N. da Costa, J. De Vicente, S. Desai, H. T. Diehl, P. Doel, T. F. Eifler, S. Everett, B. Flaugher, J. Frieman, J. Garc\ \ia-Bellido, E. Gaztanaga, D. W. Gerdes, D. Gruen, R. A. Gruendl, J. Gschwend, G. Gutierrez, D. L. Hollowood, K. Honscheid, D. J. James, A. G. Kim, E. Krause, K. Kuehn, M. A. G. Maia, J. L. Marshall, F. Menanteau, R. Miquel, R. L. C. Ogando, A. Palmese, F. Paz-Chinch\ on, A. A. Plazas, A. Roodman, E. Sanchez, V. Scarpine, M. Schubnell, S. Serrano, I. Sevilla-Noarbe, E. Suchyta, M. E. C. Swanson, G. Tarle, W. Wester, The mystery of photometric twins DES17X1boj and DES16E2bjy, Monthly Notices of the RAS, Pages: 5576-5589 2020, doi: 10.1093/mnras/staa995

M. Smith, M. Sullivan, P. Wiseman, R. Kessler, D. Scolnic, D. Brout, C. B. D Andrea, T. M. Davis, R. J. Foley, C. Frohmaier, L. Galbany, R. R. Gupta, C. P. Guti\ errez, S. R. Hinton, L. Kelsey, C. Lidman, E. Macaulay, A. M\ oller, R. C. Nichol, P. Nugent, A. Palmese, M. Pursiainen, M. Sako, E. Swann, R. C. Thomas, B. E. Tucker, M. Vincenzi, D. Carollo, G. F. Lewis, N. E. Sommer, T. M. C. Abbott, M. Aguena, S. Allam, S. Avila, E. Bertin, S. Bhargava, D. Brooks, E. Buckley-Geer, D. L. Burke, A. Carnero Rosell, M. Carrasco Kind, M. Costanzi, L. N. da Costa, J. De Vicente, S. Desai, H. T. Diehl, P. Doel, T. F. Eifler, S. Everett, B. Flaugher, P. Fosalba, J. Frieman, J. Garc\ \ia-Bellido, E. Gaztanaga, K. Glazebrook, D. Gruen, R. A. Gruendl, J. Gschwend, G. Gutierrez, W. G. Hartley, D. L. Hollowood, K. Honscheid, D. J. James, E. Krause, K. Kuehn, N. Kuropatkin, M. Lima, N. MacCrann, M. A. G. Maia, J. L. Marshall, P. Martini, P. Melchior, F. Menanteau, R. Miquel, F. Paz-Chinch\ on, A. A. Plazas, A. K. Romer, A. Roodman, E. S. Rykoff, E. Sanchez, V. Scarpine, M. Schubnell, S. Serrano, I. Sevilla-Noarbe, E. Suchyta, M. E. C. Swanson, G. Tarle, D. Thomas, D. L. Tucker, T. N. Varga, A. R. Walker, DES Collaboration, First cosmology results using type Ia supernovae from the Dark Energy Survey: the effect of host galaxy properties on supernova luminosity, Monthly Notices of the RAS, Pages: 4426-4447 2020, doi: 10.1093/mnras/staa946

D. L. Coppejans, R. Margutti, G. Terreran, A. J. Nayana, E. R. Coughlin, T. Laskar, K. D. Alexander, M. Bietenholz, D. Caprioli, P. Chandra, M. R. Drout, D. Frederiks, C. Frohmaier, K. H. Hurley, C. S. Kochanek, M. MacLeod, A. Meisner, P. E. Nugent, A. Ridnaia, D. J. Sand, D. Svinkin, C. Ward, S. Yang, A. Baldeschi, I. V. Chilingarian, Y. Dong, C. Esquivia, W. Fong, C. Guidorzi, P. Lundqvist, D. Milisavljevic, K. Paterson, D. E. Reichart, B. Shappee, M. C. Stroh, S. Valenti, B. A. Zauderer, B. Zhang, A Mildly Relativistic Outflow from the Energetic, Fast-rising Blue Optical Transient CSS161010 in a Dwarf Galaxy, Astrophysical Journal Letters, Pages: L23 2020, doi: 10.3847/2041-8213/ab8cc7

C. E. Harris, P. E. Nugent, Outside the Wall: Hydrodynamics of Type I Supernovae Interacting with a Partially Swept-up Circumstellar Medium, Astrophysical Journal, Pages: 122 2020, doi: 10.3847/1538-4357/ab879e

Peter Clark, Kate Maguire, Cosimo Inserra, Simon Prentice, Stephen J. Smartt, Carlos Contreras, Griffin Hossenizadeh, Eric Y. Hsiao, Erkki Kankare, Mansi Kasliwal, Peter Nugent, Melissa Shahbandeh, Charles Baltay, David Rabinowitz, Iair Arcavi, Chris Ashall, Christopher R. Burns, Emma Callis, Ting-Wan Chen, Tiara Diamond, Morgan Fraser, D. Andrew Howell, Emir Karamehmetoglu, Rubina Kotak, Joseph Lyman, Nidia Morrell, Mark Phillips, Giuliano Pignata, Miika Pursiainen, Jesper Sollerman, Maximilian Stritzinger, Mark Sullivan, David Young, LSQ13ddu: a rapidly evolving stripped-envelope supernova with early circumstellar interaction signatures, Monthly Notices of the RAS, Pages: 2208-2228 2020, doi: 10.1093/mnras/stz3598

Igor Andreoni, Daniel A. Goldstein, Mansi M. Kasliwal, Peter E. Nugent, Rongpu Zhou, Jeffrey A. Newman, Mattia Bulla, Francois Foucart, Kenta Hotokezaka, Ehud Nakar, Samaya Nissanke, Geert Raaijmakers, Joshua S. Bloom, Kishalay De, Jacob E. Jencson, Charlotte Ward, Tom\ as Ahumada, Shreya Anand, David A. H. Buckley, Maria D. Caballero-Garc\ \ia, Alberto J. Castro-Tirado, Christopher M. Copperwheat, Michael W. Coughlin, S. Bradley Cenko, Mariusz Gromadzki, Youdong Hu, Viraj R. Karambelkar, Daniel A. Perley, Yashvi Sharma, Azamat F. Valeev, David O. Cook, U. Christoffer Fremling, Harsh Kumar, Kirsty Taggart, Ashot Bagdasaryan, Jeff Cooke, Aishwarya Dahiwale, Suhail Dhawan, Dougal Dobie, Pradip Gatkine, V. Zach Golkhou, Ariel Goobar, Andreas Guerra Chaves, Matthew Hankins, David L. Kaplan, Albert K. H. Kong, Erik C. Kool, Siddharth Mohite, Jesper Sollerman, Anastasios Tzanidakis, Sara Webb, Keming Zhang, GROWTH on S190814bv: Deep Synoptic Limits on the Optical/Near-infrared Counterpart to a Neutron Star-Black Hole Merger, Astrophysical Journal, Pages: 131 2020, doi: 10.3847/1538-4357/ab6a1b

S. Dhawan, J. Johansson, A. Goobar, R. Amanullah, E. M\ ortsell, S. B. Cenko, A. Cooray, O. Fox, D. Goldstein, R. Kalender, M. Kasliwal, S. R. Kulkarni, W. H. Lee, H. Nayyeri, P. Nugent, E. Ofek, R. Quimby, Magnification, dust, and time-delay constraints from the first resolved strongly lensed Type Ia supernova iPTF16geu, Monthly Notices of the RAS, Pages: 2639-2654 2020, doi: 10.1093/mnras/stz2965

Aziza Suleymanzade, Alexander Anferov, Mark Stone, Ravi K Naik, Andrew Oriani, Jonathan Simon, David Schuster, "A tunable high-Q millimeter wave cavity for hybrid circuit and cavity QED experiments", Applied Physics Letters, 2020, 116:104001, doi: 10.1063/1.5137900

Akash Dixit, Srivatsan Chakram, Ankur Agrawal, Ravi Naik, David Schuster, Aaron Chou, Using Superconducting Qubits for Axion Dark Matter Detection, Bulletin of the American Physical Society, 2020,

Gang Huang, Yilun Xu, Ravi Naik, Bradley Mitchell, David Santiago, Irfan Siddiqi, QubiC-An open FPGA based Qubit Control system, Bulletin of the American Physical Society, 2020,

Akel Hashim, Kasra Nowrouzi, Alexis Morvan, Ravi Naik, John Mark Kreikebaum, Irfan Siddiqi, Experimental Realization of Randomized Compiling for in-situ Error Reduction, Bulletin of the American Physical Society, 2020,

Ravi Naik, Bradley Mitchell, Akel Hashim, John Mark Kreikebaum, Irfan Siddiqi, Fidelity Optimization of the Cross-resonance Gate on a Multi-qubit Quantum Processor, Bulletin of the American Physical Society, 2020,

Bradley Mitchell, Ravi Naik, Akel Hashim, John Mark Kreikebaum, Irfan Siddiqi, Cross-resonance Dynamics with Tunable Transmon Qubits, Bulletin of the American Physical Society, 2020,

Yilun Xu, Gang Huang, Ravi Naik, Bradley Mitchell, David Santiago, Irfan Siddiqi, Automatic single qubit characterization with QubiC, Bulletin of the American Physical Society, 2020,

Srivatsan Chakram, Kevin He, Akash V Dixit, Andrew E Oriani, Ravi K Naik, Nelson Leung, Hyeokshin Kwon, Wen-Long Ma, Liang Jiang, David I Schuster, Multimode photon blockade, arXiv preprint arXiv:2010.15292, 2020,

Srivatsan Chakram, Andrew E Oriani, Ravi K Naik, Akash V Dixit, Kevin He, Ankur Agrawal, Hyeokshin Kwon, David I Schuster, Seamless high-Q microwave cavities for multimode circuit QED, arXiv preprint arXiv:2010.16382, 2020,

Yilun Xu, Gang Huang, Jan Balewski, Ravi Naik, Alexis Morvan, Bradley Mitchell, Kasra Nowrouzi, David I Santiago, Irfan Siddiqi, QubiC: An open source FPGA-based control and measurement system for superconducting quantum information processors, arXiv preprint arXiv:2101.00071, 2020, doi: 101.00071

Gang Huang, Yilun Xu, Ravi Naik, Bradley Mitchell, David Santiago, Irfan Siddiqi, Qubit fast reset with QubiC, Bulletin of the American Physical Society, 2020,

2019

Reinhard Gentz, Sean Peisert, "An Examination and Survey of Random Bit Flips and Scientific Computing", Trusted CI Report, December 20, 2019,

D. Fan, A. Nonaka, A.S. Almgren, A. Harpole, M. Zingale, "MAESTROeX: A Massively Parallel Low Mach Number Astrophysical Solver", The Astrophysical Journal, December 19, 2019,

Timothy T Duignan, Gregory Schenter, John L Fulton, Thomas Huthwelker, Mahalingam Balasubramanian, Mirza Galib, Marcel Baer, Jan Wilhelm, Jürg Hutter, Mauro Del Ben, Xiu Song Zhao, Christopher Jay Mundy, "Quantifying the Hydration Structure of Sodium and Potassium Ions: Taking Additional Steps on Jacob's Ladder", Physical Chemistry Chemical Physics, December 19, 2019, doi: 10.1039/C9CP06161D

D. Fan, A. Nonaka, A. S. Almgren, D. E. Willcox, A. Harpole, and M. Zingale, "MAESTROeX: A Massively Parallel Low Mach Number Astrophysical Solver", Journal of Open Source Software, December 19, 2019,

Richard Warren, Jerome Soumagne, Jingqing Mu, Houjun Tang, Suren Byna, Bin Dong, Quincey Koziol, "Analysis in the Data Path of an Object-centric Data Management System", 26th IEEE International Conference on High Performance Computing, Data, and Analytics (HiPC 2019), December 18, 2019,

Houjun Tang, Suren Byna, Stephen Bailey, Zarija Lukic, Jialin Liu, Quincey Koziol, Bin Dong, "Tuning Object-centric Data Management Systems for Large Scale Scientific Applications", 26th IEEE International Conference on High Performance Computing, Data, and Analytics (HiPC 2019), December 18, 2019,

Wei Zhang, Suren Byna, Chenxu Niu, Yong Chen, "Exploring Metadata Search Essentials for Scientific Data Management", 26th IEEE International Conference on High Performance Computing, Data, and Analytics (HiPC 2019), December 17, 2019,

Amir Kamil, John Bachan, Scott B. Baden, Dan Bonachea, Paul Hargrove, Steven Hofmeyr, Kathy Yelick, UPC++ Tutorial (NERSC Dec 2019), National Energy Research Scientific Computing Center (NERSC), December 16, 2019,

This event was a repeat of the tutorial delivered on November 1, but with the restoration of the hands-on component which was omitted due to uncertainty surrounding the power outage at NERSC.

UPC++ is a C++11 library providing classes and functions that support Partitioned Global Address Space (PGAS) programming. UPC++ provides mechanisms for low-overhead one-sided communication, moving computation to data through remote-procedure calls, and expressing dependencies between asynchronous computations and data movement. It is particularly well-suited for implementing elaborate distributed data structures where communication is irregular or fine-grained. The UPC++ interfaces are designed to be composable and similar to those used in conventional C++. The UPC++ programmer can expect communication to run at close to hardware speeds.

In this tutorial we introduced basic concepts and advanced optimization techniques of UPC++. We discussed the UPC++ memory and execution models and walked through implementing basic algorithms in UPC++. We also discussed irregular applications and how to take advantage of UPC++ features to optimize their performance. The tutorial included hands-on exercises with basic UPC++ constructs. Registrants were given access to run their UPC++ exercises on NERSC’s Cori (currently the #14 fastest computer in the world).

NERSC Dec 2019 Event page

tutorial 2019 12

 

Schneider, Joseph D.; Domann, John P.; Panduranga, M. K.; Tiwari, Sidhant; Shirazi, Paymon; Yao, Zhi Jackie; Sennott, Casey; Shahan, David; Selvin, Skyler; McKnight, Geoff, et al., "Experimental demonstration and operating principles of a multiferroic antenna", Journal, December 14, 2019, 126:224104, doi: 10.1063/1.5126047

Hans Johansen, Daniel Martin, Esmond Ng, "High-resolution Treatment of Topography and Grounding Line Dynamics in BISICLES", AGU 2019 Fall Meeting, December 13, 2019,

Yao, Zhi Jackie; Tiwari, Sidhant; Lu, Ting; Rivera, Jesse; Luong, Kevin Q. T.; Candler, Robert N.; Carman, Gregory P.; Wang, Yuanxun Ethan, "Modeling of multiple dynamics in the radiation of bulk acoustic wave (BAW) antennas", Journal, December 13, 2019, 5:7-20, doi: 10.1109/JMMCT.2019.2959596

Daniel F. Martin, James Parkinson, Andrew Wells, Richard Katz, "3D convection, phase change, and solute transport in mushy sea ice", AGU 2019 Fall Meeting, December 12, 2019,

Samuel Kachuck, Daniel Martin, Jeremy Bassis, Stephen Price, "Rapid viscoelastic deformation slows marine ice sheet instability at Pine Island Glacier", AGU 2019 Fall Meeting, December 10, 2019,

A. Lazar, A. Ballow, L. Jin, C. A. Spurlock, A. Sim, K. Wu, "Machine Learning for Prediction of Mid to LongTerm Habitual Transportation Mode Use", International Workshop on Big Data Tools, Methods, and Use Cases for Innovative Scientific Discovery (BTSD), in conjunction with the IEEE International Conference on Big Data (Big Data), 2019, doi: 10.1109/BigData47090.2019.9006411

Chaincy Kuo, Daniel Feldman, Daniel Martin, "Quantification of seasonal heat retention by sea-ice: calculations from analytic surface-energy balance", AGU Fall Meeting 2019, December 9, 2019,

Marc Grau Davis, Ethan Smith, Ana Tudor, Koushik Sen, Irfan Siddiqi, Costin Iancu, "Heuristics for Quantum Compiling with a Continuous Gate Set", 3rd International Workshop on Quantum Compilation as part of the International Conference On Computer Aided Design 2019, December 5, 2019,

We present an algorithm for compiling arbitrary unitaries into a sequence of gates native to a quantum processor. As accurate CNOT gates are hard for the foreseeable Noisy- Intermediate-Scale Quantum devices era, our A* inspired algorithm attempts to minimize their count, while accounting for connectivity. We discuss the search strategy together with metrics to expand the solution frontier. For a workload of circuits with complexity appropriate for the NISQ era, we produce solutions well within the best upper bounds published in literature and match or exceed hand tuned implementations, as well as other existing synthesis alternatives. In particular, when comparing against state-of-the-art available synthesis packages we show 2.4x average (up to 5.3x) reduction in CNOT count. We also show how to re-target the algorithm for a different chip topology and native gate set, while obtaining similar quality results. We believe that empirical tools like ours can facilitate algorithmic exploration, gate set discovery for quantum processor designers, as well as providing useful optimization blocks within the quantum compilation tool-chain.

Amir Teshome Wonjiga, Louis Rilling, Christine Morin, Sean Peisert, "Blockchain as a Trusted Component in Cloud SLA Verification", Proceedings of the International Workshop on Cloud, IoT and Fog Security (CIFS), co-located with the 12th IEEE/ACM International Conference on Utility and Cloud Computing (UCC), Auckland, New Zealand, December 2019, 93-100, doi: 10.1145/3368235.3368872

M Kiran, B Mohammed and N. Krishnaswamy, "DeepRoute: Herding Elephant and Mice Flows with Reinforcement Learning", 2nd IFIP International Conference on Machine Learning for Networking (MLN'2019), December 2, 2019, doi: 10.1007/978-3-030-45778-5_20

Yong Shi, Daniel R. Ladiges, John E. Sader, "Origin of spurious oscillations in lattice Boltzmann simulations of oscillatory noncontinuum gas flows", Physical Review E, November 25, 2019, 100,

Tirthak Patel, Suren Byna, Glenn K. Lockwood, Devesh Tiwari, "Revisiting I/O Behavior in Large-Scale Storage Systems: The Expected and the Unexpected", Supercomputing 2019 (SC19), November 24, 2019, doi: 10.1145/3295500.3356183

Junmin Gu, Burlen Loring, Kesheng Wu, E. Wes Bethel, "HDF5 as a vehicle for in transit data movement", The Workshop on In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization (ISAV'19), 2019, doi: 10.1145/3364228.3364237

Tuowen Zhao, Mary Hall, Samuel Williams, Hans Johansen, "Exploiting Reuse and Vectorization in Blocked Stencil Computations on CPUs and GPUs", Supercomputing (SC), November 2019,

George Michelogiannakis, Yiwen Shen, Min Yeh Teh, Xian Meng, Benjamin Aivazi, Taylor Groves, John Shalf, Madeleine Glick, Manya Ghobadi, Larry Dennison, Keren Bergman, "Bandwidth Steering in HPC Using Silicon Nanophotonics", SC19: The International Conference for High Performance Computing, Networking, Storage, and Analysis, November 2019,

George Michelogiannakis, Bandwidth Steering in HPC Using Silicon Nanophotonics, SC19: The International Conference for High Performance Computing, Networking, Storage, and Analysis, November 20, 2019,

Donghe Kang, Oliver Rübel, Suren Byna, Spyros Blanas, "Comparison of Array Management Library Performance - A Neuroscience Use Case", SC19 Poster, November 20, 2019,

L. Jin, A. Lazar, J. Sears, A. Todd, A. Sim, K. Wu, C. A. Spurlock, Life course as a contextual system to investigate the effects of life events, gender and generation on travel mode usage, The Behavior, Energy & Climate Change Conference (BECC), 2019,

Wei Zhang, Suren Byna, Houjun Tang, Brody Williams, Yong Chen, "MIQS: Metadata Indexing and erying Service for Self-Describing File Formats", The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC19), November 19, 2019,

Houjun Tang, Quincey Koziol, Suren Byna, John Mainzer, Tonglin Li, "Enabling Transparent Asynchronous I/O using Background Threads", 2019 IEEE/ACM Fourth International Parallel Data Systems Workshop (PDSW 2019), November 19, 2019, doi: DOI 10.1109/PDSW49588.2019.00006

Megha Agarwal, Divyansh Singhvi, Preeti Malakar, Suren Byna, "Active Learning-based Automatic Tuning and Prediction of Parallel I/O Performance", 2019 IEEE/ACM Fourth International Parallel Data Systems Workshop (PDSW), November 19, 2019, doi: DOI 10.1109/PDSW49588.2019.00007

Glenn K. Lockwood, Shane Snyder, Suren Byna, Philip Carns, Nicholas J. Wright, "Understanding Data Motion in the Modern HPC Data Center", 2019 IEEE/ACM Fourth International Parallel Data Systems Workshop (PDSW), November 19, 2019, doi: DOI 10.1109/PDSW49588.2019.00012

P. Linton, W. Melodia, A. Lazar, D. Agarwal, L. Bianchi, D. Ghoshal, K. Wu, G. Pastorello, L. Ramakrishnan, "Identifying Time Series Similarity in Large-Scale Earth System Datasets", The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC19), 2019,

Nan Ding, Samuel Williams, "An Instruction Roofline Model for GPUs", Performance Modeling, Benchmarking, and Simulation (PMBS), BEST PAPER AWARD, November 18, 2019,

Zhe Bai, N. Benjamin Erichson, Muralikrishnan Gopalakrishnan Meena, Kunihiko Taira, Steven L. Brunton, "Randomized methods to characterize large-scale vortical flow networks", PLOS ONE Journal, 2019, doi: 10.1371/journal.pone.0225265

Nan Ding, Samuel Williams, An Instruction Roofline Model for GPUs, Performance Modeling, Benchmarking, and Simulation (PMBS), BEST PAPER AWARD, November 18, 2019,

Paul H. Hargrove, Dan Bonachea, "Efficient Active Message RMA in GASNet Using a Target-Side Reassembly Protocol (Extended Abstract)", IEEE/ACM Parallel Applications Workshop, Alternatives To MPI+X (PAW-ATM), Lawrence Berkeley National Laboratory Technical Report, November 17, 2019, LBNL 2001238, doi: 10.25344/S4PC7M

GASNet is a portable, open-source, high-performance communication library designed to efficiently support the networking requirements of PGAS runtime systems and other alternative models on future exascale machines. This paper investigates strategies for efficient implementation of GASNet’s “AM Long” API that couples an RMA (Remote Memory Access) transfer with an Active Message (AM) delivery.
We discuss several network-level protocols for AM Long and propose a new target-side reassembly protocol. We present a microbenchmark evaluation on the Cray XC Aries network hardware. The target-side reassembly protocol on this network improves AM Long end-to-end latency by up to 33%, and the effective bandwidth by up to 49%, while also enabling asynchronous source completion that drastically reduces injection overheads.
The improved AM Long implementation for Aries is available in GASNet-EX release v2019.9.0 and later.

Oguz Selvitopi, Cevdet Aykanat, "Regularizing irregularly sparse point-to-point communications", SC '19: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, ACM, November 2019, doi: 10.1145/3295500

Khaled Ibrahim, Samuel Williams, Leonid Oliker, "Performance Analysis of GPU Programming Models using the Roofline Scaling Trajectories", International Symposium on Benchmarking, Measuring and Optimizing (Bench), BEST PAPER AWARD, November 2019,

B Mohammed, M Kiran, N Krishnaswamy, "DeepRoute on Chameleon: Experimenting with Large-scale Reinforcement Learning and SDN on Chameleon Testbed", IEEE 27th International Conference on Network Protocols (ICNP), IEEE, November 14, 2019, 1-2, doi: 10.1109/ICNP.2019.8888090

George Papadimitriou, Mariam Kiran, Cong Wang, Anirban Mandal, Ewa Deelman, "Training Classifiers to Identify TCP Signatures in Scientific Workflows", INDIS, SC19, November 14, 2019,

Dan Bonachea, Paul H. Hargrove, "GASNet-EX: A High-Performance, Portable Communication Library for Exascale", LNCS 11882: Proceedings of Languages and Compilers for Parallel Computing (LCPC'18), edited by Hall M., Sundar H., November 2019, 11882:138-158, doi: 10.1007/978-3-030-34627-0_11

Partitioned Global Address Space (PGAS) models, typified by such languages as Unified Parallel C (UPC) and Co-Array Fortran, expose one-sided communication as a key building block for High Performance Computing (HPC) applications. Architectural trends in supercomputing make such programming models increasingly attractive, and newer, more sophisticated models such as UPC++, Legion and Chapel that rely upon similar communication paradigms are gaining popularity.

GASNet-EX is a portable, open-source, high-performance communication library designed to efficiently support the networking requirements of PGAS runtime systems and other alternative models in future exascale machines. The library is an evolution of the popular GASNet communication system, building upon over 15 years of lessons learned. We describe and evaluate several features and enhancements that have been introduced to address the needs of modern client systems. Microbenchmark results demonstrate the RMA performance of GASNet-EX is competitive with several MPI-3 implementations on current HPC systems.

Christine T. Wolf, Julia Bullard, Stacy Wood, Amelia Acker, Drew Paine, Charlotte P. Lee, "Mapping the “How” of Collaborative Action: Research Methods for Studying Contemporary Sociotechnical Processes", CSCW '19: Conference Companion Publication of the 2019 on Computer Supported Cooperative Work and Social Computing, November 10, 2019, doi: 10.1145/3311957.3359441

Process has been a concern since the beginning of CSCW. Developments in sociotechnical landscapes raise new challenges for studying processes (e.g., massive online communities bringing together vast crowds; Big Data technologies connecting many through the flow of data). This re-opens questions about how we study, document, conceptualize, and design to support processes in complex, contemporary sociotechnical systems. This one-day workshop will bring together researchers to discuss the CSCW community’s unique focus and methodological toolkit for studying process and workflow; provide a collaborative space for the improvement and extension of research projects within this space; and catalyze a network of scholars with expertise and interest in addressing challenging methodological questions around studying process in contemporary, sociotechnical systems.

Mahdi Jamei, Raksha Ramakrishna, Teklemariam Tesfay, Reinhard Gentz, Ciaran Roberts, Anna Scaglione, Sean Peisert, "Phasor Measurement Units Optimal Placement and Performance Limits for Fault Localization", IEEE Journal on Selected Areas in Communications (J-SAC), Special Issue on Communications and Data Analytics in Smart Grid, November 6, 2019, 38(1):180-192, doi: 10.1109/jsac.2019.2951971

J. Balcas, H. Newman, M. Spiropulu, X. Yang, T. Lehman, I. Monga, C. Guok, J. MacAuley, A. Sim, P. Demar, "SDN for End-to-End Networking at Exascale", the 24th International Conference on Computing in High Energy and Nuclear Physics (CHEP2019), 2019,

Marzieh Lenjani, Patricia Gonzalez, Elaheh Sadredini, M Arif Rahman, Mircea R Stan, "An overflow-free quantized memory hierarchy in general-purpose processors", International Symposium on Workload Characterization (IISWC), Orlando, FL, USA, IEEE, November 3, 2019, doi: 10.1109/IISWC47752.2019.9042035

Data movement comprises a significant portion of energy consumption and execution time in modern applications. Accelerator designers exploit quantization to reduce the bitwidth of values and reduce the cost of data movement. However, any value that does not fit in the reduced bitwidth results in an overflow (we refer to these values as outliers). Therefore accelerators use quantization for applications that are tolerant to overflows. We observe that in most applications the rate of outliers is low and values are often within a narrow range, providing the opportunity to exploit quantization in general-purpose processors. However, a software implementation of quantization in general-purpose processors has three problems. First, the programmer has to manually implement conversions and the additional instructions that quantize and dequantize values, imposing a programmer's effort and performance overhead. Second, to cover outliers, the bitwidth of the quantized values often become greater than or equal to the original values. Third, the programmer has to use standard bitwidth; otherwise, extracting non-standard bitwidth (i.e., 1-7, 9-15, and 17-31) for representing narrow integers exacerbates the overhead of software-based quantization. The key idea of this paper is to propose a hardware support in the memory hierarchy of general-purpose processors for quantization, which represents values by few and flexible numbers of bits and stores outliers in their original format in a separate space, preventing any overflow. We minimize metadata and the overhead of locating quantized values using a software-hardware interaction that transfers quantization parameters and data layout to hardware. As a result, our approach has three advantages over cache compression techniques: (i) less metadata, (ii) higher compression ratio for floating-point values and cache blocks with multiple data types, and (iii) lower overhead for locating the compressed blocks. It delivers on average 1.40/1.45/1.56× speedup and 24/26/30% energy reduction compared to a baseline that uses full-length variables in a 4/8/16-core system. Our approach also provides 1.23× speedup, in a 4-core system, compared to the state of the art cache compression techniques and adds only 0.25% area overhead to the baseline processor.

Patricia Gonzalez-Guerrero, Mircea R. Stan, "Asynchronous Stochastic Computing", 53rd Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, USA, IEEE, November 3, 2019, doi: 10.1109/IEEECONF44664.2019.9049011

Asynchronous Stochastic Computing (ASC) leverages Synchronous Stochastic Computing (SSC) advantages and addresses its drawbacks. In SSC a multiplier is a single AND gate, saving ~ 90% of power and area compared with a typical 8bit binary multiplier. The key for SSC power-area efficiency comes from mapping numbers to streams of 1s and 0s. Despite the power-area efficiency, SSC drawbacks such as long latency, costly clock distribution network (CDN), and expensive stream generation, causes the energy consumption to grow prohibitively large. In this work, we introduce the foundations for ASC using Continuous-time-Markov-chains, and analyze the computing error due to random fluctuations. In ASC data is mapped to asynchronous-continuous-time streams, which yields two advantages over the synchronous counterpart: (1) CDN elimination, and (2) better accuracy performance. We compare ASC with SSC for three applications: (1) multiplication, (2) an image processing algorithm: gamma-correction, and (3) a singlelayer of a fully-connected artificial-neural-network (ANN) using a FinFET1X technology. Our Matlab, Spice-level simulations and post-place&route (P&R) reports demonstrate that ASC yields savings of 10%-55%, 33%-44%, and 50% in latency, power, and energy respectively. These savings make ASC a good candidate to address the ultra-low-power requirements of machine learning for the IoT.

Amir Kamil, John Bachan, Scott B. Baden, Dan Bonachea, Rob Egan, Paul Hargrove, Steven Hofmeyr, Mathias Jacquelin, Kathy Yelick, UPC++ Tutorial (NERSC Nov 2019), National Energy Research Scientific Computing Center (NERSC), November 1, 2019,

UPC++ is a C++11 library providing classes and functions that support Partitioned Global Address Space (PGAS) programming. UPC++ provides mechanisms for low-overhead one-sided communication, moving computation to data through remote-procedure calls, and expressing dependencies between asynchronous computations and data movement. It is particularly well-suited for implementing elaborate distributed data structures where communication is irregular or fine-grained. The UPC++ interfaces are designed to be composable and similar to those used in conventional C++. The UPC++ programmer can expect communication to run at close to hardware speeds.

In this tutorial we will introduce basic concepts and advanced optimization techniques of UPC++. We will discuss the UPC++ memory and execution models and walk through implementing basic algorithms in UPC++. We will also look at irregular applications and how to take advantage of UPC++ features to optimize their performance.

NERSC Nov 2019 Event Page

 

Mark Adams, Stephen Cornford, Daniel Martin, Peter McCorquodale, "Composite matrix construction for structured grid adaptive mesh refinement", Computer Physics Communications, November 2019, 244:35-39, doi: 10.1016/j.cpc.2019.07.006

Pooria Mohammadiyaghni, George Michelogiannakis, Paul V. Gratz, "SpecLock: Speculative Lock Forwarding", International Conference on Computer Design (ICCD), November 2019,

L. Yang, Z. Wen, C. Yang and Y. Zhang, "`Block Algorithms with Augmented Rayleigh-Ritz Projections for Large-Scale Eigenpair Computation", Journal of Computational Mathematics, November 1, 2019, 37:889-915, doi: 10.4208/jcm.1910-m2019-0034

Alexandra Ballow, Alina Lazar (Advisor), Alex Sim (Advisor), Kesheng Wu (Advisor), "Handling Missing Values in Joint Sequence Analysis", ACM Richard Tapia Celebration of Diversity in Computing (TAPIA 2019), ACM Student Research Competition (SRC), First place winner, 2019,

Thomas W. Edgar, Aditya Ashok, Garret E. Seppala, K.M. Arthur-Durrett, M. Engels, Reinhard Gentz, Sean Peisert, "An Automated Disruption-Tolerant Key Management Framework for Critical Systems", Journal of Information Warfare, October 8, 2019, 18(4):85-124, doi: https://www.jinfowar.com/journal/volume-18-issue-4/automated-disruption-tolerant-device-authentication-key-management-framework-critical-systems

Brandon Krull, Michael Minion, "Parallel-In-Time Magnus Integrators", SIAM Journal on Scientific Computing, October 1, 2019,

Patricia Gonzalez-Guerrero, Tommy Tracy II, Xinfei Guo, Mircea R Stan, "Towards low-power random forest using asynchronous computing with streams", Tenth International Green and Sustainable Computing Conference (IGSC), EEE Computer Society, October 1, 2019, doi: 10.1109/IGSC48788.2019.8957193

We propose a sensor architecture for the internet of things (IoT), smartdust or edge-intelligence (EI) that combines near-analog-memory (NAM) processing and asynchronous computing with streams (ACS) addressing the need for machine learning (ML) capabilities at low power budgets. In ACS an analog value is mapped to an asynchronous stream that can take one of two values (vh, vl). This stream-based data representation enables area-power efficient computing units such as the multiplier implemented as an AND gate yielding savings in power of 90% compared with digital approaches. However, a major bottleneck for computing on streams, vision sensors, and NAM approaches is the cost of analog-to-digital (ADC) and digital-to-stream-to-digital converters. Our NAM-ACS architecture, simplifies the sensor and eliminates the need for the expensive conversions. The architecture is tailored for random forest (Raf), a ML algorithm, chosen for its ability to classify using a reduced number of features. Our simulations show that using an analog-memory array of 256 512, the power consumption of the ACS-core combined with the memory interface is comparable with the consumption of an ADC based memory interface, obtaining an accuracy of 83%.

Reinhard Gentz, Sean Peisert, Joshua Boverhof, Daniel Gunter, "SPARCS: Stream-Processing Architecture applied in Real-time Cyber-physical Security", Proceedings of the 15th IEEE International Conference on e-Science (eScience), San Diego, CA, IEEE, September 2019, doi: 10.1109/eScience.2019.00028

Reinhard Gentz, Héctor García Martin, Edward Baidoo, Sean Peisert, "Workflow Automation in Liquid Chromatography Mass Spectrometry", Proceedings of the 15th IEEE International Conference on e-Science (eScience), San Diego, CA, IEEE, September 2019, doi: 10.1109/eScience.2019.00095

Bin Wang, Rongxin Yin, Doug Black and Cy Chan, "Multistage and decentralized operations of electric vehicles within the California demand response markets", Decision Making Applications in Modern Power Systems, (Academic Press, Elsevier: September 21, 2019) Pages: 411-439 doi: https://doi.org/10.1016/B978-0-12-816445-7.00016-5

John Bachan, Scott Baden, Dan Bonachea, Paul Hargrove, Steven Hofmeyr, Mathias Jacquelin, Amir Kamil, Brian van Straalen, "UPC++ v1.0 Programmer’s Guide, Revision 2019.9.0", Lawrence Berkeley National Laboratory Tech Report, September 2019, LBNL 2001236, doi: 10.25344/S4V30R

UPC++ is a C++11 library that provides Partitioned Global Address Space (PGAS) programming. It is designed for writing parallel programs that run efficiently and scale well on distributed-memory parallel computers. The PGAS model is single program, multiple-data (SPMD), with each separate constituent process having access to local memory as it would in C++. However, PGAS also provides access to a global address space, which is allocated in shared segments that are distributed over the processes. UPC++ provides numerous methods for accessing and using global memory. In UPC++, all operations that access remote memory are explicit, which encourages programmers to be aware of the cost of communication and data movement. Moreover, all remote-memory access operations are by default asynchronous, to enable programmers to write code that scales well even on hundreds of thousands of cores.

John Bachan, Scott Baden, Dan Bonachea, Paul Hargrove, Steven Hofmeyr, Mathias Jacquelin, Amir Kamil, Brian van Straalen, "UPC++ v1.0 Specification, Revision 2019.9.0", Lawrence Berkeley National Laboratory Tech Report, September 14, 2019, LBNL 2001237, doi: 10.25344/S4ZW2C

UPC++ is a C++11 library providing classes and functions that support Partitioned Global Address Space (PGAS) programming. We are revising the library under the auspices of the DOE’s Exascale Computing Project, to meet the needs of applications requiring PGAS support. UPC++ is intended for implementing elaborate distributed data structures where communication is irregular or fine-grained. The UPC++ interfaces for moving non-contiguous data and handling memories with different optimal access methods are composable and similar to those used in conventional C++. The UPC++ programmer can expect communication to run at close to hardware speeds. The key facilities in UPC++ are global pointers, that enable the programmer to express ownership information for improving locality, one-sided communication, both put/get and RPC, futures and continuations. Futures capture data readiness state, which is useful in making scheduling decisions, and continuations provide for completion handling via callbacks. Together, these enable the programmer to chain together a DAG of operations to execute asynchronously as high-latency dependencies become satisfied.

S Werner, P Fotouhi, X Xiao, M Fariborz, SJB Yoo, G Michelogiannakis, D Vasudevan, "3D photonics as enabling technology for deep 3D DRAM stacking", Proceedings of the International Symposium on Memory Systems - MEMSYS 19, ACM Press, September 2019, doi: 10.1145/3357526.3357559

Bin Wang, Cy Chan, Divya Somasi, Jane Macfarlane, Eric Rask, "Data-Driven Energy Use Estimation in Large Scale Transportation Networks", Proceedings of the 2nd ACM/EIGSCC Symposium on Smart Cities and Communities - SCC '19, ACM Press, September 10, 2019,

Revathi Jambunathan, Andrew Myers, Donald Willcox, Jean-Luc Vay, Ann Almgren, Diana Amorim, John Bell, Kevin Gott, Axel Huebl, Remi Lehe, Micahel Rowan, Olga Shapoval, Maxence Thevenet, Weiqun Zhang, "WarpX: Towards exascale modeling of pulsar magnetospheres", Connecting Micro and Macro Scales: Acceleration, Reconnection, and Dissipation in Astrophysical Plasmas, September 9, 2019,

Doru Thom Popovici, Devangi N. Parikh, Daniele G. Spampinato, Tze Meng Low, "Exploiting Symmetries of Small Prime-Sized DFTs", PPAM 2019, 2019,

Patricia Gonzalez-Guerrero, Stephen G Wilson, Mircea R Stan, "Error-latency Trade-off for Asynchronous Stochastic Computing with ΣΔ Streams for the IoT", International System-on-Chip Conference (SOCC), Singapore, IEEE, September 3, 2019, doi: 10.1109/SOCC46988.2019.1570548453

Asynchronous stochastic computing (ASC) using continuous-time-asynchronous ΣΔ modulators (SC-AΣΔM) has the potential to enable ultra-low-power, on-node machine learning algorithms for the next generation of sensors for the Internet of Things (IoT). Similar to synchronous stochastic computing (SSC 1 ), in SC-AΣΔM complex processing units can be implemented with simple gates because numbers are represented with streams. For example a multiplier is implemented with a XNOR gate, yielding savings in power and area of 90% compared with the typical binary approach. Previous work demonstrated that SC-AΣΔM leverages SSC advantages and addresses its drawbacks, achieving significant savings in energy, power and latency. In this work, we study a theoretical model to determine the fundamental limits of accuracy and computing time for SCAΣΔM. Since the ΣΔ streams are periodic the final computing error is non-zero and depends on the period of the input streams. We validate our theoretical model with Spice-level simulations and evaluate the power and energy consumption using a standard FinFet1X2 technology for two cases: 1) multiplication and 2) gamma correction, an image processing algorithm. Our work determines circuit design guidelines for SC-AΣΔM and shows that multiplication with SC-AΣΔM requires at least 6X less time than SSC. The latency reduction and novel architecture positively impacts the overall energy consumption in the IoT node, enabling savings in energy of 79% compared with the binary approach.

Adrián P. Diéguez, Margarita Amor, Ramón Doallo, "Tree Partitioning Reduction: A New Parallel Partition Method for Solving Tridiagonal Systems", ACM Transactions on Mathematical Software, September 2019, 45:1-26, doi: 10.1145/3328731

Melissa Stockman, Dipankar Dwivedi, Reinhard Gentz, Sean Peisert, "Detecting Programmable Logic Controller Code Using Machine Learning", International Journal of Critical Infrastructure Protection, September 2019, vol. 26,, doi: 10.1016/j.ijcip.2019.100306

Timur Takhtaganov, Zarija Lukić, Juliane Mueller, Dmitriy Morozov, "Cosmic Inference: Constraining Parameters With Observations and Highly Limited Number of Simulations", Astrophysical Journal (in review), 2019,

Charlene Yang, Thorsten Kurth, Samuel Williams, "Hierarchical Roofline analysis for GPUs: Accelerating performance optimization for the NERSC-9 Perlmutter system", Concurrency and Computation: Practice and Experience (CCPE), August 2019, doi: 10.1002/cpe.5547

Antoine Bambade, Kesheng Wu, "An Assessment of the Prediction Quality of VPIN", Advanced Analytics and Artificial Intelligence Applications, (IntechOpen: 2019)

M. Zingale, M.P. Katz, J.B. Bell, M.L. Minion, A.J. Nonaka, W. Zhang, "Improved Coupling of Hydrodynamics and Nuclear Reactions via Spectral Deferred Corrections", August 14, 2019,

Knut Sverdrup, Ann S. Almgren, Nikolaos Nikiforakis, "An embedded boundary approach for efficient simulations of viscoplastic fluids in three dimensions", August 10, 2019,

L. Esclapez, V. Ricchiuti, J.B. Bell, M.S. Day, "A spectral deferred correction strategy for low Mach number flows subject to electric fields", August 10, 2019,

D. R. Ladiges, A. J. Nonaka, J. B. Bell, A. L. Garcia, "On the Suppression and Distortion of Non-Equilibrium Fluctuations by Transpiration", Physics of Fluids, August 10, 2019,

A. Donev, A. J. Nonaka, C. Kim, A. L. Garcia, J. B. Bell, "Fluctuating hydrodynamics of electrolytes at electroneutral scales", August 10, 2019,

N. T. Wimer, M. S. Day, C. Lapointe, A. S. Makowiecki, J. F. Glusman, J. W. Daily, G. B. Rieker, P. E. Hamlington, "High-resolution numerical simulations of a large-scale helium plume using adaptive mesh refinement", August 10, 2019,

M. T. Henry de Frahan, S. Yellapantula, R. King, M. S. Day, R. W. Grout, "Deep learning for presumed probability density function models", August 10, 2019,

D. Dasgupta, W. Sun, M. Day, A. Aspden, T. Lieuwen, "Analysis of chemical pathways for n-dodecane/air turbulent premixed flames", August 10, 2019,

M. Zingale, K. Eiden, Y. Cavecchi, A. Harpole, J. B. Bell, M. Chang, I. Hawke, M. P. Katz, C.M. Malone, A. J. Nonaka, D. E. Willcox, W. Zhang, "Toward resolved simulations of burning fronts in thermonuclear X-ray bursts", Journal of Physics: Conference Series, 2019, 1225,

A. J. Aspden, M. S. Day, J. B. Bell, "Towards the Distributed Burning Regime in Turbulent Premixed Flames", Journal of Fluid Mechanics, 2019, 871:1-21,

J. Bell, M. Day, J. Goodman, R. Grout, M. Morzfeld, "A Bayesian approach to calibrating hydrogen flame kinetics using many experiments and parameters", Combustion and Flame, 2019,

Mauro Del Ben, Osni Marques, Andrew Canning, "Improved Unconstrained Energy Functional Method for Eigensolvers in Electronic Structure Calculations", Proceedings of the 48th International Conference on Parallel Processing, ACM, 2019, 73, doi: 10.1145/3337821.3337914

Patricia Gonzalez-Guerrero, Mircea R Stan, "Asynchronous Stream Computing for Low Power IoT", International Midwest Symposium on Circuits and Systems (MWSCAS), Dallas, TX, USA, IEEE, August 4, 2019, doi: 10.1109/MWSCAS.2019.8885388

Asynchronous circuits have many advantages over their synchronous counterparts in terms of robustness to parameter variations, wide supply voltage ranges, and potentially low power by not needing a clock, yet their promise has not been translated yet into commercial success due to several issues related to design methodologies and the need for handshake signals. Stochastic computing is another processing paradigm that has shown promises of low power and extremely compact circuits but has yet to become a commercial success mainly because of the need for a fast clock to generate the random streams. The Asynchronous Stream Processing circuits described in this paper combine the best features of asynchronous circuits (lack of clock, robustness) with the best features of stochastic computing (processing on streams) to enable extremely compact and low power IoT sensing nodes that can finally fulfill the promise of smart dust, another concept that was ahead of its time and yet to achieve commercial success.

Ciaran Roberts, Anna Scaglione, Mahdi Jamei, Reinhard Gentz, Sean Peisert, Emma M. Stewart, Chuck McParland, Alex McEachern, Daniel Arnold, "Learning Behavior of Distribution System Discrete Control Devices for Cyber-Physical Security", IEEE Transaction on Smart Grid, August 1, 2019, 11(1):749-761, doi: 0.1109/TSG.2019.2936016

B Mohammed, N Krishnaswamy, M Kiran, "Multivariate Time-Series Prediction for Traffic in Large WAN Topology", ACM/IEEE Symposium on Architectures for Networking and Communications, August 1, 2019, doi: 10.1109/ANCS.2019.8901870

Andrew Adams, Kay Avila, Jim Basney, Dana Brunson, Robert Cowles, Jeannette Dopheide, Terry Fleury, Elisa Heymann, Florence Hudson, Craig Jackson, Ryan Kiser, Mark Krenz, Jim Marsteller, Barton P. Miller, Sean Peisert, Scott Russell, Susan Sons, Von Welch, John Zage, "Trusted CI Experiences in Cybersecurity and Service to Open Science", Proceedings of the Conference on Practice and Experience in Advanced Research Computing (PEARC), ACM, July 2019, doi: 10.1145/3332186.3340601

Peiyun Li, Sergii Gridin, K. Burak Ucer, Richard T. Williams, Mauro Del Ben, Andrew Canning, Federico Moretti, Edith Bourret, "Picosecond Absorption Spectroscopy of Excited States in BaBrCl with and without Eu Dopant and Au Codopant", Physical Review Applied, 2019, 12 (1):014035, doi: 10.1103/PhysRevApplied.12.014035

Nan Ding, Samuel Williams, Sherry Li, Yang Liu, "Leveraging One-Sided Communication for Sparse Triangular Solvers", SciDAC19, July 18, 2019,

Samuel Williams, Charlene Yang, Khaled Ibrahim, Thorsten Kurth, Nan Ding, Jack Deslippe, Leonid Oliker, "Performance Analysis using the Roofline Model", SciDAC PI Meeting, July 2019,

Hannah E. Ross, Keri L. Dixon, Raghunath Ghara, Ilian T. Iliev, Garrelt Mellema,, "Evaluating the QSO contribution to the 21-cm signal from the Cosmic Dawn", Monthly Notices of the Royal Astronomical Society, July 2019, 487:1101-1119, doi: 10.1093/mnras/stz1220

M. Zingale, A. S. Almgren, M. Barrios Sazo, J. B. Bell, K. Eiden, A. Harpole, M. P. Katz, A. J. Nonaka, D. E. Willcox, and W. Zhang, "The Castro AMR Simulation Code: Current and Future Developments", Proceedings of Astronum 2019, July 1, 2019,

J. Choi, A. Sim, Data reduction methods, systems and devices, U.S. Patent No. 10,366,078, 2019,

U.S. Patent No. 10,366,078, “DATA REDUCTION METHODS, SYSTEMS, AND DEVICES”, LBNL IB2013-133.

A. Harpole, D. Fan, M. P. Katz, A. J. Nonaka, D. E. Willcox, and M. Zingale, "Modelling low Mach number stellar hydrodynamics with MAESTROeX", Proceedings of Astronum 2019, July 1, 2019,

J. Onorbe, F. B. Davies, Z. Lukić, J. F. Hennawi, D. Sorini, "Inhomogeneous Reionization Models in Cosmological Hydrodynamical Simulations", Monthly Notices of Royal Astronomical Society, 2019, 486:4075, doi: 10.1093/mnras/stz984

Hengjie Wang, Aparna Chandramowlishwaran, "Multi-criteria partitioning of multi-block structured grids", Proceedings of the ACM International Conference on Supercomputing, 2019, 261--271,

I. Srivastava, B. L. Peters, J. M. D. Lane, H. Fan, K. M. Salerno, G. S. Grest, "Mechanics of Gold Nanoparticle Superlattices at High Hydrostatic Pressures", Journal of Physical Chemistry C, June 20, 2019, 123:17530, doi: 10.1021/acs.jpcc.9b02438

B Mohammed, IU Awan, H Ugail, and Y Mohammad., "Failure Prediction using Machine Learning in a Virtualized HPC System and Application", Cluster Computing: The Journal of Networks, Software Tools and Applications, June 3, 2019, 471–485, doi: 10.1007/s10586-019-02917-1

Vikram Khaire, Michael Walther, Joseph F. Hennawi, Jose Oñorbe, Zarija Lukić, Xavier J. Prochaska, Todd M. Tripp, Joseph N. Burchett, Christian Rodriguez, "The power spectrum of the Lyman-α Forest at z < 0.5", Monthly Notices of the Royal Astronomical Society, 2019, 486:769, doi: 10.1093/mnras/stz344

John Bachan, Scott B. Baden, Steven Hofmeyr, Mathias Jacquelin, Amir Kamil, Dan Bonachea, Paul H. Hargrove, Hadia Ahmed, "UPC++: A High-Performance Communication Framework for Asynchronous Computation", 33rd IEEE International Parallel & Distributed Processing Symposium (IPDPS'19), Rio de Janeiro, Brazil, IEEE, May 2019, doi: 10.25344/S4V88H

UPC++ is a C++ library that supports high-performance computation via an asynchronous communication framework. This paper describes a new incarnation that differs substantially from its predecessor, and we discuss the reasons for our design decisions. We present new design features, including future-based asynchrony management, distributed objects, and generalized Remote Procedure Call (RPC).
We show microbenchmark performance results demonstrating that one-sided Remote Memory Access (RMA) in UPC++ is competitive with MPI-3 RMA; on a Cray XC40 UPC++ delivers up to a 25% improvement in the latency of blocking RMA put, and up to a 33% bandwidth improvement in an RMA throughput test. We showcase the benefits of UPC++ with irregular applications through a pair of application motifs, a distributed hash table and a sparse solver component. Our distributed hash table in UPC++ delivers near-linear weak scaling up to 34816 cores of a Cray XC40. Our UPC++ implementation of the sparse solver component shows robust strong scaling up to 2048 cores, where it outperforms variants communicating using MPI by up to 3.1x.
UPC++ encourages the use of aggressive asynchrony in low-overhead RMA and RPC, improving programmer productivity and delivering high performance in irregular applications.

Elliott Binder, Tze Meng Low, Doru Thom Popovici, "Portable GPU Framework for SNP Comparisons", HiCOMB 2019, 2019,

Revathi Jambunathan, Deborah Levin, "Kinetic, three-dimensional, PIC-DSMC simulations of ion thruster plumes and the backflow region, Part 1: A colocated ion-electron source", (under review), May 20, 2019,

S. Kim, A. Sim, K. Wu, S. Byna, T. Wang, Y. Son, H. Eom, "DCA-IO: A Dynamic I/O Control Scheme for Parallel and Distributed File System", 19th Annual IEEE/ACM International Symposium in Cluster, Cloud, and Grid Computing (CCGrid 2019), 2019, doi: 10.1109/CCGRID.2019.00049

Teng Wang, Suren Byna, Glenn Lockwood, Philip Carns, Shane Snyder, Sunggon Kim, Nicholas Wright, "A Zoom-in Analysis of I/O Logs to Detect Root Causes of I/O Performance Bottlenecks", IEEE/ACM CCGrid 2019, May 14, 2019,

Weiqun Zhang, Ann Almgren, Vince Beckner, John Bell, Johannes Blashke, Cy Chan, Marcus Day, Brian Friesen, Kevin Gott, Daniel Graves, Max P. Katz, Andrew Myers, Tan Nguyen, Andrew Nonaka, Michele Rosso, Samuel Williams, Michael Zingale, "AMReX: a framework for block-structured adaptive mesh refinement", Journal of Open Source Software, May 2019, doi: 10.21105/joss.01370

Tonglin Li, Quincey Koziol, Houjun Tang, Jialin Liu, Suren Byna, "I/O Performance Analysis of Science Applications Using HDF5 File-level Provenance", Cray User Group (CUG) 2019, May 10, 2019,

T. Bowen, E. Zhivun, A. Wickenbrock, V. Dumont, S. D. Bale, C. Pankow, G. Dobler, J. S. Wurtele, D. Budker, "A Network of Magnetometers for Multi-Scale Urban Science and Informatics", Geosci. Instrum. Method. Data Syst., Volume 8, Issue 1, Pages 129-138, May 8, 2019, doi: 10.5194/gi-8-129-2019

Charlene Yang, Thorsten Kurth, Samuel Williams, "Hierarchical Roofline Analysis for GPUs: Accelerating Performance Optimization for the NERSC-9 Perlmutter System", Cray User Group (CUG), May 2019,

Jingqing Mu, Jerome Soumagne, Suren Byna, Quincey Koziol, Houjun Tang, Richard Warren, "Interfacing HDF5 with A Scalable Object-centric Storage System on Hierarchical Storage", Cray User Group (CUG) 2019, May 7, 2019,

Wenjing Ma, Yulong Ao, Chao Yang, Samuel Williams, "Solving a trillion unknowns per second with HPGMG on Sunway TaihuLight", Cluster Computing, May 2019, doi: 10.1007/s10586-019-02938-w

M. Mustafa, D. Bard, W. Bhimji, Z. Lukić, R. Al-Rfou, J. Kratochvil, "CosmoGAN: creating high-fidelity weak lensing convergence maps using Generative Adversarial Networks", Computational Astrophysics and Cosmology, 2019, 6:1, doi: 10.1186/s40668-019-0029-9

Anastasiia Butko, George Michelogiannakis, David Donofrio, John Shalf, "Extending classical processors to support future large scale quantum accelerators", Proceedings of the 16th ACM International Conference on Computing Frontiers Pages, April 2019,

Anastasiia Butko, George Michelogiannakis, David Donofrio, John Shalf, "TIGER: topology-aware task assignment approach using ising machines", Proceedings of the 16th ACM International Conference on Computing Frontiers, April 2019,

Boris Lo, Phillip Colella, "An Adaptive Local Discrete Convolution Method for the Numerical Solution of Maxwell's Equations", Communications in Applied Mathematics and Computational Science, April 26, 2019, 14:105-119, doi: DOI: 10.2140/camcos.2019.14.105

Doru Thom Popovici, Martin D. Schatz, Franz Franchetti, Tze Meng Low, "A Flexible Framework for Parallel Multi-Dimensional DFTs", April 23, 2019,

D.L. Brown, S. Crivelli, M. A. Leung, "Sustainable Research Pathways: Building Connections across Communities to Diversify the National Laboratory Workforce", CoNECD 2019 - Collaborative Network for Engineering and Computing Diversity., April 14, 2019,

G Tzimpragos, A Madhavan, D Vasudevan, D Strukov and T Sherwood, "Boosted Race Trees for Low Energy Classification - Best Paper Award", ("Best Paper Award"), ASPLOS 2019, April 2019, doi: 10.1145/3297858.3304036

Francois P. Hamon, Martin Schreiber, Michael L. Minion, "Parallel-in-Time Multi-Level Integration of the Shallow-Water Equations on the Rotating Sphere", April 12, 2019,

Submitted to Journal of Computational Physics

D.F. Martin, H.S. Johansen, P.O. Schwartz, E.G. Ng, "Improved Discretization of Grounding Lines and Calving Fronts using an Embedded-Boundary Approach in BISICLES", European Geosciences Union General Assembly, April 10, 2019,

B. Peng, R. Van Beeumen, D.B. Williams-Young, K. Kowalski, C. Yang, "Approximate Green’s function coupled cluster method employing effective dimension reduction", Journal of Chemical Theory and Computation, 2019, 15:3185-3196, doi: 10.1021/acs.jctc.9b00172

J. Kim, A. Sim, B. Tierney, S. Suh, I. Kim, "Multivariate Network Traffic Analysis using Clustered Patterns", Journal of Computing, April 2019, 101(4):339-361, doi: 10.1007/s00607-018-0619-4

P. Benner, V. Khoromskaia, B. N. Khoromskij and C. Yang, "Computing the density of states for optical spectra of molecules by low-rank and QTT tensor approximation", Journal of Computational Physics, April 1, 2019, 382:221-239, doi: https://doi.org/10.1016/j.jcp.2019.01.011

J. Kim, A. Sim, "A new approach to multivariate network traffic analysis", Journal of Computer Science and Technology, 2019, 34(2):388–402, doi: 10.1007/s11390-019-1915-y

Sean Peisert, Brooks Evans, Michael Liang, Barclay Osborn, David Rusting, David Thurston, Security Without Moats and Walls: Zero-Trust Networking for Enhancing Security in R&E Environments, CENIC Annual Conference, March 19, 2019,

Charlene Yang, Samuel Williams, Performance Analysis of GPU-Accelerated Applications using the Roofline Model, GPU Technology Conference (GTC), March 2019,

Zhe Bai, Eurika Kaiser, Joshua L. Proctor, J. Nathan Kutz, Steven L. Brunton, "Dynamic mode decomposition for compressive system identification", AIAA Journal, 2019, 58:2, doi: 10.2514/1.J057870

Drew Paine, Lavanya Ramakrishnan, "Surfacing Data Change in Scientific Work", iConference 2019, Springer Verlag, March 19, 2019, 15-26, doi: 10.1007/978-3-030-15742-5_2

Mauro Del Ben, H Felipe, Gabriel Antonius, Tonatiuh Rangel, Steven G Louie, Jack Deslippe, Andrew Canning, "Static Subspace Approximation for the Evaluation of G0W0 Quasiparticle Energies within a Sum-Over-Bands Approach", Physical Review B, 2019, 99 (12):125128, doi: 10.1103/PhysRevB.99.125128

John Bachan, Scott Baden, Dan Bonachea, Paul Hargrove, Steven Hofmeyr, Mathias Jacquelin, Amir Kamil, Brian van Straalen, "UPC++ Programmer's Guide, v1.0-2019.3.0", Lawrence Berkeley National Laboratory Tech Report, March 2019, LBNL 2001191, doi: 10.25344/S4F301

UPC++ is a C++11 library that provides Partitioned Global Address Space (PGAS) programming. It is designed for writing parallel programs that run efficiently and scale well on distributed-memory parallel computers. The PGAS model is single program, multiple-data (SPMD), with each separate constituent process having access to local memory as it would in C++. However, PGAS also provides access to a global address space, which is allocated in shared segments that are distributed over the processes. UPC++ provides numerous methods for accessing and using global memory. In UPC++, all operations that access remote memory are explicit, which encourages programmers to be aware of the cost of communication and data movement. Moreover, all remote-memory access operations are by default asynchronous, to enable programmers to write code that scales well even on hundreds of thousands of cores.

John Bachan, Scott Baden, Dan Bonachea, Paul Hargrove, Steven Hofmeyr, Mathias Jacquelin, Amir Kamil, Brian van Straalen, "UPC++ Specification v1.0, Draft 10", Lawrence Berkeley National Laboratory Tech Report, March 15, 2019, LBNL 2001192, doi: 10.25344/S4JS30

UPC++ is a C++11 library providing classes and functions that support Partitioned Global Address Space (PGAS) programming. We are revising the library under the auspices of the DOE’s Exascale Computing Project, to meet the needs of applications requiring PGAS support. UPC++ is intended for implementing elaborate distributed data structures where communication is irregular or fine-grained. The UPC++ interfaces for moving non-contiguous data and handling memories with different optimal access methods are composable and similar to those used in conventional C++. The UPC++ programmer can expect communication to run at close to hardware speeds. The key facilities in UPC++ are global pointers, that enable the programmer to express ownership information for improving locality, one-sided communication, both put/get and RPC, futures and continuations. Futures capture data readiness state, which is useful in making scheduling decisions, and continuations provide for completion handling via callbacks. Together, these enable the programmer to chain together a DAG of operations to execute asynchronously as high-latency dependencies become satisfied.

Babak Behzad, Suren Byna, Prabhat, and Marc Snir, "Optimizing I/O Performance of HPC Applications with Autotuning", ACM Transactions on Parallel Computing (TOPC), February 28, 2019,

Alexandra Ballow, Alina Lazar, Alex Sim, Kesheng Wu, "Joint Sequence Analysis Challenges: How to Handle Missing Values and Mixed Variable Types", SIAM Conference on Computational Science and Engineering (CSE19), 2019,

Tyler Leibengood, Alina Lazar, Alex Sim, Kesheng Wu, "Network Traffic Performance Prediction with Multivariate Clusters in Time Windows", SIAM Conference on Computational Science and Engineering (CSE19), 2019,

Daniel Martin, Modeling Antarctic Ice Sheet Dynamics using Adaptive Mesh Refinement, 2019 SIAM Conference on Computational Science and Engineering, February 26, 2019,

Patricia Gonzalez-Guerrero, Xinfei Guo, Mircea R Stan, "ASC-FFT: Area-efficient low-latency FFT design based on asynchronous stochastic computing", 10th Latin American Symposium on Circuits & Systems (LASCAS), Armenia, Colombia, IEEE, February 24, 2019, doi: 10.1109/LASCAS.2019.8667599

Asynchronous Stochastic Computing (ASC) is a new paradigm that addresses Synchronous Stochastic Computing (SSC) drawbacks, expensive stochastic number generation (SNG) and long latency, by using continuous time streams (CTS). To go beyond the basic operations of addition and multiplication in ASC we need to incorporate a memory element. Although for SSC the natural memory element is a clocked-flip-flop, using the same approach with no synchronized data leads to unacceptable large error. In this paper, we propose to use a capacitor embedded in a feedback loop as the ASC memory element. Based on this idea, we design a low-error asynchronous adder that stores the carry information in the capacitor. Our adder enables the implementation of more complex computation logic. As an example, we implement an asynchronous stochastic Fast Fourier Transform (ASC-FFT) using a FinFET1X 1 technology. The proposed adder requires 76%-24% less hardware cost compared against conventional and SSC adders respectively. Besides, the ASC-FFT shows 3X less latency when compared with SSC-FFT approaches and significant improvements in latency and area over conventional FFT architectures with no degradation of the computation accuracy measured by the FFT Signal to Noise Ratio (SNR).

Samuel Williams, Performance Modeling and Analysis, CS267 Lecture, University of California at Berkeley, February 14, 2019,

Sean Peisert, Experiences in Building a Mission-Driven Security R&D Program for Science and Energy, Computer Science Colloquium Seminar, University of California, Davis, February 7, 2019,

Sean Peisert, Daniel Arnold, Using Physics to Improve Cybersecurity for the Distribution Grid and Distributed Energy Resources, Naval Postgraduate School, February 5, 2019,

George Michelogiannakis, Jeremiah Wilke, Min Yee Teh, Madeleine Glick, John Shalf, Keren Bergman, "Challenges and opportunities in system-level evaluation of photonics", Proceedings Volume 10946, Metro and Data Center Optical Networks and Short-Reach Links II, February 2019, doi: https://doi.org/10.1117/12.2510443

Aleksandar Donev, Alejandro L. Garcia, Jean-Philippe Péraud, Andrew J. Nonaka, John B. Bell, "Fluctuating Hydrodynamics and Debye-Hückel-Onsager Theory for Electrolytes", Current Opinion in Electrochemistry, 2019, 13:1 - 10, doi: https://doi.org/10.1016/j.coelec.2018.09.004

M Kiran, A Chhabra, "Understanding flows in high-speed scientific networks: A Netflow data study", Future Generation Computer Systems, February 1, 2019, 94:72-79,

Mauro Del Ben, H Felipe, Andrew Canning, Nathan Wichmann, Karthik Raman, Ruchira Sasanka, Chao Yang, Steven G Louie, Jack Deslippe, "Large-Scale GW Calculations on Pre-Exascale HPC Systems", Computer Physics Communications, 2019, 235:187-195, doi: 10.1016/j.cpc.2018.09.003

M. Walther, J. Onorbe, J. F. Hennawi, Z. Lukić, "New Constraints on IGM Thermal Evolution from the Ly-alpha Forest Power Spectrum", The Astrophysical Journal, 2019, 872:13, doi: 10.3847/1538-4357/aafad1

I. Srivastava, L. E. Silbert, G. S. Grest, J. B. Lechman, "Flow-Arrest Transitions in Frictional Granular Matter", Physical Review Letters, January 30, 2019, 122:048003, doi: 10.1103/PhysRevLett.122.048003

Yu-Hang Tang, Wibe A. de Jong, "Prediction of atomization energy using graph kernel and active learning", The Journal of Chemical Physics, January 25, 2019, 150:044107, doi: 10.1063/1.5078640

Sean Peisert, Building a Mission-Driven, Applied Cybersecurity R&D Program from Scratch, VISA Research, January 23, 2019,

Stefano Marchesini, Anne Sakdinawat, "Shaping Coherent X-rays with Binary Optics", Optics Express Vol. 27, Issue 2, pp. 907-917 (2019), January 21, 2019,

Sebastian Götschel , Michael Minion, "An Efficient Parallel-in-Time Method for Optimization with Parabolic PDEs", SIAM Journal on Scientific Computing, January 21, 2019,

In submission

Oliver Rübel, Andrew Tritt, Benjamin Dichter, Thomas Braun, Nicholas Cain, Nathan Clack, Thomas J. Davidson, Max Dougherty, Jean-Christophe Fillion-Robin, Nile Graddis, Michael Grauer, Justin T. Kiggins, Lawrence Niu, Doruk Ozturk, William Schroeder, Ivan Soltesz, Friedrich T. Sommer, Karel Svoboda, Lydia Ng, Loren M. Frank, Kristofer Bouchard, "NWB:N 2.0: An Accessible Data Standard for Neurophysiology", bioRxiv, January 17, 2019, doi: https://doi.org/10.1101/523035

Samuel Williams, Introduction to the Roofline Model, Roofline Tutorial, ECP Annual Meeting, January 2019,

George Michelogiannakis, Computation and Communication in a Post Moore’s Law Era, Post Exascale workshop part of HiPEAC conference, January 2019,

Samuel Williams, Roofline on CPU-based Systems, Roofline Tutorial, ECP Annual Meeting, January 2019,

Jack Deslippe, Optimization Use Cases with the Roofline Model, Roofline Tutorial, ECP Annual Meeting, January 2019,

Charlene Yang, Performance Analysis with Roofline on GPUs, Roofline Tutorial, ECP Annual Meeting, January 2019,

Scott B. Baden, Paul H. Hargrove, Hadia Ahmed, John Bachan, Dan Bonachea, Steve Hofmeyr, Mathias Jacquelin, Amir Kamil, Brian van Straalen, "Pagoda: Lightweight Communications and Global Address Space Support for Exascale Applications - UPC++ (ECP'19)", Poster at Exascale Computing Project (ECP) Annual Meeting 2019, January 2019,

Scott B. Baden, Paul H. Hargrove, Dan Bonachea, "Pagoda: Lightweight Communications and Global Address Space Support for Exascale Applications - GASNet-EX (ECP'19)", Poster at Exascale Computing Project (ECP) Annual Meeting 2019, January 2019,

Daniel F. Martin, Stephen L. Cornford, Antony J. Payne, "Millennial‐scale Vulnerability of the Antarctic Ice Sheet to Regional Ice Shelf Collapse", Geophysical Research Letters, January 9, 2019, doi: 10.1029/2018gl081229

Abstract: 

The Antarctic Ice Sheet (AIS) remains the largest uncertainty in projections of future sea level rise. A likely climate‐driven vulnerability of the AIS is thinning of floating ice shelves resulting from surface‐melt‐driven hydrofracture or incursion of relatively warm water into subshelf ocean cavities. The resulting melting, weakening, and potential ice‐shelf collapse reduces shelf buttressing effects. Upstream ice flow accelerates, causing thinning, grounding‐line retreat, and potential ice sheet collapse. While high‐resolution projections have been performed for localized Antarctic regions, full‐continent simulations have typically been limited to low‐resolution models. Here we quantify the vulnerability of the entire present‐day AIS to regional ice‐shelf collapse on millennial timescales treating relevant ice flow dynamics at the necessary ∼1km resolution. Collapse of any of the ice shelves dynamically connected to the West Antarctic Ice Sheet (WAIS) is sufficient to trigger ice sheet collapse in marine‐grounded portions of the WAIS. Vulnerability elsewhere appears limited to localized responses.

Plain Language Summary:

The biggest uncertainty in near‐future sea level rise (SLR) comes from the Antarctic Ice Sheet. Antarctic ice flows in relatively fast‐moving ice streams. At the ocean, ice flows into enormous floating ice shelves which push back on their feeder ice streams, buttressing them and slowing their flow. Melting and loss of ice shelves due to climate changes can result in faster‐flowing, thinning and retreating ice leading to accelerated rates of global sea level rise.To learn where Antarctica is vulnerable to ice‐shelf loss, we divided it into 14 sectors, applied extreme melting to each sector's floating ice shelves in turn, then ran our ice flow model 1000 years into the future for each case. We found three levels of vulnerability. The greatest vulnerability came from attacking any of the three ice shelves connected to West Antarctica, where much of the ice sits on bedrock lying below sea level. Those dramatic responses contributed around 2m of sea level rise. The second level came from four other sectors, each with a contribution between 0.5‐1m. The remaining sectors produced little to no contribution. We examined combinations of sectors, determining that sectors behave independently of each other for at least a century.

M. Emmett, E. Motheau, W. Zhang, M. Minion, J. B. Bell, "A Fourth-Order Adaptive Mesh Refinement Algorithm for the Multicomponent, Reacting Compressible Navier-Stokes Equations", Combustion Theory and Modeling, 2019,

Mariam Kiran, Anshuman Chhabra, "Understanding flows in high-speed scientific networks: A Netflow data study", Future Generation Computer Science, 2019,

BA Brock, Y Chen, J Yan, J Owens, A Buluç, K Yelick, "RDMA vs. RPC for implementing distributed data structures", 2019 IEEE/ACM 9th Workshop on Irregular Applications: Architectures and Algorithms, IA3 2019, January 1, 2019, 17--22, doi: 10.1109/IA349570.2019.00009

Distributed data structures are key to implementing scalable applications for scientific simulations and data analysis. In this paper we look at two implementation styles for distributed data structures: remote direct memory access (RDMA) and remote procedure call (RPC). We focus on operations that require individual accesses to remote portions of a distributed data structure, e.g., accessing a hash table bucket or distributed queue, rather than global operations in which all processors collectively exchange information. We look at the trade-offs between the two styles through microbenchmarks and a performance model that approximates the cost of each. The RDMA operations have direct hardware support in the network and therefore lower latency and overhead, while the RPC operations are more expressive but higher cost and can suffer from lack of attentiveness from the remote side. We also run experiments to compare the real-world performance of RDMA- and RPC-based data structure operations with the predicted performance to evaluate the accuracy of our model, and show that while the model does not always precisely predict running time, it allows us to choose the best implementation in the examples shown. We believe this analysis will assist developers in designing data structures that will perform well on current network architectures, as well as network architects in providing better support for this class of distributed data structures.

Catherine A Watkinson, Sambit K. Giri, Hannah E. Ross, Keri L. Dixon, Ilian T. Iliev, Garrelt Mellema, Jonathan R. Pritchard, "The 21-cm bispectrum as a probe of non-Gaussianities due to X-ray heating", Monthly Notices of the Royal Astronomical Society, January 2019, 482:2653-2669, doi: 10.1093/mnras/sty2740

Bin Dong, Kesheng Wu, Suren Byna, Houjun Tang, "SLOPE: Structural Locality-Aware Programming Model for Composing Array Data Analysis", International Conference on High Performance Computing, January 1, 2019, 61--80,

Alina Lazar, Ling Jin, C Anna Spurlock, Kesheng Wu, Alex Sim, Annika Todd, "Evaluating the effects of missing values and mixed data types on social sequence clustering using t-SNE visualization", Journal of Data and Information Quality (JDIQ), 2019, 11:1--22,

Kesheng Wu, Florin Rusu, Special issue on scientific and statistical data management, Distributed and Parallel Databases, Pages: 1--3 2019,

Sunggon Kim, Alex Sim, Kesheng Wu, Suren Byna, Teng Wang, Yongseok Son, Hyeonsang Eom, DCA-IO: A Dynamic I/O Control Scheme for Parallel and Distributed File Systems., CCGRID, Pages: 351--360 2019,

Payton Linton, William Melodia, Alina Lazar, Deborah Agarwal, Ludovico Bianchi, Devarshi Ghoshal, Gilberto Pastorello, Lavanya Ramakrishnan, Kesheng Wu, Understanding Data Similarity in Large-Scale Scientific Datasets, 2019 IEEE International Conference on Big Data (Big Data), Pages: 4525--4531 2019,

Sambit Shukla, Dipak Ghosal, Kesheng Wu, Alex Sim, Matthew Farrens, "Co-optimizing Latency and Energy for IoT services using HMP servers in Fog Clusters", 2019 Fourth International Conference on Fog and Mobile Edge Computing (FMEC), 2019, 121--128,

Alina Lazar, Alexandra Ballow, Ling Jin, C Anna Spurlock, Alexander Sim, Kesheng Wu, Machine Learning for Prediction of Mid to Long Term Habitual Transportation Mode Use, 2019 IEEE International Conference on Big Data (Big Data), Pages: 4520--4524 2019,

Francois P. Hamon, Martin Schreiber, Michael L. Minion, "Multi-Level Spectral Deferred Corrections Scheme for the Shallow Water Equations on the Rotating Sphere", Journal of Computational Physics, January 1, 2019, 376:435-454,

O Karslıoğlu, M Gehlmann, J Müller, S Nemšák, JA Sethian, A Kaduwela, H Bluhm, C Fadley, "An Efficient Algorithm for Automatic Structure Optimization in X-ray Standing-Wave Experiments", Journal of Electron Spectroscopy and Related Phenomena, January 1, 2019,

Hanul Sung, Jiwoo Bang, Alexander Sim, Kesheng Wu, Hyeonsang Eom, "Understanding Parallel I/O Performance Trends Under Various HPC Configurations", Proceedings of the ACM Workshop on Systems and Network Telemetry and Analytics, 2019, 29--36,

Mengtian Jin, Youkow Homma, Alex Sim, Wilko Kroeger, Kesheng Wu, "Performance prediction for data transfers in LCLS workflow", Proceedings of the ACM Workshop on Systems and Network Telemetry and Analytics, 2019, 37--44,

Olivia Del Guercio, Rafael Orozco, Alex Sim, Kesheng Wu, "Similarity-based Compression with Multidimensional Pattern Matching", Proceedings of the ACM Workshop on Systems and Network Telemetry and Analytics, 2019, 19--24,

Astha Syal, Alina Lazar, Jinoh Kim, Alex Sim, Kesheng Wu, "Automatic detection of network traffic anomalies and changes", Proceedings of the ACM Workshop on Systems and Network Telemetry and Analytics, 2019, 3--10,

D Vasudevan, G Michclogiannakis, D Donofrio, J Shalf, "PARADISE - Post-Moore Architecture and Accelerator Design Space Exploration Using Device Level Simulation and Experiments", 2019 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS), IEEE, January 2019, doi: 10.1109/ispass.2019.00022

G Rocha, AJ Banday, RB Barreiro, A Challinor, KM Górski, B Hensley, T Jaffe, J Jewell, B Keating, A Kogut, C Lawrence, G Panopoulou, B Partridge, T Pearson, J Silk, P Steinhardt, I Whehus, J Bock, B Crill, J Delabrouille, O Doré, R Fernandez-Cobos, A Ijjas, R Keskitalo, A Kritsuk, A Mangilli, L Moncelsi, S Myers, B Steinbach, M Tristram, Astro2020 APC White Paper: The need for better tools to design future CMB experiments, 2019,

Bin Dong, Patrick Kilian, Xiaocan Li, Fan Guo, Suren Byna, Kesheng Wu, "Terabyte-scale Particle Data Analysis: An ArrayUDF Case Study", Proceedings of the 31st International Conference on Scientific and Statistical Database Management, January 1, 2019, 202--205,

K Abazajian, G Addison, P Adshead, Z Ahmed, SW Allen, D Alonso, M Alvarez, MA Amin, A Anderson, KS Arnold, C Baccigalupi, K Bailey, D Barkats, D Barron, PS Barry, JG Bartlett, RB Thakur, N Battaglia, E Baxter, R Bean, C Bebek, AN Bender, BA Benson, E Berger, S Bhimani, CA Bischoff, L Bleem, JJ Bock, S Bocquet, K Boddy, M Bonato, JR Bond, J Borrill, FR Bouchet, ML Brown, S Bryan, B Burkhart, V Buza, K Byrum, E Calabrese, V Calafut, R Caldwell, JE Carlstrom, J Carron, T Cecil, A Challinor, CL Chang, Y Chinone, H-MS Cho, A Cooray, TM Crawford, A Crites, A Cukierman, F-Y Cyr-Racine, T de Haan, G de Zotti, J Delabrouille, M Demarteau, M Devlin, E Di Valentino, M Dobbs, S Duff, A Duivenvoorden, C Dvorkin, W Edwards, J Eimer, J Errard, T Essinger-Hileman, G Fabbian, C Feng, S Ferraro, JP Filippini, R Flauger, B Flaugher, AA Fraisse, A Frolov, N Galitzki, S Galli, K Ganga, M Gerbino, M Gilchriese, V Gluscevic, D Green, D Grin, E Grohs, R Gualtieri, V Guarino, JE Gudmundsson, S Habib, G Haller, M Halpern, NW Halverson, S Hanany, K Harrington, M Hasegawa, M Hasselfield, M Hazumi, K Heitmann, S Henderson, JW Henning, JC Hill, R Hlozek, G Holder, W Holzapfel, J Hubmayr, KM Huffenberger, M Huffer, H Hui, K Irwin, BR Johnson, D Johnstone, WC Jones, K Karkare, N Katayama, J Kerby, S Kernovsky, R Keskitalo, T Kisner, L Knox, A Kosowsky, J Kovac, ED Kovetz, S Kuhlmann, C-L Kuo, N Kurita, A Kusaka, A Lahteenmaki, CR Lawrence, AT Lee, A Lewis, D Li, E Linder, M Loverde, A Lowitz, MS Madhavacheril, A Mantz, F Matsuda, P Mauskopf, J McMahon, PD Meerburg, J-B Melin, J Meyers, M Millea, J Mohr, L Moncelsi, T Mroczkowski, S Mukherjee, M Münchmeyer, D Nagai, J Nagy, T Namikawa, F Nati, T Natoli, M Negrello, L Newburgh, MD Niemack, H Nishino, M Nordby, V Novosad, P O Connor, G Obied, S Padin, S Pandey, B Partridge, E Pierpaoli, L Pogosian, C Pryke, G Puglisi, B Racine, S Raghunathan, A Rahlin, S Rajagopalan, M Raveri, M Reichanadter, CL Reichardt, M Remazeilles, G Rocha, NA Roe, A Roy, J Ruhl, M Salatino, B Saliwanchik, E Schaan, A Schillaci, MM Schmittfull, D Scott, N Sehgal, S Shandera, C Sheehy, BD Sherwin, E Shirokoff, SM Simon, A Slosar, R Somerville, ST Staggs, A Stark, R Stompor, KT Story, C Stoughton, A Suzuki, O Tajima, GP Teply, K Thompson, P Timbie, M Tomasi, JI Treu, M Tristram, G Tucker, C Umiltà, A van Engelen, JD Vieira, AG Vieregg, M Vogelsberger, G Wang, S Watson, M White, N Whitehorn, EJ Wollack, WLK Wu, Z Xu, S Yasini, J Yeck, KW Yoon, E Young, A Zonca, CMB-S4 Decadal Survey APC White Paper, 2019,

M Ellis, G Guidi, A Buluç, L Oliker, K Yelick, "DiBELLA: Distributed long read to long read alignment", ACM International Conference Proceeding Series, January 1, 2019, doi: 10.1145/3337821.3337919

TSO Collaboration, MH Abitbol, S Adachi, P Ade, J Aguirre, Z Ahmed, S Aiola, A Ali, D Alonso, MA Alvarez, K Arnold, P Ashton, Z Atkins, J Austermann, H Awan, C Baccigalupi, T Baildon, AB Lizancos, D Barron, N Battaglia, R Battye, E Baxter, A Bazarko, JA Beall, R Bean, D Beck, S Beckman, B Beringue, T Bhandarkar, S Bhimani, F Bianchini, S Boada, D Boettger, B Bolliet, JR Bond, J Borrill, ML Brown, SM Bruno, S Bryan, E Calabrese, V Calafut, P Calisse, J Carron, FM Carl, J Cayuso, A Challinor, G Chesmore, Y Chinone, J Chluba, H-MS Cho, S Choi, S Clark, P Clarke, C Contaldi, G Coppi, NF Cothard, K Coughlin, W Coulton, D Crichton, KD Crowley, KT Crowley, A Cukierman, JM D Ewart, R Dünner, TD Haan, M Devlin, S Dicker, B Dober, CJ Duell, S Duff, A Duivenvoorden, J Dunkley, HE Bouhargani, J Errard, G Fabbian, S Feeney, J Fergusson, S Ferraro, P Fluxà, K Freese, JC Frisch, A Frolov, G Fuller, N Galitzki, PA Gallardo, JTG Ghersi, J Gao, E Gawiser, M Gerbino, V Gluscevic, N Goeckner-Wald, J Golec, S Gordon, M Gralla, D Green, A Grigorian, J Groh, C Groppi, Y Guan, JE Gudmundsson, M Halpern, D Han, P Hargrave, K Harrington, M Hasegawa, M Hasselfield, M Hattori, V Haynes, M Hazumi, E Healy, SW Henderson, B Hensley, C Hervias-Caimapo, CA Hill, JC Hill, G Hilton, M Hilton, AD Hincks, G Hinshaw, R Hložek, S Ho, S-PP Ho, TD Hoang, J Hoh, SC Hotinli, Z Huang, J Hubmayr, K Huffenberger, JP Hughes, A Ijjas, M Ikape, K Irwin, AH Jaffe, B Jain, O Jeong, M Johnson, D Kaneko, ED Karpel, N Katayama, B Keating, R Keskitalo, T Kisner, K Kiuchi, J Klein, K Knowles, A Kofman, B Koopman, A Kosowsky, N Krachmalnicoff, A Kusaka, P LaPlante, J Lashner, A Lee, E Lee, A Lewis, Y Li, Z Li, M Limon, E Linder, J Liu, C Lopez-Caraballo, T Louis, M Lungu, M Madhavacheril, D Mak, F Maldonado, H Mani, B Mates, F Matsuda, L Maurin, P Mauskopf, A May, N McCallum, H McCarrick, C McKenney, J McMahon, PD Meerburg, J Mertens, J Meyers, A Miller, M Mirmelstein, K Moodley, J Moore, M Munchmeyer, C Munson, M Murata, S Naess, T Namikawa, F Nati, M Navaroli, L Newburgh, HN Nguyen, A Nicola, M Niemack, H Nishino, Y Nishinomiya, J Orlowski-Scherer, L Pagano, B Partridge, F Perrotta, P Phakathi, L Piccirillo, E Pierpaoli, G Pisano, D Poletti, R Puddu, G Puglisi, C Raum, CL Reichardt, M Remazeilles, Y Rephaeli, D Riechers, F Rojas, A Rotti, A Roy, S Sadeh, Y Sakurai, M Salatino, MS Rao, L Saunders, E Schaan, M Schmittfull, N Sehgal, J Seibert, U Seljak, P Shellard, B Sherwin, M Shimon, C Sierra, J Sievers, C Sifon, P Sikhosana, M Silva-Feaver, SM Simon, A Sinclair, K Smith, W Sohn, R Sonka, D Spergel, J Spisak, ST Staggs, G Stein, JR Stevens, R Stompor, A Suzuki, O Tajima, S Takakura, G Teply, DB Thomas, B Thorne, R Thornton, H Trac, J Treu, C Tsai, C Tucker, J Ullom, S Vagnozzi, AV Engelen, JV Lanen, DDV Winkle, EM Vavagiakis, C Vergès, M Vissers, K Wagoner, S Walker, Y Wang, J Ward, B Westbrook, N Whitehorn, J Williams, J Williams, E Wollack, Z Xu, S Yasini, E Young, B Yu, C Yu, F Zago, M Zannoni, H Zhang, K Zheng, N Zhu, A Zonca, "The Simons Observatory: Astro2020 Decadal Project Whitepaper", Bull. Am. Astron. Soc., 2019, 51:147,

K Abazajian, G Addison, P Adshead, Z Ahmed, SW Allen, D Alonso, M Alvarez, A Anderson, KS Arnold, C Baccigalupi, K Bailey, D Barkats, D Barron, PS Barry, JG Bartlett, RB Thakur, N Battaglia, E Baxter, R Bean, C Bebek, AN Bender, BA Benson, E Berger, S Bhimani, CA Bischoff, L Bleem, S Bocquet, K Boddy, M Bonato, JR Bond, J Borrill, FR Bouchet, ML Brown, S Bryan, B Burkhart, V Buza, K Byrum, E Calabrese, V Calafut, R Caldwell, JE Carlstrom, J Carron, T Cecil, A Challinor, CL Chang, Y Chinone, H-MS Cho, A Cooray, TM Crawford, A Crites, A Cukierman, F-Y Cyr-Racine, T de Haan, G de Zotti, J Delabrouille, M Demarteau, M Devlin, E Di Valentino, M Dobbs, S Duff, A Duivenvoorden, C Dvorkin, W Edwards, J Eimer, J Errard, T Essinger-Hileman, G Fabbian, C Feng, S Ferraro, JP Filippini, R Flauger, B Flaugher, AA Fraisse, A Frolov, N Galitzki, S Galli, K Ganga, M Gerbino, M Gilchriese, V Gluscevic, D Green, D Grin, E Grohs, R Gualtieri, V Guarino, JE Gudmundsson, S Habib, G Haller, M Halpern, NW Halverson, S Hanany, K Harrington, M Hasegawa, M Hasselfield, M Hazumi, K Heitmann, S Henderson, JW Henning, JC Hill, R Hlozek, G Holder, W Holzapfel, J Hubmayr, KM Huffenberger, M Huffer, H Hui, K Irwin, BR Johnson, D Johnstone, WC Jones, K Karkare, N Katayama, J Kerby, S Kernovsky, R Keskitalo, T Kisner, L Knox, A Kosowsky, J Kovac, ED Kovetz, S Kuhlmann, C-L Kuo, N Kurita, A Kusaka, A Lahteenmaki, CR Lawrence, AT Lee, A Lewis, D Li, E Linder, M Loverde, A Lowitz, MS Madhavacheril, A Mantz, F Matsuda, P Mauskopf, J McMahon, M McQuinn, PD Meerburg, J-B Melin, J Meyers, M Millea, J Mohr, L Moncelsi, T Mroczkowski, S Mukherjee, M Münchmeyer, D Nagai, J Nagy, T Namikawa, F Nati, T Natoli, M Negrello, L Newburgh, MD Niemack, H Nishino, M Nordby, V Novosad, P O Connor, G Obied, S Padin, S Pandey, B Partridge, E Pierpaoli, L Pogosian, C Pryke, G Puglisi, B Racine, S Raghunathan, A Rahlin, S Rajagopalan, M Raveri, M Reichanadter, CL Reichardt, M Remazeilles, G Rocha, NA Roe, A Roy, J Ruhl, M Salatino, B Saliwanchik, E Schaan, A Schillaci, MM Schmittfull, D Scott, N Sehgal, S Shandera, C Sheehy, BD Sherwin, E Shirokoff, SM Simon, A Slosar, R Somerville, D Spergel, ST Staggs, A Stark, R Stompor, KT Story, C Stoughton, A Suzuki, O Tajima, GP Teply, K Thompson, P Timbie, M Tomasi, JI Treu, M Tristram, G Tucker, C Umiltà, A van Engelen, JD Vieira, AG Vieregg, M Vogelsberger, G Wang, S Watson, M White, N Whitehorn, EJ Wollack, WLK Wu, Z Xu, S Yasini, J Yeck, KW Yoon, E Young, A Zonca, CMB-S4 Science Case, Reference Design, and Project Plan, 2019,

M Hazumi, PAR Ade, Y Akiba, D Alonso, K Arnold, J Aumont, C Baccigalupi, D Barron, S Basak, S Beckman, J Borrill, F Boulanger, M Bucher, E Calabrese, Y Chinone, S Cho, A Cukierman, DW Curtis, T de Haan, M Dobbs, A Dominjon, T Dotani, L Duband, A Ducout, J Dunkley, JM Duval, T Elleflot, HK Eriksen, J Errard, J Fischer, T Fujino, T Funaki, U Fuskeland, K Ganga, N Goeckner-Wald, J Grain, NW Halverson, T Hamada, T Hasebe, M Hasegawa, K Hattori, M Hattori, L Hayes, N Hidehira, CA Hill, G Hilton, J Hubmayr, K Ichiki, T Iida, H Imada, M Inoue, Y Inoue, KD Irwin, H Ishino, O Jeong, H Kanai, D Kaneko, S Kashima, N Katayama, T Kawasaki, SA Kernasovskiy, R Keskitalo, A Kibayashi, Y Kida, K Kimura, T Kisner, K Kohri, E Komatsu, K Komatsu, CL Kuo, NA Kurinsky, A Kusaka, A Lazarian, AT Lee, D Li, E Linder, B Maffei, A Mangilli, M Maki, T Matsumura, S Matsuura, D Meilhan, S Mima, Y Minami, K Mitsuda, L Montier, M Nagai, T Nagasaki, R Nagata, M Nakajima, S Nakamura, T Namikawa, M Naruse, H Nishino, T Nitta, T Noguchi, H Ogawa, S Oguri, N Okada, A Okamoto, "LiteBIRD: A Satellite for the Studies of B-Mode Polarization and Inflation from Cosmic Background Radiation Detection", Journal of Low Temperature Physics, 2019, 194:443--452, doi: 10.1007/s10909-019-02150-5

P Ade, J Aguirre, Z Ahmed, S Aiola, A Ali, D Alonso, MA Alvarez, K Arnold, P Ashton, J Austermann, H Awan, C Baccigalupi, T Baildon, D Barron, N Battaglia, R Battye, E Baxter, A Bazarko, JA Beall, R Bean, D Beck, S Beckman, B Beringue, F Bianchini, S Boada, D Boettger, JR Bond, J Borrill, ML Brown, SM Bruno, S Bryan, E Calabrese, V Calafut, P Calisse, J Carron, A Challinor, G Chesmore, Y Chinone, J Chluba, HMS Cho, S Choi, G Coppi, NF Cothard, K Coughlin, D Crichton, KD Crowley, KT Crowley, A Cukierman, JM D Ewart, R Dünner, T De Haan, M Devlin, S Dicker, J Didier, M Dobbs, B Dober, CJ Duell, S Duff, A Duivenvoorden, J Dunkley, J Dusatko, J Errard, G Fabbian, S Feeney, S Ferraro, P Fluxà, K Freese, JC Frisch, A Frolov, G Fuller, B Fuzia, N Galitzki, PA Gallardo, JTG Ghersi, J Gao, E Gawiser, M Gerbino, V Gluscevic, N Goeckner-Wald, J Golec, S Gordon, M Gralla, D Green, A Grigorian, J Groh, C Groppi, Y Guan, JE Gudmundsson, D Han, P Hargrave, M Hasegawa, M Hasselfield, M Hattori, V Haynes, M Hazumi, Y He, E Healy, SW Henderson, C Hervias-Caimapo, CA Hill, The Simons Observatory: Science goals and forecasts, Journal of Cosmology and Astroparticle Physics, 2019, doi: 10.1088/1475-7516/2019/02/056

A Eddins, JM Kreikebaum, DM Toyli, EM Levenson-Falk, A Dove, WP Livingston, BA Levitan, LCG Govia, AA Clerk, I Siddiqi, "High-Efficiency Measurement of an Artificial Atom Embedded in a Parametric Amplifier", Physical Review X, 2019, 9, doi: 10.1103/PhysRevX.9.011004

E. Y. Hsiao, M. M. Phillips, G. H. Marion, R. P. Kirshner, N. Morrell, D. J. Sand, C. R. Burns, C. Contreras, P. Hoeflich, M. D. Stritzinger, S. Valenti, J. P. Anderson, C. Ashall, C. Baltay, E. Baron, D. P. K. Banerjee, S. Davis, T. R. Diamond, G. Folatelli, Wendy L. Freedman, F. F\ orster, L. Galbany, C. Gall, S. Gonz\ alez-Gait\ an, A. Goobar, M. Hamuy, S. Holmbo, M. M. Kasliwal, K. Krisciunas, S. Kumar, C. Lidman, J. Lu, P. E. Nugent, S. Perlmutter, S. E. Persson, A. L. Piro, D. Rabinowitz, M. Roth, S. D. Ryder, B. P. Schmidt, M. Shahbandeh, N. B. Suntzeff, F. Taddia, S. Uddin, L. Wang, Carnegie Supernova Project-II: The Near-infrared Spectroscopy Program, Publications of the ASP, Pages: 014002 2019, doi: 10.1088/1538-3873/aae961

M. M. Phillips, C. Contreras, E. Y. Hsiao, N., C. R. Burns, M. Stritzinger, C. Ashall, W. L., P. Hoeflich, S. E. Persson, A. L., N. B. Suntzeff, S. A. Uddin, J. Anais, E., L. Busta, A. Campillay, S. Castell\ on, C., T. Diamond, C. Gall, C. Gonzalez, S., K. Krisciunas, M. Roth, J. Ser\ on, F., S. Torres, J. P. Anderson, C. Baltay, G., L. Galbany, A. Goobar, E. Hadjiyska, M., M. Kasliwal, C. Lidman, P. E. Nugent, S., D. Rabinowitz, S. D. Ryder, B. P. Schmidt, B. J. Shappee, E. S. Walker, "Carnegie Supernova Project-II: Extending the Near-infrared Hubble Diagram for Type Ia Supernovae to z\nbsp\sim\nbsp0.1", Publications of the ASP, 2019, 131:014001, doi: 10.1088/1538-3873/aae8bd

C Varadharajan, B Faybishenko, A Henderson, M Henderson, VC Hendrix, SS Hubbard, Z Kakalia, A Newman, B Potter, H Steltzer, R Versteeg, DA Agarwal, KH Williams, C Wilmer, Y Wu, W Brown, M Burrus, RWH Carroll, DS Christianson, B Dafflon, D Dwivedi, BJ Enquist, Challenges in Building an End-to-End System for Acquisition, Management, and Integration of Diverse Data from Sensor Networks in Watersheds: Lessons from a Mountainous Community Observatory in East River, Colorado, IEEE Access, Pages: 182796--18 2019, doi: 10.1109/ACCESS.2019.2957793

C Varadharajan, S Cholia, C Snavely, V Hendrix, C Procopiou, D Swantek, W Riley, D Agarwal, "Launching an Accessible Archive of Environmental Data", Eos, January 1, 2019, 100, doi: 10.1029/2019eo111263

Dipak Ghosal, Sambit Shukla, Alex Sim, Aditya V Thakur, Kesheng Wu, "A Reinforcement Learning Based Network Scheduler For Deadline-Driven Data Transfers", 2019 IEEE Global Communications Conference (GLOBECOM), 2019, 1--6,

Moritz Kiehn, others, The TrackML high-energy physics tracking challenge on Kaggle, EPJ Web Conf., Pages: 06037 2019, doi: 10.1051/epjconf/201921406037

Sabrina Amrouche, others, The Tracking Machine Learning challenge : Accuracy phase, The NeurIPS 18 Competition: From Machine Learning to Intelligent Conversations, 2019, doi: 10.1007/978-3-030-29135-8_9

Illya Shapoval, Paolo Calafiura, Quantum Associative Memory in HEP Track Pattern Recognition, EPJ Web Conf., Pages: 01012 2019, doi: 10.1051/epjconf/201921401012

W Cui, G Tzimpragos, Y Tao, J Mcmahan, D Dangwal, N Tsiskaridze, G Michelogiannakis, DP Vasudevan, T Sherwood, "Language Support for Navigating Architecture Design in Closed Form", ACM Journal on Emerging Technologies in Computing Systems, January 2019, 16:1--28, doi: 10.1145/3360047

Qiao Kang, Ankit Agrawal, Alok Choudhary, Alex Sim, Kesheng Wu, Rajkumar Kettimuthu, Peter H Beckman, Zhengchun Liu, Wei-keng Liao, "Spatiotemporal Real-Time Anomaly Detection for Supercomputing Systems", 2019 IEEE International Conference on Big Data (Big Data), 2019, 4381--4389,

Burak Cetin, Alina Lazar, Jinoh Kim, Alex Sim, Kesheng Wu, "Federated Wireless Network Intrusion Detection", 2019 IEEE International Conference on Big Data (Big Data), Pages: 6004--6006 2019,

Olivia Del Guercio, Rafael Orozco, Alex Sim, Kesheng Wu, "Multidimensional Compression with Pattern Matching", 2019 Data Compression Conference (DCC), Pages: 567--567 2019,

Daan Camps, Karl Meerbergen, Raf Vandebril, "A rational QZ method", SIAM J. Matrix Anal. Appl., 2019, 40:943--972, doi: 10.1137/18M1170480

Daan Camps, Karl Meerbergen, Raf Vandebril, "An implicit filter for rational Krylov using core transformations", Linear Algebra Appl., 2019, 561:113--140, doi: 10.1016/j.laa.2018.09.021

S Takakura, MAO Aguilar-Faundez, Y Akiba, K Arnold, C Baccigalupi, D Barron, D Beck, F Bianchini, D Boettger, J Borrill, K Cheung, Y Chinone, T Elleflot, J Errard, G Fabbian, C Feng, N Goeckner-Wald, T Hamada, M Hasegawa, M Hazumi, L Howe, D Kaneko, N Katayama, B Keating, R Keskitalo, T Kisner, N Krachmalnicoff, A Kusaka, AT Lee, LN Lowry, FT Matsuda, AJ May, Y Minami, M Navaroli, H Nishino, L Piccirillo, D Poletti, G Puglisi, CL Reichardt, Y Segawa, M Silva-Feaver, P Siritanasak, A Suzuki, O Tajima, S Takatori, D Tanabe, GP Teply, C Tsai, "Measurements of Tropospheric Ice Clouds with a Ground-based CMB Polarization Experiment, POLARBEAR", Astrophysical Journal, 2019, 870, doi: 10.3847/1538-4357/aaf381

Pole swapping methods for the eigenvalue problem - Rational QR algorithms, Daan Camps, 2019,

Daan Camps, Nicola Mastronardi, Raf Vandebril, Paul Van Dooren, "Swapping 2 × 2 blocks in the Schur and generalized Schur form", Journal of Computational and Applied Mathematics, 2019, doi: https://doi.org/10.1016/j.cam.2019.05.022

Jongbeen Han, Heemin Kim, Hyeonsang Eom, Jonathan Coignard, Kesheng Wu, Yongseok Son, "Enabling SQL-Query Processing for Ethereum-based Blockchain Systems", Proceedings of the 9th International Conference on Web Intelligence, Mining and Semantics, 2019, 1--7,

Jung Heon Song, Marcos L\ opez de Prado, Horst D Simon, Kesheng Wu, Extracting Signals from High-Frequency Trading with Digital Signal Processing Tools, The Journal of Financial Data Science, Pages: 124--138 2019,

BA Brock, Y Chen, J Yan, JD Owens, A Buluç, KA Yelick, RDMA vs. RPC for Implementing Distributed Data Structures., [email protected], Pages: 17--22 2019,

Junmin Gu, Burlen Loring, Kesheng Wu, E Wes Bethel, "HDF5 as a vehicle for in transit data movement", Proceedings of the Workshop on In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization, 2019, 39--43,

Beytullah Yildiz, Kesheng Wu, Suren Byna, Arie Shoshani, "Parallel membership queries on very large scientific data sets using bitmap indexes", Concurrency and Computation: Practice and Experience, January 1, 2019, 31:e5157,

Many scientific applications produce very large amounts of data as advances in hardware fuel computing and experimental facilities. Managing and analyzing massive quantities of scientific data is challenging as data are often stored in specific formatted files, such as HDF5 and NetCDF, which do not offer appropriate search capabilities. In this research, we investigated a special class of search capability, called membership query, to identify whether queried elements of a set are members of an attribute. Attributes that naturally have classification values appear frequently in scientific domains such as category and object type as well as in daily life such as zip code and occupation. Because classification attribute values are discrete and require random data access, performing a membership query on a large scientific data set creates challenges. We applied bitmap indexing and parallelization to membership queries to overcome these challenges. Bitmap indexing provides high performance not only for low cardinality attributes but also for high cardinality attributes, such as floating‐point variables, electric charge, or momentum in a particle physics data set, due to compression algorithms such as Word‐Aligned Hybrid. We conducted experiments, in a highly parallelized environment, on data obtained from a particle accelerator model and a synthetic data set.

J. Müller, M. Day, "Surrogate Optimization of Computationally Expensive Black-Box Problems with Hidden Constraints", INFORMS Journal on Computing, 2019, 31:633-845,

W. Langhans, J. Mueller, W.D. Collins, "Optimization of the Eddy-Diffusivity/Mass-Flux shallow cumulus and boundary-layer parametrization using surrogate models", Journal of Advances in Modeling Earth Systems (JAMES), Vol 11, Issue 2,, 2019,

J Atalaya, S Hacohen-Gourgy, I Siddiqi, AN Korotkov, "Correlators Exceeding One in Continuous Measurements of Superconducting Qubits.", Physical review letters, 2019, 122:223603, doi: 10.1103/physrevlett.122.223603

Y. Liu, W. Sid-Lakhdar, E. Rebrova, P. Ghysels, X. Sherry Li, "A parallel hierarchical blocked adaptive cross approximation algorithm", The International Journal of High Performance Computing Applications, January 1, 2019,

Payton A Linton, William M Melodia, Alina Lazar, Deborah Agarwal, Ludovico Bianchi, Devarshi Ghoshal, Kesheng Wu, Gilberto Pastorello, Lavanya Ramakrishnan, "Identifying Time Series Similarity in Large-Scale Earth System Datasets", 2019,

Kesheng Wu, Alex Sim, Jonathan Wang, Seongwook Hwangbo, Methods, systems, and devices for accurate signal timing of power component events, 2019,

US Patent app no. 20190138371, “Methods, systems, and devices for accurate signal timing of power component events”

Devarshi Ghoshal, Kesheng Wu, Eric Pouyoul, Erich Strohmaier, "Analysis and Prediction of Data Transfer Throughput for Data-Intensive Workloads", 2019 IEEE International Conference on Big Data (Big Data), 2019, 3648--3657,

E Georganas, R Egan, S Hofmeyr, E Goltsman, B Arndt, A Tritt, A Buluc, L Oliker, K Yelick, "Extreme scale de novo metagenome assembly", Proceedings - International Conference for High Performance Computing, Networking, Storage, and Analysis, SC 2018, 2019, 122--134, doi: 10.1109/SC.2018.00013

R. Oguz Selvitopi, Gunduz Vehbi Demirci, Ata Turk, Cevdet Aykanat, "Locality-aware and load-balanced static task scheduling for MapReduce", Future Generation Computer Systems (FGCS), January 2019, 90:49-61, doi: https://doi.org/10.1016/j.future.2018.06.035

N Leung, Y Lu, S Chakram, RK Naik, N Earnest, R Ma, K Jacobs, AN Cleland, DI Schuster, "Deterministic bidirectional communication and remote entanglement generation between superconducting qubits", npj Quantum Information, 2019, 5:1--5, doi: 10.1038/s41534-019-0128-0

Victor Yu, William Dawson, Alberto Garcia, Ville Havu, Ben Hourahine, William Huhn, Mathias Jacquelin, Weile Jia, Murat Keceli, Raul Laasner, others, Large-Scale Benchmark of Electronic Structure Solvers with the ELSI Infrastructure, Bulletin of the American Physical Society, 2019,

Anna Y. Q. Ho, Daniel A. Goldstein, Steve Schulze, David K. Khatami, Daniel A. Perley, Mattias Ergon, Avishay Gal-Yam, Alessandra Corsi, Igor Andreoni, Cristina Barbarino, Eric C. Bellm, Nadia Blagorodnova, Joe S. Bright, E. Burns, S. Bradley Cenko, Virginia Cunningham, Kishalay De, Richard Dekany, Alison Dugas, Rob P. Fender, Claes Fransson, Christoffer Fremling, Adam Goldstein, Matthew J. Graham, David Hale, Assaf Horesh, Tiara Hung, Mansi M. Kasliwal, N. Paul M. Kuin, S. R. Kulkarni, Thomas Kupfer, Ragnhild Lunnan, Frank J. Masci, Chow-Choong Ngeow, Peter E. Nugent, Eran O. Ofek, Maria T. Patterson, Glen Petitpas, Ben Rusholme, Hanna Sai, Itai Sfaradi, David L. Shupe, Jesper Sollerman, Maayane T. Soumagnac, Yutaro Tachibana, Francesco Taddia, Richard Walters, Xiaofeng Wang, Yuhan Yao, Xinhan Zhang, Evidence for Late-stage Eruptive Mass Loss in the Progenitor to SN2018gep, a Broad-lined Ic Supernova: Pre-explosion Emission and a Rapidly Rising Luminous Transient, Astrophysical Journal, Pages: 169 2019, doi: 10.3847/1538-4357/ab55ec

Ido Irani, Steve Schulze, Avishay Gal-Yam, Ragnhild Lunnan, Thomas G. Brink, WeiKang Zheng, Alexei V. Filippenko, Yi Yang, Thomas de Jaeger, Peter E. Nugent, Mansi M. Kasliwal, Christoffer Fremling, James Don Neill, Umaa Rebbapragada, Frank J. Masci, Jesper Sollerman, Ofer Yaron, On the Origin of SN 2016hil\textemdashA Type II Supernova in the Remote Outskirts of an Elliptical Host, Astrophysical Journal, Pages: 127 2019, doi: 10.3847/1538-4357/ab505d

Yuhan Yao, Adam A. Miller, S. R. Kulkarni, Mattia Bulla, Frank J. Masci, Daniel A. Goldstein, Ariel Goobar, Peter Nugent, Alison Dugas, Nadia Blagorodnova, James D. Neill, Mickael Rigault, Jesper Sollerman, J. Nordin, Eric C. Bellm, S. Bradley Cenko, Kishalay De, Suhail Dhawan, Ulrich Feindt, C. Fremling, Pradip Gatkine, Matthew J. Graham, Melissa L. Graham, Anna Y. Q. Ho, T. Hung, Mansi M. Kasliwal, Thomas Kupfer, Russ R. Laher, Daniel A. Perley, Ben Rusholme, David L. Shupe, Maayane T. Soumagnac, K. Taggart, Richard Walters, Lin Yan, ZTF Early Observations of Type Ia Supernovae. I. Properties of the 2018 Sample, Astrophysical Journal, Pages: 152 2019, doi: 10.3847/1538-4357/ab4cf5

Ravi Naik, Bradley Mitchell, Unpil Baek, Dar Dahlen, John Mark Kreikebaum, Vinay Ramasesh, Machiel Blok, Irfan Siddiqi, Limitations and improvements of two qubit gates in superconducting circuit QED, APS March Meeting Abstracts, Pages: L29--006 2019,

C. R. Angus, M. Smith, M. Sullivan, C. Inserra, P. Wiseman, C. B. D Andrea, B. P. Thomas, R. C. Nichol, L. Galbany, M. Childress, J. Asorey, P. J. Brown, R. Casas, F. J. Castander, C. Curtin, C. Frohmaier, K. Glazebrook, D. Gruen, C. Gutierrez, R. Kessler, A. G. Kim, C. Lidman, E. Macaulay, P. Nugent, M. Pursiainen, M. Sako, M. Soares-Santos, R. C. Thomas, T. M. C. Abbott, S. Avila, E. Bertin, D. Brooks, E. Buckley-Geer, D. L. Burke, A. Carnero Rosell, J. Carretero, L. N. da Costa, J. De Vicente, S. Desai, H. T. Diehl, P. Doel, T. F. Eifler, B. Flaugher, P. Fosalba, J. Frieman, J. Garc\ \ia-Bellido, R. A. Gruendl, J. Gschwend, W. G. Hartley, D. L. Hollowood, K. Honscheid, B. Hoyle, D. J. James, K. Kuehn, N. Kuropatkin, O. Lahav, M. Lima, M. A. G. Maia, M. March, J. L. Marshall, F. Menanteau, C. J. Miller, R. Miquel, R. L. C. Ogando, A. A. Plazas, A. K. Romer, E. Sanchez, R. Schindler, M. Schubnell, F. Sobreira, E. Suchyta, M. E. C. Swanson, G. Tarle, D. Thomas, D. L. Tucker, DES Collaboration, Superluminous supernovae from the Dark Energy Survey, Monthly Notices of the RAS, Pages: 2215-2241 2019, doi: 10.1093/mnras/stz1321

Srivatsan Chakram, Ravi Naik, Akash Dixit, Yao Lu, Alexander Anferov, Nelson Leung, Andrew Oriani, David Schuster, Quantum information processing using 3D multimode circuit QED, APS March Meeting Abstracts, Pages: C29--008 2019,

Igor Andreoni, Daniel A. Goldstein, Shreya Anand, Michael W. Coughlin, Leo P. Singer, Tom\ as Ahumada, Michael Medford, Erik C. Kool, Sara Webb, Mattia Bulla, Joshua S. Bloom, Mansi M. Kasliwal, Peter E. Nugent, Ashot Bagdasaryan, Jennifer Barnes, David O. Cook, Jeff Cooke, Dmitry A. Duev, U. Christoffer Fremling, Pradip Gatkine, V. Zach Golkhou, Albert K. H. Kong, Ashish Mahabal, Jorge Mart\ \inez-Palomera, Duo Tao, Keming Zhang, GROWTH on S190510g: DECam Observation Planning and Follow-up of a Distant Binary Neutron Star Merger Candidate, Astrophysical Journal Letters, Pages: L16 2019, doi: 10.3847/2041-8213/ab3399

Akash Dixit, David Schuster, Aaron Chou, Ankur Agrawal, Srivatsan Chakram, Ravi Naik, Axion Dark Matter Detection with Superconducting Qubits, APS March Meeting Abstracts, Pages: K28--010 2019,

Daniel A. Goldstein, Igor Andreoni, Peter E. Nugent, Mansi M. Kasliwal, Michael W. Coughlin, Shreya Anand, Joshua S. Bloom, Jorge Mart\ \inez-Palomera, Keming Zhang, Tom\ as Ahumada, Ashot Bagdasaryan, Jeff Cooke, Kishalay De, Dmitry A. Duev, U. Christoffer Fremling, Pradip Gatkine, Matthew Graham, Eran O. Ofek, Leo P. Singer, Lin Yan, GROWTH on S190426c: Real-time Search for a Counterpart to the Probable Neutron Star-Black Hole Merger using an Automated Difference Imaging Pipeline for DECam, Astrophysical Journal Letters, Pages: L7 2019, doi: 10.3847/2041-8213/ab3046

Bradley Mitchell, Ravi Naik, Unpil Baek, Dar Dahlen, John Mark Kreikebaum, Kevin O Brien, Vinay Ramasesh, Machiel Blok, Wim Lavrijsen, Costin Iancu, others, Experimental Methods for Improving Heuristic Quantum Algorithms on NISQ Devices, APS March Meeting Abstracts, Pages: C42--012 2019,

Deep Chatterjee, Peter E. Nugent, Patrick R. Brady, Chris Cannella, David L. Kaplan, Mansi M. Kasliwal, Toward Rate Estimation for Transient Surveys. I. Assessing Transient Detectability and Volume Sensitivity for iPTF, Astrophysical Journal, Pages: 128 2019, doi: 10.3847/1538-4357/ab2b9c

Matthew J. Graham, S. R. Kulkarni, Eric C. Bellm, Scott M. Adams, Cristina Barbarino, Nadejda Blagorodnova, Dennis Bodewits, Bryce Bolin, Patrick R. Brady, S. Bradley Cenko, Chan-Kao Chang, Michael W. Coughlin, Kishalay De, Gwendolyn Eadie, Tony L. Farnham, Ulrich Feindt, Anna Franckowiak, Christoffer Fremling, Suvi Gezari, Shaon Ghosh, Daniel A. Goldstein, V. Zach Golkhou, Ariel Goobar, Anna Y. Q. Ho, Daniela Huppenkothen, \vZeljko Ivezi\ c, R. Lynne Jones, Mario Juric, David L. Kaplan, Mansi M. Kasliwal, Michael S. P. Kelley, Thomas Kupfer, Chien-De Lee, Hsing Wen Lin, Ragnhild Lunnan, Ashish A. Mahabal, Adam A. Miller, Chow-Choong Ngeow, Peter Nugent, Eran O. Ofek, Thomas A. Prince, Ludwig Rauch, Jan van Roestel, Steve Schulze, Leo P. Singer, Jesper Sollerman, Francesco Taddia, Lin Yan, Quan-Zhi Ye, Po-Chieh Yu, Tom Barlow, James Bauer, Ron Beck, Justin Belicki, Rahul Biswas, Valery Brinnel, Tim Brooke, Brian Bue, Mattia Bulla, Rick Burruss, Andrew Connolly, John Cromer, Virginia Cunningham, Richard Dekany, Alex Delacroix, Vandana Desai, Dmitry A. Duev, Michael Feeney, David Flynn, Sara Frederick, Avishay Gal-Yam, Matteo Giomi, Steven Groom, Eugean Hacopians, David Hale, George Helou, John Henning, David Hover, Lynne A. Hillenbrand, Justin Howell, Tiara Hung, David Imel, Wing-Huen Ip, Edward Jackson, Shai Kaspi, Stephen Kaye, Marek Kowalski, Emily Kramer, Michael Kuhn, Walter Landry, Russ R. Laher, Peter Mao, Frank J. Masci, Serge Monkewitz, Patrick Murphy, Jakob Nordin, Maria T. Patterson, Bryan Penprase, Michael Porter, Umaa Rebbapragada, Dan Reiley, Reed Riddle, Mickael Rigault, Hector Rodriguez, Ben Rusholme, Jakob van Santen, David L. Shupe, Roger M. Smith, Maayane T. Soumagnac, Robert Stein, Jason Surace, Paula Szkody, Scott Terek, Angela Van Sistine, Sjoert van Velzen, W. Thomas Vestrand, Richard Walters, Charlotte Ward, Chaoran Zhang, Jeffry Zolkower, The Zwicky Transient Facility: Science Objectives, Publications of the ASP, Pages: 078001 2019, doi: 10.1088/1538-3873/ab006c

Daniel A. Goldstein, Peter E. Nugent, Ariel Goobar, Rates and Properties of Supernovae Strongly Gravitationally Lensed by Elliptical Galaxies in Time-domain Imaging Surveys, Astrophysical Journal Supplement, Pages: 6 2019, doi: 10.3847/1538-4365/ab1fe0

Eric C. Bellm, Shrinivas R. Kulkarni, Tom Barlow, Ulrich Feindt, Matthew J. Graham, Ariel Goobar, Thomas Kupfer, Chow-Choong Ngeow, Peter Nugent, Eran Ofek, Thomas A. Prince, Reed Riddle, Richard Walters, Quan-Zhi Ye, The Zwicky Transient Facility: Surveys and Scheduler, Publications of the ASP, Pages: 068003 2019, doi: 10.1088/1538-3873/ab0c2a

C. Frohmaier, M. Sullivan, P. E. Nugent, M. Smith, G. Dimitriadis, J. S. Bloom, S. B. Cenko, M. M. Kasliwal, S. R. Kulkarni, K. Maguire, E. O. Ofek, D. Poznanski, R. M. Quimby, The volumetric rate of normal type Ia supernovae in the local Universe discovered by the Palomar Transient Factory, Monthly Notices of the RAS, Pages: 2308-2320 2019, doi: 10.1093/mnras/stz807

M. Del Ben, F.H. da Jornada, A. Canning, N. Wichmann, K. Raman, R. Sasanka, C. Yang, S.G. Louie, J. Deslippe, "Large-scale GW calculations on pre-exascale HPC systems", Computer Physics Communications, 2019, 235:187-195, doi: 10.1016/j.cpc.2018.09.003

E. Macaulay, R. C. Nichol, D. Bacon, D. Brout, T. M. Davis, B. Zhang, B. A. Bassett, D. Scolnic, A. M\ oller, C. B. D Andrea, S. R. Hinton, R. Kessler, A. G. Kim, J. Lasker, C. Lidman, M. Sako, M. Smith, M. Sullivan, T. M. C. Abbott, S. Allam, J. Annis, J. Asorey, S. Avila, K. Bechtol, D. Brooks, P. Brown, D. L. Burke, J. Calcino, A. Carnero Rosell, D. Carollo, M. Carrasco Kind, J. Carretero, F. J. Castander, T. Collett, M. Crocce, C. E. Cunha, L. N. da Costa, C. Davis, J. De Vicente, H. T. Diehl, P. Doel, A. Drlica-Wagner, T. F. Eifler, J. Estrada, A. E. Evrard, A. V. Filippenko, D. A. Finley, B. Flaugher, R. J. Foley, P. Fosalba, J. Frieman, L. Galbany, J. Garc\ \ia-Bellido, E. Gaztanaga, K. Glazebrook, S. Gonz\ alez-Gait\ an, D. Gruen, R. A. Gruendl, J. Gschwend, G. Gutierrez, W. G. Hartley, D. L. Hollowood, K. Honscheid, J. K. Hoormann, B. Hoyle, D. Huterer, B. Jain, D. J. James, T. Jeltema, E. Kasai, E. Krause, K. Kuehn, N. Kuropatkin, O. Lahav, G. F. Lewis, T. S. Li, M. Lima, H. Lin, M. A. G. Maia, J. L. Marshall, P. Martini, R. Miquel, P. Nugent, A. Palmese, Y. -C. Pan, A. A. Plazas, A. K. Romer, A. Roodman, E. Sanchez, V. Scarpine, R. Schindler, M. Schubnell, S. Serrano, I. Sevilla-Noarbe, R. Sharp, M. Soares-Santos, F. Sobreira, N. E. Sommer, E. Suchyta, E. Swann, M. E. C. Swanson, G. Tarle, D. Thomas, R. C. Thomas, B. E. Tucker, S. A. Uddin, V. Vikram, A. R. Walker, P. Wiseman, DES Collaboration, First cosmological results using Type Ia supernovae from the Dark Energy Survey: measurement of the Hubble constant, Monthly Notices of the RAS, Pages: 2184-2196 2019, doi: 10.1093/mnras/stz978

E. O. Ofek, B. Zackay, A. Gal-Yam, J. Sollerman, C. Fransson, C. Fremling, S. R. Kulkarni, P. E. Nugent, O. Yaron, M. M. Kasliwal, F. Masci, R. Laher, A Six-year Image-subtraction Light Curve of SN2010jl, Publications of the ASP, Pages: 054204 2019, doi: 10.1088/1538-3873/ab0a19

R. Kessler, D. Brout, C. B. D Andrea, T. M. Davis, S. R. Hinton, A. G. Kim, J. Lasker, C. Lidman, E. Macaulay, A. M\ oller, M. Sako, D. Scolnic, M. Smith, M. Sullivan, B. Zhang, P. Andersen, J. Asorey, A. Avelino, J. Calcino, D. Carollo, P. Challis, M. Childress, A. Clocchiatti, S. Crawford, A. V. Filippenko, R. J. Foley, K. Glazebrook, J. K. Hoormann, E. Kasai, R. P. Kirshner, G. F. Lewis, K. S. Mandel, M. March, E. Morganson, D. Muthukrishna, P. Nugent, Y. -C. Pan, N. E. Sommer, E. Swann, R. C. Thomas, B. E. Tucker, S. A. Uddin, T. M. C. Abbott, S. Allam, J. Annis, S. Avila, M. Banerji, K. Bechtol, E. Bertin, D. Brooks, E. Buckley-Geer, D. L. Burke, A. Carnero Rosell, M. Carrasco Kind, J. Carretero, F. J. Castander, M. Crocce, L. N. da Costa, C. Davis, J. De Vicente, S. Desai, H. T. Diehl, P. Doel, T. F. Eifler, B. Flaugher, P. Fosalba, J. Frieman, J. Garc\ \ia-Bellido, E. Gaztanaga, D. W. Gerdes, D. Gruen, R. A. Gruendl, G. Gutierrez, W. G. Hartley, D. L. Hollowood, K. Honscheid, D. J. James, M. W. G. Johnson, M. D. Johnson, E. Krause, K. Kuehn, N. Kuropatkin, O. Lahav, T. S. Li, M. Lima, J. L. Marshall, P. Martini, F. Menanteau, C. J. Miller, R. Miquel, B. Nord, A. A. Plazas, A. Roodman, E. Sanchez, V. Scarpine, R. Schindler, M. Schubnell, S. Serrano, I. Sevilla-Noarbe, M. Soares-Santos, F. Sobreira, E. Suchyta, G. Tarle, D. Thomas, A. R. Walker, Y. Zhang, DES Collaboration, First cosmology results using Type Ia supernova from the Dark Energy Survey: simulations to correct supernova distance biases, Monthly Notices of the RAS, Pages: 1171-1187 2019, doi: 10.1093/mnras/stz463

Arjun Dey, David J. Schlegel, Dustin Lang, Robert Blum, Kaylan Burleigh, Xiaohui Fan, Joseph R. Findlay, Doug Finkbeiner, David Herrera, St\ ephanie Juneau, Martin Landriau, Michael Levi, Ian McGreer, Aaron Meisner, Adam D. Myers, John Moustakas, Peter Nugent, Anna Patej, Edward F. Schlafly, Alistair R. Walker, Francisco Valdes, Benjamin A. Weaver, Christophe Y\ eche, Hu Zou, Xu Zhou, Behzad Abareshi, T. M. C. Abbott, Bela Abolfathi, C. Aguilera, Shadab Alam, Lori Allen, A. Alvarez, James Annis, Behzad Ansarinejad, Marie Aubert, Jacqueline Beechert, Eric F. Bell, Segev Y. BenZvi, Florian Beutler, Richard M. Bielby, Adam S. Bolton, C\ esar Brice\ no, Elizabeth J. Buckley-Geer, Karen Butler, Annalisa Calamida, Raymond G. Carlberg, Paul Carter, Ricard Casas, Francisco J. Castander, Yumi Choi, Johan Comparat, Elena Cukanovaite, Timoth\ ee Delubac, Kaitlin DeVries, Sharmila Dey, Govinda Dhungana, Mark Dickinson, Zhejie Ding, John B. Donaldson, Yutong Duan, Christopher J. Duckworth, Sarah Eftekharzadeh, Daniel J. Eisenstein, Thomas Etourneau, Parker A. Fagrelius, Jay Farihi, Mike Fitzpatrick, Andreu Font-Ribera, Leah Fulmer, Boris T. G\ ansicke, Enrique Gaztanaga, Koshy George, David W. Gerdes, Satya Gontcho A. Gontcho, Claudio Gorgoni, Gregory Green, Julien Guy, Diane Harmer, M. Hernandez, Klaus Honscheid, Lijuan Wendy Huang, David J. James, Buell T. Jannuzi, Linhua Jiang, Richard Joyce, Armin Karcher, Sonia Karkar, Robert Kehoe, Jean-Paul Kneib, Andrea Kueter-Young, Ting-Wen Lan, Tod R. Lauer, Laurent Le Guillou, Auguste Le Van Suu, Jae Hyeon Lee, Michael Lesser, Laurence Perreault Levasseur, Ting S. Li, Justin L. Mann, Robert Marshall, C. E. Mart\ \inez-V\ azquez, Paul Martini, H\ elion du Mas des Bourboux, Sean McManus, Tobias Gabriel Meier, Brice M\ enard, Nigel Metcalfe, Andrea Mu\ noz-Guti\ errez, Joan Najita, Kevin Napier, Gautham Narayan, Jeffrey A. Newman, Jundan Nie, Brian Nord, Dara J. Norman, Knut A. G. Olsen, Anthony Paat, Nathalie Palanque-Delabrouille, Xiyan Peng, Claire L. Poppett, Megan R. Poremba, Abhishek Prakash, David Rabinowitz, Anand Raichoor, Mehdi Rezaie, A. N. Robertson, Natalie A. Roe, Ashley J. Ross, Nicholas P. Ross, Gregory Rudnick, Sasha Safonova, Abhijit Saha, F. Javier S\ anchez, Elodie Savary, Heidi Schweiker, Adam Scott, Hee-Jong Seo, Huanyuan Shan, David R. Silva, Zachary Slepian, Christian Soto, David Sprayberry, Ryan Staten, Coley M. Stillman, Robert J. Stupak, David L. Summers, Suk Sien Tie, H. Tirado, Mariana Vargas-Maga\ na, A. Katherina Vivas, Risa H. Wechsler, Doug Williams, Jinyi Yang, Qian Yang, Tolga Yapici, Dennis Zaritsky, A. Zenteno, Kai Zhang, Tianmeng Zhang, Rongpu Zhou, Zhimin Zhou, Overview of the DESI Legacy Imaging Surveys, Astronomical Journal, Pages: 168 2019, doi: 10.3847/1538-3881/ab089d

J. van Roestel, P. J. Groot, T. Kupfer, K. Verbeek, S. van Velzen, M. Bours, P. Nugent, T. Prince, D. Levitan, S. Nissanke, S. R. Kulkarni, R. R. Laher, The Palomar Transient Factory Sky2Night programme, Monthly Notices of the RAS, Pages: 4507-4528 2019, doi: 10.1093/mnras/stz241

D. Brout, D. Scolnic, R. Kessler, C. B. D Andrea, T. M. Davis, R. R. Gupta, S. R. Hinton, A. G. Kim, J. Lasker, C. Lidman, E. Macaulay, A. M\ oller, R. C. Nichol, M. Sako, M. Smith, M. Sullivan, B. Zhang, P. Andersen, J. Asorey, A. Avelino, B. A. Bassett, P. Brown, J. Calcino, D. Carollo, P. Challis, M. Childress, A. Clocchiatti, A. V. Filippenko, R. J. Foley, L. Galbany, K. Glazebrook, J. K. Hoormann, E. Kasai, R. P. Kirshner, K. Kuehn, S. Kuhlmann, G. F. Lewis, K. S. Mandel, M. March, V. Miranda, E. Morganson, D. Muthukrishna, P. Nugent, A. Palmese, Y. -C. Pan, R. Sharp, N. E. Sommer, E. Swann, R. C. Thomas, B. E. Tucker, S. A. Uddin, W. Wester, T. M. C. Abbott, S. Allam, J. Annis, S. Avila, K. Bechtol, G. M. Bernstein, E. Bertin, D. Brooks, D. L. Burke, A. Carnero Rosell, M. Carrasco Kind, J. Carretero, F. J. Castander, C. E. Cunha, L. N. da Costa, C. Davis, J. De Vicente, D. L. DePoy, S. Desai, H. T. Diehl, P. Doel, A. Drlica-Wagner, T. F. Eifler, J. Estrada, E. Fernandez, B. Flaugher, P. Fosalba, J. Frieman, J. Garc\ \ia-Bellido, D. Gruen, R. A. Gruendl, G. Gutierrez, W. G. Hartley, D. L. Hollowood, K. Honscheid, B. Hoyle, D. J. James, M. Jarvis, T. Jeltema, E. Krause, O. Lahav, T. S. Li, M. Lima, M. A. G. Maia, J. Marriner, J. L. Marshall, P. Martini, F. Menanteau, C. J. Miller, R. Miquel, R. L. C. Ogando, A. A. Plazas, A. K. Romer, A. Roodman, E. S. Rykoff, E. Sanchez, B. Santiago, V. Scarpine, M. Schubnell, S. Serrano, I. Sevilla-Noarbe, R. C. Smith, M. Soares-Santos, F. Sobreira, E. Suchyta, M. E. C. Swanson, G. Tarle, D. Thomas, M. A. Troxel, D. L. Tucker, V. Vikram, A. R. Walker, Y. Zhang, DES Collaboration, First Cosmology Results Using SNe Ia from the Dark Energy Survey: Analysis, Systematic Uncertainties, and Validation, Astrophysical Journal, Pages: 150 2019, doi: 10.3847/1538-4357/ab08a0

D. Brout, M. Sako, D. Scolnic, R. Kessler, C. B. D Andrea, T. M. Davis, S. R. Hinton, A. G. Kim, J. Lasker, E. Macaulay, A. M\ oller, R. C. Nichol, M. Smith, M. Sullivan, R. C. Wolf, S. Allam, B. A. Bassett, P. Brown, F. J. Castander, M. Childress, R. J. Foley, L. Galbany, K. Herner, E. Kasai, M. March, E. Morganson, P. Nugent, Y. -C. Pan, R. C. Thomas, B. E. Tucker, W. Wester, T. M. C. Abbott, J. Annis, S. Avila, E. Bertin, D. Brooks, D. L. Burke, A. Carnero Rosell, M. Carrasco Kind, J. Carretero, M. Crocce, C. E. Cunha, L. N. da Costa, C. Davis, J. De Vicente, S. Desai, H. T. Diehl, P. Doel, T. F. Eifler, B. Flaugher, P. Fosalba, J. Frieman, J. Garc\ \ia-Bellido, E. Gaztanaga, D. W. Gerdes, D. A. Goldstein, D. Gruen, R. A. Gruendl, J. Gschwend, G. Gutierrez, W. G. Hartley, D. L. Hollowood, K. Honscheid, D. J. James, K. Kuehn, N. Kuropatkin, O. Lahav, T. S. Li, M. Lima, J. L. Marshall, P. Martini, R. Miquel, B. Nord, A. A. Plazas, A. Roodman, E. S. Rykoff, E. Sanchez, V. Scarpine, R. Schindler, M. Schubnell, S. Serrano, I. Sevilla-Noarbe, M. Soares-Santos, F. Sobreira, E. Suchyta, M. E. C. Swanson, G. Tarle, D. Thomas, D. L. Tucker, A. R. Walker, B. Yanny, Y. Zhang, DES COLLABORATION, First Cosmology Results Using Type Ia Supernovae from the Dark Energy Survey: Photometric Pipeline and Light-curve Data Release, Astrophysical Journal, Pages: 106 2019, doi: 10.3847/1538-4357/ab06c1

Kishalay De, Mansi M. Kasliwal, Abigail Polin, Peter E. Nugent, Lars Bildsten, Scott M. Adams, Eric C. Bellm, Nadia Blagorodnova, Kevin B. Burdge, Christopher Cannella, S. Bradley Cenko, Richard G. Dekany, Michael Feeney, David Hale, U. Christoffer Fremling, Matthew J. Graham, Anna Y. Q. Ho, Jacob E. Jencson, S. R. Kulkarni, Russ R. Laher, Frank J. Masci, Adam A. Miller, Maria T. Patterson, Umaa Rebbapragada, Reed L. Riddle, David L. Shupe, Roger M. Smith, ZTF 18aaqeasu (SN2018byg): A Massive Helium-shell Double Detonation on a Sub-Chandrasekhar-mass White Dwarf, Astrophysical Journal Letters, Pages: L18 2019, doi: 10.3847/2041-8213/ab0aec

N. Blagorodnova, S. B. Cenko, S. R. Kulkarni, I. Arcavi, J. S. Bloom, G. Duggan, A. V. Filippenko, C. Fremling, A. Horesh, G. Hosseinzadeh, E. Karamehmetoglu, A. Levan, F. J. Masci, P. E. Nugent, D. R. Pasham, S. Veilleux, R. Walters, L. Yan, W. Zheng, The Broad Absorption Line Tidal Disruption Event iPTF15af: Optical and Ultraviolet Evolution, Astrophysical Journal, Pages: 92 2019, doi: 10.3847/1538-4357/ab04b0

Abigail Polin, Peter Nugent, Daniel Kasen, Observational Predictions for Sub-Chandrasekhar Mass Explosions: Further Evidence for Multiple Progenitor Systems for Type Ia Supernovae, Astrophysical Journal, Pages: 84 2019, doi: 10.3847/1538-4357/aafb6a

T. M. C. Abbott, S. Allam, P. Andersen, C. Angus, J. Asorey, A. Avelino, S. Avila, B. A. Bassett, K. Bechtol, G. M. Bernstein, E. Bertin, D. Brooks, D. Brout, P. Brown, D. L. Burke, J. Calcino, A. Carnero Rosell, D. Carollo, M. Carrasco Kind, J. Carretero, R. Casas, F. J. Castander, R. Cawthon, P. Challis, M. Childress, A. Clocchiatti, C. E. Cunha, C. B. D Andrea, L. N. da Costa, C. Davis, T. M. Davis, J. De Vicente, D. L. DePoy, S. Desai, H. T. Diehl, P. Doel, A. Drlica-Wagner, T. F. Eifler, A. E. Evrard, E. Fernandez, A. V. Filippenko, D. A. Finley, B. Flaugher, R. J. Foley, P. Fosalba, J. Frieman, L. Galbany, J. Garc\ \ia-Bellido, E. Gaztanaga, T. Giannantonio, K. Glazebrook, D. A. Goldstein, S. Gonz\ alez-Gait\ an, D. Gruen, R. A. Gruendl, J. Gschwend, R. R. Gupta, G. Gutierrez, W. G. Hartley, S. R. Hinton, D. L. Hollowood, K. Honscheid, J. K. Hoormann, B. Hoyle, D. J. James, T. Jeltema, M. W. G. Johnson, M. D. Johnson, E. Kasai, S. Kent, R. Kessler, A. G. Kim, R. P. Kirshner, E. Kovacs, E. Krause, R. Kron, K. Kuehn, S. Kuhlmann, N. Kuropatkin, O. Lahav, J. Lasker, G. F. Lewis, T. S. Li, C. Lidman, M. Lima, H. Lin, E. Macaulay, M. A. G. Maia, K. S. Mandel, M. March, J. Marriner, J. L. Marshall, P. Martini, F. Menanteau, C. J. Miller, R. Miquel, V. Miranda, J. J. Mohr, E. Morganson, D. Muthukrishna, A. M\ oller, E. Neilsen, R. C. Nichol, B. Nord, P. Nugent, R. L. C. Ogando, A. Palmese, Y. -C. Pan, A. A. Plazas, M. Pursiainen, A. K. Romer, A. Roodman, E. Rozo, E. S. Rykoff, M. Sako, E. Sanchez, V. Scarpine, R. Schindler, M. Schubnell, D. Scolnic, S. Serrano, I. Sevilla-Noarbe, R. Sharp, M. Smith, M. Soares-Santos, F. Sobreira, N. E. Sommer, H. Spinka, E. Suchyta, M. Sullivan, E. Swann, G. Tarle, D. Thomas, R. C. Thomas, M. A. Troxel, B. E. Tucker, S. A. Uddin, A. R. Walker, W. Wester, P. Wiseman, R. C. Wolf, B. Yanny, B. Zhang, Y. Zhang, DES Collaboration, First Cosmology Results using Type Ia Supernovae from the Dark Energy Survey: Constraints on Cosmological Parameters, Astrophysical Journal Letters, Pages: L30 2019, doi: 10.3847/2041-8213/ab04fa

Maayane T. Soumagnac, Eran O. Ofek, Avishay Gal-yam, Eli Waxman, Sivan Ginzburg, Nora Linn Strotjohann, Steve Schulze, Tom A. Barlow, Ehud Behar, Doron Chelouche, Christoffer Fremling, Noam Ganot, Suvi Gezari, Mansi M. Kasliwal, Shai Kaspi, Shrinivas R. Kulkarni, Russ R. Laher, Dan Maoz, Christopher D. Martin, Ehud Nakar, James D. Neill, Peter E. Nugent, Dovi Poznanski, Ofer Yaron, Supernova PTF 12glz: A Possible Shock Breakout Driven through an Aspherical Wind, Astrophysical Journal, Pages: 141 2019, doi: 10.3847/1538-4357/aafe84

Eric C. Bellm, Shrinivas R. Kulkarni, Matthew J. Graham, Richard Dekany, Roger M. Smith, Reed Riddle, Frank J. Masci, George Helou, Thomas A. Prince, Scott M. Adams, C. Barbarino, Tom Barlow, James Bauer, Ron Beck, Justin Belicki, Rahul Biswas, Nadejda Blagorodnova, Dennis Bodewits, Bryce Bolin, Valery Brinnel, Tim Brooke, Brian Bue, Mattia Bulla, Rick Burruss, S. Bradley Cenko, Chan-Kao Chang, Andrew Connolly, Michael Coughlin, John Cromer, Virginia Cunningham, Kishalay De, Alex Delacroix, Vandana Desai, Dmitry A. Duev, Gwendolyn Eadie, Tony L. Farnham, Michael Feeney, Ulrich Feindt, David Flynn, Anna Franckowiak, S. Frederick, C. Fremling, Avishay Gal-Yam, Suvi Gezari, Matteo Giomi, Daniel A. Goldstein, V. Zach Golkhou, Ariel Goobar, Steven Groom, Eugean Hacopians, David Hale, John Henning, Anna Y. Q. Ho, David Hover, Justin Howell, Tiara Hung, Daniela Huppenkothen, David Imel, Wing-Huen Ip, \vZeljko Ivezi\ c, Edward Jackson, Lynne Jones, Mario Juric, Mansi M. Kasliwal, S. Kaspi, Stephen Kaye, Michael S. P. Kelley, Marek Kowalski, Emily Kramer, Thomas Kupfer, Walter Landry, Russ R. Laher, Chien-De Lee, Hsing Wen Lin, Zhong-Yi Lin, Ragnhild Lunnan, Matteo Giomi, Ashish Mahabal, Peter Mao, Adam A. Miller, Serge Monkewitz, Patrick Murphy, Chow-Choong Ngeow, Jakob Nordin, Peter Nugent, Eran Ofek, Maria T. Patterson, Bryan Penprase, Michael Porter, Ludwig Rauch, Umaa Rebbapragada, Dan Reiley, Mickael Rigault, Hector Rodriguez, Jan van Roestel, Ben Rusholme, Jakob van Santen, S. Schulze, David L. Shupe, Leo P. Singer, Maayane T. Soumagnac, Robert Stein, Jason Surace, Jesper Sollerman, Paula Szkody, F. Taddia, Scott Terek, Angela Van Sistine, Sjoert van Velzen, W. Thomas Vestrand, Richard Walters, Charlotte Ward, Quan-Zhi Ye, Po-Chieh Yu, Lin Yan, Jeffry Zolkower, The Zwicky Transient Facility: System Overview, Performance, and First Results, Publications of the ASP, Pages: 018002 2019, doi: 10.1088/1538-3873/aaecbe

M. M. Phillips, Carlos Contreras, E. Y. Hsiao, Nidia Morrell, Christopher R. Burns, Maximilian Stritzinger, C. Ashall, Wendy L. Freedman, P. Hoeflich, S. E. Persson, Anthony L. Piro, Nicholas B. Suntzeff, Syed A. Uddin, Jorge Anais, E. Baron, Luis Busta, Abdo Campillay, Sergio Castell\ on, Carlos Corco, T. Diamond, Christa Gall, Consuelo Gonzalez, Simon Holmbo, Kevin Krisciunas, Miguel Roth, Jacqueline Ser\ on, F. Taddia, Sim\ on Torres, J. P. Anderson, C. Baltay, Gast\ on Folatelli, L. Galbany, A. Goobar, Ellie Hadjiyska, Mario Hamuy, Mansi Kasliwal, C. Lidman, Peter E. Nugent, S. Perlmutter, David Rabinowitz, Stuart D. Ryder, Brian P. Schmidt, B. J. Shappee, Emma S. Walker, Carnegie Supernova Project-II: Extending the Near-infrared Hubble Diagram for Type Ia Supernovae to z \ensuremath\sim 0.1, Publications of the ASP, Pages: 014001 2019, doi: 10.1088/1538-3873/aae8bd

M. L. Graham, C. E. Harris, P. E. Nugent, K. Maguire, M. Sullivan, M. Smith, S. Valenti, A. Goobar, O. D. Fox, K. J. Shen, P. L. Kelly, C. McCully, T. G. Brink, A. V. Filippenko, Delayed Circumstellar Interaction for Type Ia SN 2015cp Revealed by an HST Ultraviolet Imaging Survey, Astrophysical Journal, Pages: 62 2019, doi: 10.3847/1538-4357/aaf41e

G. Dimitriadis, R. J. Foley, A. Rest, D. Kasen, A. L. Piro, A. Polin, D. O. Jones, A. Villar, G. Narayan, D. A. Coulter, C. D. Kilpatrick, Y. -C. Pan, C. Rojas-Bravo, O. D. Fox, S. W. Jha, P. E. Nugent, A. G. Riess, D. Scolnic, M. R. Drout, K2 Mission Team, G. Barentsen, J. Dotson, M. Gully-Santiago, C. Hedges, A. M. Cody, T. Barclay, S. Howell, KEGS, P. Garnavich, B. E. Tucker, E. Shaya, R. Mushotzky, R. P. Olling, S. Margheim, A. Zenteno, Kepler spacecraft Team, J. Coughlin, J. E. Van Cleve, J. Vin\ \icius de Miranda Cardoso, K. A. Larson, K. M. McCalmont-Everton, C. A. Peterson, S. E. Ross, L. H. Reedy, D. Osborne, C. McGinn, L. Kohnert, L. Migliorini, A. Wheaton, B. Spencer, C. Labonde, G. Castillo, G. Beerman, K. Steward, M. Hanley, R. Larsen, R. Gangopadhyay, R. Kloetzel, T. Weschler, V. Nystrom, J. Moffatt, M. Redick, K. Griest, M. Packard, M. Muszynski, J. Kampmeier, R. Bjella, S. Flynn, B. Elsaesser, Pan-STARRS, K. C. Chambers, H. A. Flewelling, M. E. Huber, E. A. Magnier, C. Z. Waters, A. S. B. Schultz, J. Bulger, T. B. Lowe, M. Willman, S. J. Smartt, K. W. Smith, DECam, S. Points, G. M. Strampelli, ASAS-SN, J. Brimacombe, P. Chen, J. A. Mu\ noz, R. L. Mutel, J. Shields, P. J. Vallely, S. Villanueva, PTSS/TNTS, W. Li, X. Wang, J. Zhang, H. Lin, J. Mo, X. Zhao, H. Sai, X. Zhang, K. Zhang, T. Zhang, L. Wang, J. Zhang, E. Baron, J. M. DerKacy, L. Li, Z. Chen, D. Xiang, L. Rui, L. Wang, F. Huang, X. Li, Las Cumbres Observatory, G. Hosseinzadeh, D. A. Howell, I. Arcavi, D. Hiramatsu, J. Burke, S. Valenti, ATLAS, J. L. Tonry, L. Denneau, A. N. Heinze, H. Weiland, B. Stalder, Konkoly, J. Vink\ o, K. S\ arneczky, A. P\ al, A. B\ odi, Zs. Bogn\ ar, B. Cs\ ak, B. Cseh, G. Cs\ ornyei, O. Hanyecz, B. Ign\ acz, Cs. Kalup, R. K\ onyves-T\ oth, L. Kriskovics, A. Ordasi, I. Rajmon, A. S\ odor, R. Szab\ o, R. Szak\ ats, G. Zsidi, ePESSTO, S. C. Williams, J. Nordin, R. Cartier, C. Frohmaier, L. Galbany, C. P. Guti\ errez, I. Hook, C. Inserra, M. Smith, University of Arizona, D. J. Sand, J. E. Andrews, N. Smith, C. Bilinski, K2 Observations of SN 2018oh Reveal a Two-component Rising Light Curve for a Type Ia Supernova, Astrophysical Journal Letters, Pages: L1 2019, doi: 10.3847/2041-8213/aaedb0

F. Taddia, J. Sollerman, C. Fremling, C. Barbarino, E. Karamehmetoglu, I. Arcavi, S. B. Cenko, A. V. Filippenko, A. Gal-Yam, D. Hiramatsu, G. Hosseinzadeh, D. A. Howell, S. R. Kulkarni, R. Laher, R. Lunnan, F. Masci, P. E. Nugent, A. Nyholm, D. A. Perley, R. Quimby, J. M. Silverman, Analysis of broad-lined Type Ic supernovae from the (intermediate) Palomar Transient Factory, Astronomy and Astrophysics, Pages: A71 2019, doi: 10.1051/0004-6361/201834429

B Brock, A Buluç, K Yelick, "BCL: A cross-platform distributed data structures library", ACM International Conference Proceeding Series, January 2019, doi: 10.1145/3337821.3337912

One-sided communication is a useful paradigm for irregular parallel applications, but most one-sided programming environments, including MPI's one-sided interface and PGAS programming languages, lack application-level libraries to support these applications. We present the Berkeley Container Library, a set of generic, cross-platform, high-performance data structures for irregular applications, including queues, hash tables, Bloom filters and more. BCL is written in C++ using an internal DSL called the BCL Core that provides one-sided communication primitives such as remote get and remote put operations. The BCL Core has backends for MPI, OpenSHMEM, GASNet-EX, and UPC++, allowing BCL data structures to be used natively in programs written using any of these programming environments. Along with our internal DSL, we present the BCL ObjectContainer abstraction, which allows BCL data structures to transparently serialize complex data types while maintaining efficiency for primitive types. We also introduce the set of BCL data structures and evaluate their performance across a number of high-performance computing systems, demonstrating that BCL programs are competitive with hand-optimized code, even while hiding many of the underlying details of message aggregation, serialization, and synchronization.

2018

O. Erbilgin, O. Rübel, K. B. Louie, M. Trinh, M. de Raad, T. Wildish, D. W. Udwary, C. A. Hoover,, "MAGI: A Bayesian-like method for metabolite, annotation, and gene integration", bioRxiv, December 19, 2018, doi: 10.1101/204362

Y. Li, Z. Wen, C. Yang, Y. Yuan, "A Semi-smooth Newton Method For semidefinite programs and its applications in electronic structure calculations", SIAM J. Sci. Comput., December 18, 2018, 40:A4131–A415, doi: 10.1137/18M1188069

Suren Byna, Quincey Koziol, Venkatram Vishwanath, Jerome Soumagne, Houjun Tang, Kimmy Mu, Richard Warren, François Tessier, Bin Dong, Teng Wang, and Jialin Liu, Proactive Data Containers (PDC): An object-centric data store for large-scale computing systems, AGU Fall Meeting, December 13, 2018,

Dan Martin, Brent Minchew, Stephen Price, Esmond Ng, Modeling Marine Ice Cliff Instability: Higher resolution leads to lower impact, AGU Fall Meeting, December 12, 2018,

You-Wei Cheah, Danielle Svehla Christianson, Housen Chu, Gilberto Pastorello, Fianna O’Brien, Yeongshnn Ong, Catharine van Ingen, Margaret Torn, Deb Agarwal, AmeriFlux BADM: Implementing lessons from 12 years of long-tail data management into next generation earth science systems (IN34A-03), 2018 AGU Fall Meeting, Washington, D.C., December 12, 2018,

Kade Gibson, Dongeun Lee, Jaesik Choi, Alex Sim, "Dynamic Online Performance Optimization in Streaming Data Compression", IEEE International Conference on Big Data (Big Data 2018), 2018, doi: 10.1109/bigdata.2018.8621867

Xiaoguang Peng, J. Galen Wang, Qi Li, Dongjie Chen, Roseanna N. Zia, Gregory B. McKenna, "Exploring the validity of time-concentration superposition in glassy colloids: Experiments and simulations", Physical Review E, December 6, 2018, doi: 10.1103/PhysRevE.98.062602

Seher Acer, R. Oguz Selvitopi, Cevdet Aykanat, "Optimizing nonzero-based sparse matrix partitioning models via reducing latency", Journal of Parallel and Distributed Computing (JPDC), December 2018, 122:145-158, doi: https://doi.org/10.1016/j.jpdc.2018.08.005

S. Afach, D. Budker, G. DeCamp, V. Dumont, Z. D. Grujić, H. Guo, D. F. Jackson Kimball, T. W. Kornack, V. Lebedev, W. Li, H. Masia-Roig, S. Nix, M. Padniuk, C. A. Palm, C. Pankow, A. Penaflor, X. Peng, S. Pustelny, T. Scholtes, J. A. Smiga, J. E. Stalnaker, A. Weis, A. Wickenbrock, D. Wurm, "Characterization of the Global Network of Optical Magnetometers to search for Exotic Physics (GNOME)", Physics of the Dark Universe, Volume 22, Pages 162-180, December 2018, doi: 10.1016/j.dark.2018.10.002

R. Van Beeumen, O. Marques, E.G. Ng, C. Yang, Z. Bai, L. Ge, O. Kononenko, Z. Li, C.-K. Ng, L. Xiao, "Computing resonant modes of accelerator cavities by solving nonlinear eigenvalue problems via rational approximation", Journal of Computational Physics, 2018, 374:1031-1043, doi: 10.1016/j.jcp.2018.08.017

Tze Meng Low, Daniele G. Spampinato, Anurag Kutuluru, Upasana Sridhar, Doru Thom Popovici, Franz Franchetti, Scott McMillan, "Linear Algebraic Formulation of Edge-centric K-truss Algorithms with Adjacency Matrices", HPEC, 2018,

Shichao Sun, David B. Williams-Young, Torin F. Stetina, Xiaosong Li, "Generalized Hartree-Fock with a Non-perturbative Treatment of Strong Magnetic Fields: Application to Molecular Spin Phase Transitions", Journal of Chemical Theory and Computation, 2018, 51:348-356, doi: 10.1021/acs.jctc.8b01140

Tuowen Zhao, Samuel Williams, Mary Hall, Hans Johansen, "Delivering Performance Portable Stencil Computations on CPUs and GPUs Using Bricks", International Workshop on Performance, Portability and Productivity in HPC (P3HPC), November 2018,

Charlene Yang, Rahulkumar Gayatri, Thorsten Kurth, Protonu Basu, Zahra Ronaghi, Adedoyin Adetokunbo, Brian Friesen, Brandon Cook, Douglas Doerfler, Leonid Oliker, Jack Deslippe, Samuel Williams, "An Empirical Roofline Methodology for Quantitatively Assessing Performance Portability", International Workshop on Performance, Portability and Productivity in HPC (P3HPC), November 2018,

Paul H. Hargrove, Dan Bonachea, "GASNet-EX Performance Improvements Due to Specialization for the Cray Aries Network", Parallel Applications Workshop, Alternatives To MPI (PAW-ATM), Dallas, Texas, USA, IEEE, November 16, 2018, 23-33, doi: 10.25344/S44S38

GASNet-EX is a portable, open-source, high-performance communication library designed to efficiently support the networking requirements of PGAS runtime systems and other alternative models on future exascale machines. This paper reports on the improvements in performance observed on Cray XC-series systems due to enhancements made to the GASNet-EX software. These enhancements, known as "specializations", primarily consist of replacing network-independent implementations of several recently added features with implementations tailored to the Cray Aries network. Performance gains from specialization include (1) Negotiated-Payload Active Messages improve bandwidth of a ping-pong test by up to 14%, (2) Immediate Operations reduce running time of a synthetic benchmark by up to 93%, (3) non-bulk RMA Put bandwidth is increased by up to 32%, (4) Remote Atomic performance is 70% faster than the reference on a point-to-point test and allows a hot-spot test to scale robustly, and (5) non-contiguous RMA interfaces see up to 8.6x speedups for an intra-node benchmark and 26% for inter-node. These improvements are all available in GASNet-EX version 2018.3.0 and later.

Maximilian H Bremer, John D Bachan, Cy P Chan, "Semi-Static and Dynamic Load Balancing for Asynchronous Hurricane Storm Surge Simulations", 2018 Parallel Applications Workshop, Alternatives To MPI (PAW-ATM), November 16, 2018,

Glenn Lockwood, Shane Snyder, Teng Wang, Suren Byna, Phil Carns, and Nicholas Wright, "A Year in the Life of a Parallel File System", International Conference for High Performance Computing, Networking, and Storage (SC'18), IEEE / ACM, November 15, 2018,

Wahid Bhimji, Steven Farrell, Oliver Evans, Matthew Henderson, Shreyas Cholia, Aaron Vose, Mr Prabhat, Rollin Thomas, Richard Shane Canon, "Interactive HPC Deep Learning with Jupyter Notebooks", Supercomputing 2018, Dallas, TX, November 2018,

Karen Tu, Alex Sim (Advisor), John Wu (Advisor), "Identification of Network Data Transfer Bottlenecks in HPC Systems", International Conference for High Performance Computing, Networking, Storage and Analysis (SC’18), ACM Student Research Competition (SRC), 2018,

Fahim Chowdhury, Jialin Liu, Quincey Koziol, Thorsten Kurth, Steven Farrell, Suren Byna, Prabhat, Weikuan Yu,, Initial Characterization of I/O in Large-Scale Deep Learning Applications, 3rd Joint International Workshop on Parallel Data Storage and Data Intensive Scalable Computing Systems (PDSW-DISCS), November 13, 2018,

Scott B. Baden, Paul H. Hargrove, Hadia Ahmed, John Bachan, Dan Bonachea, Steve Hofmeyr, Mathias Jacquelin, Amir Kamil, Brian van Straalen, "UPC++ and GASNet-EX: PGAS Support for Exascale Applications and Runtimes", The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC'18) Research Poster, November 2018,

Lawrence Berkeley National Lab is developing a programming system to support HPC application development using the Partitioned Global Address Space (PGAS) model. This work is driven by the emerging need for adaptive, lightweight communication in irregular applications at exascale. We present an overview of UPC++ and GASNet-EX, including examples and performance results.

GASNet-EX is a portable, high-performance communication library, leveraging hardware support to efficiently implement Active Messages and Remote Memory Access (RMA). UPC++ provides higher-level abstractions appropriate for PGAS programming such as: one-sided communication (RMA), remote procedure call, locality-aware APIs for user-defined distributed objects, and robust support for asynchronous execution to hide latency. Both libraries have been redesigned relative to their predecessors to meet the needs of exascale computing. While both libraries continue to evolve, the system already demonstrates improvements in microbenchmarks and application proxies.

Nan Ding, Victor W Lee, Wei Xue, Weimin Zheng, "Understanding Potential Performance Issues Using Resource-based Alongside Time Models", SC'18, November 13, 2018,

Jialin Liu, Quincey Koziol, Gregory Butler, Neil Fortner, Mohamad Chaarawi, Houjun Tang, Suren Byna, Glenn Lockwood, Ravi Cheema, Kristy Kallback-Rose, Damian Hazen, Prabhat, "Evaluation of HPC Application I/O on Object Storage Systems", 3rd Joint International Workshop on Parallel Data Storage and Data Intensive Scalable Computing Systems (PDSW-DISCS), November 12, 2018,

Hongzhang Shan, Samuel Williams, Calvin W. Johnson, "Improving MPI Reduction Performance for Manycore Architectures with OpenMP and Data Compression", Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS), November 2018,

Samuel Williams, Introduction to the Roofline Model, Supercomputing, November 2018,

I. Monga, C. Guok, J. MacAuley, A. Sim, H. Newman, J. Balcas, P. DeMar, L. Winkler, T. Lehman, X. Yang, "SDN for End-to-end Networked Science at the Exascale (SENSE)", Innovate the Network for Data-Intensive Science Workshop (INDIS 2018), in conjunction with the International Conference for High Performance Computing, Networking, Storage, and Analysis (SC'18), 2018, doi: 10.1109/INDIS.2018.00007

Anna Giannakou, Daniel Gunter, Sean Peisert, "Flowzilla: A Methodology for Detecting Data Transfer Anomalies in Research Networks", Workshop on Innovating the Network for Data-Intensive Science (INDIS), November 11, 2018, doi: 10.1109/INDIS.2018.00004

Gianina Alina Negoita, James P. Vary, Glenn R. Luecke, Pieter Maris, Andrey M. Shirokov, Ik Jae Shin, Youngman Kim, Esmond G. Ng, Chao Yang, Matthew Lockner, Gurpur M. Prabhu, "Deep Learning: Extrapolation Tool for Ab Initio Nuclear Theory", CoRR, November 10, 2018,

Sean Peisert, Usable Computer Security and Privacy to Enable and Encourage Data Sharing for Scientific Research, National Academies of Sciences, Engineering, and Medicine Committee on Science, Engineering, Medicine, and Public Policy (COSEMPUP) Meeting, November 8, 2018,

K. M. Salerno, D. S. Bolintineanu, G. S. Grest, J. B. Lechman, S. J. Plimpton, I. Srivastava, L. E. Silbert, "Effect of Shape and Friction on the Packing and Flow of Granular Materials", Physical Review E, November 7, 2018, 98:050901(R), doi: 10.1103/PhysRevE.98.050901

Patricia Gonzalez-Guerrero, Xinfei Guo, Mircea Stan, "SC-SD: Towards low power stochastic computing using sigma delta streams", International Conference on Rebooting Computing (ICRC), McLean, VA, USA, IEEE, November 7, 2018, doi: 10.1109/ICRC.2018.8638611

Processing data using Stochastic Computing (SC) requires only ~ 7% of the area and power of the typical binary approach. However, SC has two major drawbacks that eclipse any area and power savings. First, it takes sim 99% more time to finish a computation when compared with the binary approach, since data is represented as streams of bits. Second, the Linear Feedback Shift Registers (LFSRs) required to generate the stochastic streams increment the power and area of the overall SC-LFSR system. These drawbacks result in similar or higher area, power, and energy numbers when compared with the binary counterpart. In this work, we address these drawbacks by applying SC directly on Pulse Density Modulated (PDM) streams. Most modern Systems on Chip (SoCs) already include Analog to Digital Converters (ADCs). The core of Σ△ -ADCs is the Σ△ Modulator whose output is a PDM stream. Our approach (SC-SD) simplifies the system hardware in two ways. First, we drop the filter stage at the ADC and, second, we replace the costly Stochastic Number Generators (SNGs) with Σ△ -Modulators. To further lower the system complexity, we adopt an Asynchronous Σ△ -Modulator (AΣ△M) architecture. We design and simulate the AΣ△M: using an industry-standard 1×FinFET 11 In modern technologies the node number does not refer to any one feature in the process, and foundries use slightly different conventions; we use 1x to denote the 14/16nm FinFET nodes offered by the foundry. technology with foundry models. We achieve power savings of 81 % in SNG compared to the LFSR approach. To evaluate how this area and power savings scale to more complex applications, we implement Gamma Correction, a popular image processing algorithm. For this application, our simulations show that SC-SD can save 98%-11% in the total system latency and 50%-38% in power consumption when compared with the SC-LFSR approach or the binary counterpart.

Cy P Chan, Bin Wang, John D Bachan, Jane Macfarlane, "Mobiliti: Scalable Transportation Simulation Using High-Performance Parallel Computing", 2018 IEEE International Conference on Intelligent Transportation Systems (ITSC), November 6, 2018,

Adrián P. Diéguez, Margarita Amor, Ramón Doallo, "Parallel prefix operations on GPU: tridiagonal system solvers and scan operators", The Journal of Supercomputing, November 2018, 75:1510-1523, doi: 10.1007/s11227-018-2676-z

Hongyuan Zhan, Gabriel Gomes, Xiaoye S Li, Kamesh Madduri, Kesheng Wu, "Efficient Online Hyperparameter Optimization for Kernel Ridge Regression with Applications to Traffic Time Series Prediction", arXiv preprint arXiv:1811.00620, 2018,

Wei Zhang, Houjun Tang, Suren Byna, Yong Chen, "DART: Distributed Adaptive Radix Tree for Efficient Affix-based Keyword Search on HPC Systems", Proceedings of the 27th International Conference on Parallel Architectures and Compilation Techniques, November 1, 2018, 24,

Chris Kavouklis, Phillip Colella, "Computation of volume potentials on structured grids with the method of local corrections", Communications in Applied Mathematics and Computational Science, October 31, 2018, 14:1-32, doi: DOI: 10.2140/camcos.2019.14.1

Cheah You-Wei, Drew Paine, Devarshi Ghoshal, Lavanya Ramakrishnan, Bringing Data Science to Qualitative Analysis, 2018 IEEE 14th International Conference on e-Science, Pages: 325-326 2018, doi: 10.1109/eScience.2018.00076

Mahdi Jamei, Anna Scaglione, Sean Peisert, "Low-Resolution Fault Localization Using Phasor Measurement Units with Community Detection", Proceedings of the 2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm), Allborg, Denmark, IEEE, October 29, 2018, doi: 10.1109/SmartGridComm.2018.8587461

David P. Randall, Drew Paine, Charlotte P. Lee, "Educational Outreach & Stakeholder Role Evolution in a Cyberinfrastructure Project", 2018 IEEE 14th International Conference on e-Science, IEEE Computer Society, 2018, 201-211, doi: 10.1109/eScience.2018.00035

Franz Franchetti, Tze Meng Low, Doru Thom Popovici, Richard Michael Veras, Daniele G. Spampinato, Jeremy R. Johnson, Markus Puschel, James C. Hoe Jose M. F. Moura, "SPIRAL: Extreme Performance Portability", Proceeding of IEEE, 2018,

Cy Chan, Vesselin Drensky, Alan Edelman, Raymond Kan, Plamen Koev, "On Computing Schur Functions and Series Thereof", Journal of Algebraic Combinatorics, October 20, 2018,

Sean Peisert, Ciaran Roberts, Anna Scaglione, Mahdi Jamei, Reinhard Gentz, Charles McParland, Alex McEachren, Galen Rasche, Aaron Snyder, "Supporting Cyber Security of Power Distribution Systems by Detecting Differences Between Real-time Micro-Synchrophasor Measurements and Cyber-Reported SCADA - Final Report", October 15, 2018,

Dan Bonachea, Paul H. Hargrove, "GASNet-EX: A High-Performance, Portable Communication Library for Exascale", Languages and Compilers for Parallel Computing (LCPC'18), Salt Lake City, Utah, USA, October 11, 2018, LBNL 2001174, doi: 10.25344/S4QP4W

Partitioned Global Address Space (PGAS) models, typified by such languages as Unified Parallel C (UPC) and Co-Array Fortran, expose one-sided communication as a key building block for High Performance Computing (HPC) applications. Architectural trends in supercomputing make such programming models increasingly attractive, and newer, more sophisticated models such as UPC++, Legion and Chapel that rely upon similar communication paradigms are gaining popularity.

GASNet-EX is a portable, open-source, high-performance communication library designed to efficiently support the networking requirements of PGAS runtime systems and other alternative models in future exascale machines. The library is an evolution of the popular GASNet communication system, building upon over 15 years of lessons learned. We describe and evaluate several features and enhancements that have been introduced to address the needs of modern client systems. Microbenchmark results demonstrate the RMA performance of GASNet-EX is competitive with several MPI-3 implementations on current HPC systems.

J. Deusch, M. Shao, C. Yang, M. Gu, "A Robust and Efficient Implementation of LOBPCG", SIAM J. Sc. Comput., October 4, 2018, 40:C655–C676, doi: 10.1137/17M1129830

Anastasiia Butko, Albert Chen, David Donofrio, Farzad Fatollahi-Fard, John Shalf, "Open2C: Open-source Generator for Exploration of Coherent Cache Memory Subsystems", MEMSYS '18, New York, NY, USA, ACM, 2018, 311--317, doi: 10.1145/3240302.3270314

George Michelogiannakis, How Open Source Hardware Will Drive the Next Generation of HPC Systems, CROSS Symposium at UCSC, October 2018,

Paul C. Duffell, Eliot Quataert, Daniel Kasen, Hannah Klion, "Jet Dynamics in Compact Object Mergers: GW170817 Likely Had a Successful Jet", Astrophysical Journal, 2018, 866:3, doi: 10.3847/1538-4357/aae084

T. M. Schmidt, J. F. Hennawi, K.-G. Lee, Z. Lukić, J. Oñorbe, M. White, "Mapping quasar light echoes in 3D with Ly alpha forest tomography", The Astrophysical Journal (in review), 2018,

John Bachan, Scott Baden, Dan Bonachea, Paul Hargrove, Steven Hofmeyr, Mathias Jacquelin, Amir Kamil, Brian van Straalen, "UPC++ Programmer's Guide, v1.0-2018.9.0", Lawrence Berkeley National Laboratory Tech Report, September 2018, LBNL 2001180, doi: 10.25344/S49G6V

UPC++ is a C++11 library that provides Partitioned Global Address Space (PGAS) programming. It is designed for writing parallel programs that run efficiently and scale well on distributed-memory parallel computers. The PGAS model is single program, multiple-data (SPMD), with each separate constituent process having access to local memory as it would in C++. However, PGAS also provides access to a global address space, which is allocated in shared segments that are distributed over the processes. UPC++ provides numerous methods for accessing and using global memory. In UPC++, all operations that access remote memory are explicit, which encourages programmers to be aware of the cost of communication and data movement. Moreover, all remote-memory access operations are by default asynchronous, to enable programmers to write code that scales well even on hundreds of thousands of cores.

Shreyas Cholia, Matthew Henderson, Oliver Evans, Fernando Perez, "Kale: A System for Enabling Human-in-the-loop Interactivity in HPC Workflows", Science Gateways 2018, figshare, September 26, 2018, doi: 10.6084/m9.figshare.7067075.v3

John Bachan, Scott Baden, Dan Bonachea, Paul Hargrove, Steven Hofmeyr, Mathias Jacquelin, Amir Kamil, Brian van Straalen, "UPC++ Specification v1.0, Draft 8", Lawrence Berkeley National Laboratory Tech Report, September 26, 2018, LBNL 2001179, doi: 10.25344/S45P4X

UPC++ is a C++11 library providing classes and functions that support Partitioned Global Address Space (PGAS) programming. We are revising the library under the auspices of the DOE’s Exascale Computing Project, to meet the needs of applications requiring PGAS support. UPC++ is intended for implementing elaborate distributed data structures where communication is irregular or fine-grained. The UPC++ interfaces for moving non-contiguous data and handling memories with different optimal access methods are composable and similar to those used in conventional C++. The UPC++ programmer can expect communication to run at close to hardware speeds. The key facilities in UPC++ are global pointers, that enable the programmer to express ownership information for improving locality, one-sided communication, both put/get and RPC, futures and continuations. Futures capture data readiness state, which is useful in making scheduling decisions, and continuations provide for completion handling via callbacks. Together, these enable the programmer to chain together a DAG of operations to execute asynchronously as high-latency dependencies become satisfied.

George Michelogiannakis, John Shalf, Benjamin Aivazi, Yiwen Shen, Keren Bergman, Madeleine Glick, Larry Dennison, Architectural Opportunities and Challenges from Emerging Photonics in Future Systems, IEEE conference on Photonics in Switching and Computing (PSC), September 2018,

George Michelogiannakis, Benjamin Aivazi, Yiwen Shen, Larry Dennison, John Shalf, Keren Bergman, Madeleine Glick, "Architectural Opportunities and Challenges from Emerging Photonics in Future Systems", Photonics in Switching and Computing (PSC), September 2018,

Teng Wang, Suren Byna, Glenn Lockwood, Nicholas Wright, Phil Carns, and Shane Snyder,, "IOMiner: Large-scale Analytics Framework for Gaining Knowledge from I/O Logs", IEEE Cluster 2018, September 10, 2018,

Kimmy Mu, Jerome Soumagne, Houjun Tang, Suren Byna, Quincey Koziol, Richard Warren, "A Server-managed Transparent Object Storage Abstraction for HPC", 2018 IEEE International Conference on Cluster Computing (CLUSTER), September 10, 2018,

Teng Wang, Suren Byna, Bin Dong, and Houjun Tang, "UniviStor: Integrated Hierarchical and Distributed Storage for HPC", IEEE Cluster 2018., September 1, 2018,

Carter KP, Jian J, Pyrch MM, Forbes TZ, Eaton TM, Abergel RJ, De Jong WA, Gibson JK, "Reductive activation of neptunyl and plutonyl oxo species with a hydroxypyridinone chelating ligand", Chemical Communications, August 30, 2018, 54:10698-1070, doi: 10.1039/C8CC05626A

Samuel Williams, Roofline on Manycore and Accelerated Systems, ModSim, August 2018,

Daniel Fortunato, Chris H. Rycroft, Robert Saye, "Efficient operator-coarsening multigrid schemes for local discontinuous Galerkin methods", arXiv:1808.05320, August 16, 2018,

Weijie Zhao, Florin Rusu, Kesheng Wu, Peter Nugent, "Automatic identification and classification of Palomar Transient Factory astrophysical objects in GLADE", International Journal of Computational Science and Engineering, 2018, 16:337--349,

Sean Peisert, Security Concerns of an NRP, Second National Research Platform (NRP) Workshop, August 6, 2018,

Samuel Williams, Parallelism and Performance, MolSSI Summer School, August 2018,

Doru Thom Popovici, Tze Meng Low, Franz Franchetti, "Large Bandwidth-Efficient FFTs on Multicore and Multi-socket Systems", IPDPS, 2018,

M. C. Clement, J. Zhang, C. A. Lewis, C. Yang, Edward F. Valeev, "Optimized Pair Natural Orbitals for the Coupled Cluster Methods", J. Chem. Theory Comput., August 1, 2018, 14:4581–4589, doi: 10.1021/acs.jctc.8b00294

Alireza Khorshidi, Muammar El Khatib, Andrew A Peterson, Amp: The Atomistic Machine-learning Package v0.6.1, August 1, 2018,

Alessio Petrone, David B. Williams-Young, Shichao Sun, F. Stetina, Xiaosong Li, "An Efficient Implementation of Two-Component Relativistic Density Functional Theory with Torque-Free Auxiliary Variables", European Physical Journal B, 2018, 91:169, doi: 10.1140/epjb/e2018-90170-1

Muammar El Khatib, Andrew A Peterson, "Local Chemical Environments In Machine Learning", Gordon Research Conference: Towards Next-Generation Challenges in Computational Chemistry: From Quan- tum Chemistry and Molecular Simulation to Data Discovery and Quantum Computing., July 21, 2018,

"A Holistic Approach to Distribution Grid Intrusion Detection Systems", Ciaran Roberts, Anna Scaglione Sean Peisert,, EnergyCentral, July 18, 2018,

P Collaboration, N Aghanim, Y Akrami, MIR Alves, M Ashdown, J Aumont, C Baccigalupi, M Ballardini, AJ Banday, RB Barreiro, N Bartolo, S Basak, K Benabed, J-P Bernard, M Bersanelli, P Bielewicz, JJ Bock, JR Bond, J Borrill, FR Bouchet, F Boulanger, A Bracco, M Bucher, C Burigana, E Calabrese, J-F Cardoso, J Carron, R-R Chary, HC Chiang, LPL Colombo, C Combet, BP Crill, F Cuttaia, PD Bernardis, GD Zotti, J Delabrouille, J-M Delouis, ED Valentino, C Dickinson, JM Diego, O Doré, M Douspis, A Ducout, X Dupac, G Efstathiou, F Elsner, TA Enßlin, HK Eriksen, Y Fantaye, R Fernandez-Cobos, K Ferrière, F Forastieri, M Frailis, AA Fraisse, E Franceschi, A Frolov, S Galeotta, S Galli, K Ganga, RT Génova-Santos, M Gerbino, T Ghosh, J González-Nuevo, KM Górski, S Gratton, G Green, A Gruppuso, JE Gudmundsson, V Guillet, W Handley, FK Hansen, G Helou, D Herranz, E Hivon, Z Huang, AH Jaffe, WC Jones, E Keihänen, R Keskitalo, K Kiiveri, J Kim, N Krachmalnicoff, M Kunz, H Kurki-Suonio, G Lagache, J-M Lamarre, A Lasenby, M Lattanzi, CR Lawrence, ML Jeune, F Levrier, M Liguori, PB Lilje, V Lindholm, M López-Caniego, PM Lubin, Y-Z Ma, JF Macías-Pérez, G Maggio, D Maino, N Mandolesi, A Mangilli, A Marcos-Caballero, M Maris, PG Martin, E Martínez-González, S Matarrese, N Mauri, JD McEwen, A Melchiorri, A Mennella, M Migliaccio, M-A Miville-Deschênes, D Molinari, A Moneti, L Montier, G Morgante, A Moss, P Natoli, L Pagano, D Paoletti, G Patanchon, F Perrotta, V Pettorino, F Piacentini, L Polastri, G Polenta, J-L Puget, JP Rachen, M Reinecke, M Remazeilles, A Renzi, I Ristorcelli, G Rocha, C Rosset, G Roudier, JA Rubiño-Martín, B Ruiz-Granados, L Salvati, M Sandri, M Savelainen, D Scott, C Sirignano, R Sunyaev, A-S Suur-Uski, JA Tauber, D Tavagnacco, M Tenti, L Toffolatti, M Tomasi, T Trombetti, J Valiviita, BV Tent, P Vielva, F Villa, N Vittorio, BD Wandelt, IK Wehus, A Zacchei, A Zonca, Planck 2018 results. XII. Galactic astrophysics using polarized dust emission, 2018,

P Collaboration, Y Akrami, F Arroja, M Ashdown, J Aumont, C Baccigalupi, M Ballardini, AJ Banday, RB Barreiro, N Bartolo, S Basak, K Benabed, J-P Bernard, M Bersanelli, P Bielewicz, JJ Bock, JR Bond, J Borrill, FR Bouchet, F Boulanger, M Bucher, C Burigana, RC Butler, E Calabrese, J-F Cardoso, J Carron, A Challinor, HC Chiang, LPL Colombo, C Combet, D Contreras, BP Crill, F Cuttaia, PD Bernardis, GD Zotti, J Delabrouille, J-M Delouis, ED Valentino, JM Diego, S Donzelli, O Doré, M Douspis, A Ducout, X Dupac, S Dusini, G Efstathiou, F Elsner, TA Enßlin, HK Eriksen, Y Fantaye, J Fergusson, R Fernandez-Cobos, F Finelli, F Forastieri, M Frailis, E Franceschi, A Frolov, S Galeotta, S Galli, K Ganga, C Gauthier, RT Génova-Santos, M Gerbino, T Ghosh, J González-Nuevo, KM Górski, S Gratton, A Gruppuso, JE Gudmundsson, J Hamann, W Handley, FK Hansen, D Herranz, E Hivon, DC Hooper, Z Huang, AH Jaffe, WC Jones, E Keihänen, R Keskitalo, K Kiiveri, J Kim, TS Kisner, N Krachmalnicoff, M Kunz, H Kurki-Suonio, G Lagache, J-M Lamarre, A Lasenby, M Lattanzi, CR Lawrence, ML Jeune, J Lesgourgues, F Levrier, A Lewis, M Liguori, PB Lilje, V Lindholm, M Lpez-Caniego, PM Lubin, Y-Z Ma, JF Macías-Pérez, G Maggio, D Maino, N Mandolesi, A Mangilli, A Marcos-Caballero, M Maris, PG Martin, E Martínez-González, S Matarrese, N Mauri, JD McEwen, PD Meerburg, PR Meinhold, A Melchiorri, A Mennella, M Migliaccio, S Mitra, M-A Miville-Deschênes, D Molinari, A Moneti, L Montier, G Morgante, A Moss, M Münchmeyer, P Natoli, HU Nørgaard-Nielsen, L Pagano, D Paoletti, B Partridge, G Patanchon, HV Peiris, F Perrotta, V Pettorino, F Piacentini, L Polastri, G Polenta, J-L Puget, JP Rachen, M Reinecke, M Remazeilles, A Renzi, G Rocha, C Rosset, G Roudier, JA Rubiño-Martín, B Ruiz-Granados, L Salvati, M Sandri, M Savelainen, D Scott, EPS Shellard, M Shiraishi, C Sirignano, G Sirri, LD Spencer, R Sunyaev, A-S Suur-Uski, JA Tauber, D Tavagnacco, M Tenti, L Toffolatti, M Tomasi, T Trombetti, J Valiviita, BV Tent, P Vielva, F Villa, N Vittorio, BD Wandelt, IK Wehus, SDM White, A Zacchei, JP Zibin, A Zonca, Planck 2018 results. X. Constraints on inflation, 2018,

P Collaboration, N Aghanim, Y Akrami, M Ashdown, J Aumont, C Baccigalupi, M Ballardini, AJ Banday, RB Barreiro, N Bartolo, S Basak, K Benabed, J-P Bernard, M Bersanelli, P Bielewicz, JJ Bock, JR Bond, J Borrill, FR Bouchet, F Boulanger, M Bucher, C Burigana, E Calabrese, J-F Cardoso, J Carron, A Challinor, HC Chiang, LPL Colombo, C Combet, BP Crill, F Cuttaia, PD Bernardis, GD Zotti, J Delabrouille, ED Valentino, JM Diego, O Doré, M Douspis, A Ducout, X Dupac, G Efstathiou, F Elsner, TA Enßlin, HK Eriksen, Y Fantaye, R Fernandez-Cobos, F Forastieri, M Frailis, AA Fraisse, E Franceschi, A Frolov, S Galeotta, S Galli, K Ganga, RT Génova-Santos, M Gerbino, T Ghosh, J González-Nuevo, KM Górski, S Gratton, A Gruppuso, JE Gudmundsson, J Hamann, W Handley, FK Hansen, D Herranz, E Hivon, Z Huang, AH Jaffe, WC Jones, A Karakci, E Keihänen, R Keskitalo, K Kiiveri, J Kim, L Knox, N Krachmalnicoff, M Kunz, H Kurki-Suonio, G Lagache, J-M Lamarre, A Lasenby, M Lattanzi, CR Lawrence, ML Jeune, F Levrier, A Lewis, M Liguori, PB Lilje, V Lindholm, M López-Caniego, PM Lubin, Y-Z Ma, JF Macías-Pérez, G Maggio, D Maino, N Mandolesi, A Mangilli, A Marcos-Caballero, M Maris, PG Martin, E Martínez-González, S Matarrese, N Mauri, JD McEwen, A Melchiorri, A Mennella, M Migliaccio, M-A Miville-Deschênes, D Molinari, A Moneti, L Montier, G Morgante, A Moss, P Natoli, L Pagano, D Paoletti, B Partridge, G Patanchon, F Perrotta, V Pettorino, F Piacentini, L Polastri, G Polenta, J-L Puget, JP Rachen, M Reinecke, M Remazeilles, A Renzi, G Rocha, C Rosset, G Roudier, JA Rubiño-Martín, B Ruiz-Granados, L Salvati, M Sandri, M Savelainen, D Scott, C Sirignano, R Sunyaev, A-S Suur-Uski, JA Tauber, D Tavagnacco, M Tenti, L Toffolatti, M Tomasi, T Trombetti, J Valiviita, BV Tent, P Vielva, F Villa, N Vittorio, BD Wandelt, IK Wehus, M White, SDM White, A Zacchei, A Zonca, Planck 2018 results. VIII. Gravitational lensing, 2018,

P Collaboration, N Aghanim, Y Akrami, M Ashdown, J Aumont, C Baccigalupi, M Ballardini, AJ Banday, RB Barreiro, N Bartolo, S Basak, R Battye, K Benabed, J-P Bernard, M Bersanelli, P Bielewicz, JJ Bock, JR Bond, J Borrill, FR Bouchet, F Boulanger, M Bucher, C Burigana, RC Butler, E Calabrese, J-F Cardoso, J Carron, A Challinor, HC Chiang, J Chluba, LPL Colombo, C Combet, D Contreras, BP Crill, F Cuttaia, PD Bernardis, GD Zotti, J Delabrouille, J-M Delouis, ED Valentino, JM Diego, O Doré, M Douspis, A Ducout, X Dupac, S Dusini, G Efstathiou, F Elsner, TA Enßlin, HK Eriksen, Y Fantaye, M Farhang, J Fergusson, R Fernandez-Cobos, F Finelli, F Forastieri, M Frailis, E Franceschi, A Frolov, S Galeotta, S Galli, K Ganga, RT Génova-Santos, M Gerbino, T Ghosh, J González-Nuevo, KM Górski, S Gratton, A Gruppuso, JE Gudmundsson, J Hamann, W Handley, D Herranz, E Hivon, Z Huang, AH Jaffe, WC Jones, A Karakci, E Keihänen, R Keskitalo, K Kiiveri, J Kim, TS Kisner, L Knox, N Krachmalnicoff, M Kunz, H Kurki-Suonio, G Lagache, J-M Lamarre, A Lasenby, M Lattanzi, CR Lawrence, ML Jeune, P Lemos, J Lesgourgues, F Levrier, A Lewis, M Liguori, PB Lilje, M Lilley, V Lindholm, M López-Caniego, PM Lubin, Y-Z Ma, JF Macías-Pérez, G Maggio, D Maino, N Mandolesi, A Mangilli, A Marcos-Caballero, M Maris, PG Martin, M Martinelli, E Martínez-González, S Matarrese, N Mauri, JD McEwen, PR Meinhold, A Melchiorri, A Mennella, M Migliaccio, M Millea, S Mitra, M-A Miville-Deschênes, D Molinari, L Montier, G Morgante, A Moss, P Natoli, HU Nørgaard-Nielsen, L Pagano, D Paoletti, B Partridge, G Patanchon, HV Peiris, F Perrotta, V Pettorino, F Piacentini, L Polastri, G Polenta, J-L Puget, JP Rachen, M Reinecke, M Remazeilles, A Renzi, G Rocha, C Rosset, G Roudier, JA Rubiño-Martín, B Ruiz-Granados, L Salvati, M Sandri, M Savelainen, D Scott, EPS Shellard, C Sirignano, G Sirri, LD Spencer, R Sunyaev, A-S Suur-Uski, JA Tauber, D Tavagnacco, M Tenti, L Toffolatti, M Tomasi, T Trombetti, L Valenziano, J Valiviita, BV Tent, L Vibert, P Vielva, F Villa, N Vittorio, BD Wandelt, IK Wehus, M White, SDM White, A Zacchei, A Zonca, Planck 2018 results. VI. Cosmological parameters, 2018,

P Collaboration, N Aghanim, Y Akrami, M Ashdown, J Aumont, C Baccigalupi, M Ballardini, AJ Banday, RB Barreiro, N Bartolo, S Basak, K Benabed, J-P Bernard, M Bersanelli, P Bielewicz, JR Bond, J Borrill, FR Bouchet, F Boulanger, M Bucher, C Burigana, E Calabrese, J-F Cardoso, J Carron, A Challinor, HC Chiang, LPL Colombo, C Combet, F Couchot, BP Crill, F Cuttaia, PD Bernardis, AD Rosa, GD Zotti, J Delabrouille, J-M Delouis, ED Valentino, JM Diego, O Doré, M Douspis, A Ducout, X Dupac, G Efstathiou, F Elsner, TA Enßlin, HK Eriksen, E Falgarone, Y Fantaye, F Finelli, M Frailis, AA Fraisse, E Franceschi, A Frolov, S Galeotta, S Galli, K Ganga, RT Génova-Santos, M Gerbino, T Ghosh, J González-Nuevo, KM Górski, S Gratton, A Gruppuso, JE Gudmundsson, W Handley, FK Hansen, S Henrot-Versillé, D Herranz, E Hivon, Z Huang, AH Jaffe, WC Jones, A Karakci, E Keihänen, R Keskitalo, K Kiiveri, J Kim, TS Kisner, N Krachmalnicoff, M Kunz, H Kurki-Suonio, G Lagache, J-M Lamarre, A Lasenby, M Lattanzi, CR Lawrence, F Levrier, M Liguori, PB Lilje, V Lindholm, M López-Caniego, Y-Z Ma, JF Macías-Pérez, G Maggio, D Maino, N Mandolesi, A Mangilli, PG Martin, E Martínez-González, S Matarrese, N Mauri, JD McEwen, A Melchiorri, A Mennella, M Migliaccio, M-A Miville-Deschênes, D Molinari, A Moneti, L Montier, G Morgante, A Moss, S Mottet, P Natoli, L Pagano, D Paoletti, B Partridge, G Patanchon, L Patrizii, O Perdereau, F Perrotta, V Pettorino, F Piacentini, J-L Puget, JP Rachen, M Reinecke, M Remazeilles, A Renzi, G Rocha, G Roudier, L Salvati, M Sandri, M Savelainen, D Scott, C Sirignano, G Sirri, LD Spencer, R Sunyaev, A-S Suur-Uski, JA Tauber, D Tavagnacco, M Tenti, L Toffolatti, M Tomasi, M Tristram, T Trombetti, J Valiviita, F Vansyngel, BV Tent, L Vibert, P Vielva, F Villa, N Vittorio, BD Wandelt, IK Wehus, A Zonca, Planck 2018 results. III. High Frequency Instrument data processing and frequency maps, 2018,

P Collaboration, Y Akrami, F Arroja, M Ashdown, J Aumont, C Baccigalupi, M Ballardini, AJ Banday, RB Barreiro, N Bartolo, S Basak, R Battye, K Benabed, J-P Bernard, M Bersanelli, P Bielewicz, JJ Bock, JR Bond, J Borrill, FR Bouchet, F Boulanger, M Bucher, C Burigana, RC Butler, E Calabrese, J-F Cardoso, J Carron, B Casaponsa, A Challinor, HC Chiang, LPL Colombo, C Combet, D Contreras, BP Crill, F Cuttaia, PD Bernardis, GD Zotti, J Delabrouille, J-M Delouis, F-X Désert, ED Valentino, C Dickinson, JM Diego, S Donzelli, O Doré, M Douspis, A Ducout, X Dupac, G Efstathiou, F Elsner, TA Enßlin, HK Eriksen, E Falgarone, Y Fantaye, J Fergusson, R Fernandez-Cobos, F Finelli, F Forastieri, M Frailis, E Franceschi, A Frolov, S Galeotta, S Galli, K Ganga, RT Génova-Santos, M Gerbino, T Ghosh, J González-Nuevo, KM Górski, S Gratton, A Gruppuso, JE Gudmundsson, J Hamann, W Handley, FK Hansen, G Helou, D Herranz, E Hivon, Z Huang, AH Jaffe, WC Jones, A Karakci, E Keihänen, R Keskitalo, K Kiiveri, J Kim, TS Kisner, L Knox, N Krachmalnicoff, M Kunz, H Kurki-Suonio, G Lagache, J-M Lamarre, M Langer, A Lasenby, M Lattanzi, CR Lawrence, ML Jeune, JP Leahy, J Lesgourgues, F Levrier, A Lewis, M Liguori, PB Lilje, M Lilley, V Lindholm, M López-Caniego, PM Lubin, Y-Z Ma, JF Macías-Pérez, G Maggio, D Maino, N Mandolesi, A Mangilli, A Marcos-Caballero, M Maris, PG Martin, E Martínez-González, S Matarrese, N Mauri, JD McEwen, PD Meerburg, PR Meinhold, A Melchiorri, A Mennella, M Migliaccio, M Millea, S Mitra, M-A Miville-Deschênes, D Molinari, A Moneti, L Montier, G Morgante, A Moss, S Mottet, M Münchmeyer, P Natoli, HU Nørgaard-Nielsen, CA Oxborrow, L Pagano, D Paoletti, B Partridge, G Patanchon, TJ Pearson, M Peel, HV Peiris, F Perrotta, V Pettorino, F Piacentini, L Polastri, G Polenta, J-L Puget, JP Rachen, M Reinecke, M Remazeilles, A Renzi, G Rocha, C Rosset, G Roudier, JA Rubiño-Martín, B Ruiz-Granados, L Salvati, M Sandri, M Savelainen, D Scott, EPS Shellard, M Shiraishi, C Sirignano, G Sirri, LD Spencer, R Sunyaev, A-S Suur-Uski, JA Tauber, D Tavagnacco, M Tenti, L Terenzi, L Toffolatti, M Tomasi, T Trombetti, J Valiviita, BV Tent, L Vibert, P Vielva, F Villa, N Vittorio, BD Wandelt, IK Wehus, M White, SDM White, A Zacchei, A Zonca, Planck 2018 results. I. Overview and the cosmological legacy of Planck, 2018,

Khaled Ibrahim, Samuel Williams, Leonid Oliker, "Roofline Scaling Trajectories: A Method for Parallel Application and Architectural Performance Analysis", HPCS Special Session on High Performance Computing Benchmarking and Optimization (HPBench), July 2018,

Jürg Hutter, Jan Wilhelm, Vladimir V Rybkin, Mauro Del Ben, Joost VandeVondele, "MP2-and RPA-Based Ab Initio Molecular Dynamics and Monte Carlo Sampling", Handbook of Materials Modeling: Methods: Theory and Modeling, ( 2018) doi: 10.1007/978-3-319-42913-7_58-1

R. Huang, J. Sun, C. Yang, "Recursive integral method with Cayley transformation", Numerical Linear Algebra with Applications, July 10, 2018, 25:1-12, doi: 10.1002/nla.2199

J. M. D. Lane, K. M. Salerno, I. Srivastava, G. S. Grest, H. Fan, "Modeling Pressure-Driven Assembly of Polymer Coated Nanoparticles", Shock Compression of Condensed Matter - 2017, July 3, 2018, 1979:090007, doi: 10.1063/1.5044864

J. Kim, J. Choi, A. Sim, "Spatio-temporal Analysis of HPC I/O and Connection Data", International Workshop on Scalable Network Traffic Analytics (SNTA 2018), 2018, in conjunction with the 38th IEEE International Conference on Distributed Computing Systems (ICDCS 2018), 2018, doi: 10.1109/icdcs.2018.00176

Weijie Zhao, Florin Rusu, Bin Dong, Kesheng Wu, Anna YQ Ho, Peter Nugent, "Distributed Caching for Complex Querying of Raw Arrays", SSDBM, 2018,

AP Arkin,RW Cottingham,CS Henry,NL Harris,RL Stevens,S Maslov,P Dehal,D Ware,F Perez,S Canon,MW Sneddon,ML Henderson,WJ Riehl,D Murphy-Olson,SY Chan,RT Kamimura,S Kumari,MM Drake,TS Brettin,EM Glass,D Chivian,D Gunter,DJ Weston,BH Allen,J Baumohl,AA Best,B Bowen,SE Brenner,CC Bun,JM Chandonia,JM Chia,R Colasanti,N Conrad,JJ Davis,BH Davison,M Dejongh,S Devoid,E Dietrich,I Dubchak,JN Edirisinghe,G Fang,JP Faria,PM Frybarger,W Gerlach,M Gerstein,A Greiner,J Gurtowski,HL Haun,F He,R Jain,MP Joachimiak,KP Keegan,S Kondo,V Kumar,ML Land,F Meyer,M Mills,PS Novichkov,T Oh,GJ Olsen,R Olson,B Parrello,S Pasternak,E Pearson,SS Poon,GA Price,S Ramakrishnan,P Ranjan,PC Ronald,MC Schatz,SMD Seaver,M Shukla,RA Sutormin,MH Syed,J Thomason,NL Tintle,D Wang,F Xia,H Yoo,S Yoo,D Yu, "KBase: The United States department of energy systems biology knowledgebase", Nature Biotechnology, July 2018, 36:566--569, doi: 10.1038/nbt.4163

S. Farrell, A. Vose, O. Evans, M. Henderson, S. Cholia, W. Bhimji, R. Thomas, S.
Canon, and Prabhat,,
"Interactive Distributed Deep Learning with Jupyter Notebooks", ISC Workshop on Interactive High-Performance Computing, June 28, 2018,

Sean Peisert, Cyber Security Challenges and Opportunities in High-Performance Computing Environments, International Supercomputing Conference, June 26, 2018,

Tuomas Koskela, Zakhar Matveev, Charlene Yang, Adetokunbo Adedoyin, Roman Belenov, Philippe Thierry, Zhengji Zhao, Rahulkumar Gayatri, Hongzhang Shan, Leonid Oliker, Jack Deslippe, Ron Green, and Samuel Williams, "A Novel Multi-Level Integrated Roofline Model Approach for Performance Characterization", ISC, June 2018,

Joseph P. Kenny, Khachik Sargsyan, Samuel Knight, George Michelogiannakis, Jeremiah J. Wilke, "The Pitfalls of Provisioning Exascale Networks: A Trace Replay Analysis for Understanding Communication Performance", ISC High Performance 2018, June 2018, 10876,

W. Hu, M. Shao, A. Cepelloti, F. H. Jornada, L. Lin, K. Thicke, C. Yang, S. Louie, "Accelerating Optical Absorption Spectra and Exciton Energy Computation via Interpolative Separable Density Fitting", International Conference on Computational Science (ICCS2018), Lecture Notes in Computer Science, Springer, Cham, June 12, 2018, 10861:604-617, doi: 10.1007/978-3-319-93701-4_48

Keren Bergman, John Shalf, George Michelogiannakis, Sebastien Rumley, Larry Dennison, Monia Ghobadi, "PINE: An Energy Efficient Flexibly Interconnected Photonic Data Center Architecture for Extreme Scalability", 31st annual conference of the IEEE Photonics Society, IEEE, June 2018,

E. O. Zavarygin, J. K. Webb, S. Riemer-Sørensen, V. Dumont, "Primordial deuterium abundance at z=2.504 towards Q1009+2956", Journal of Physics: Conference Series, Volume 1038, International Conference PhysicA.SPb/2017 24–26 October 2017, Saint-Petersburg, Russian Federation, June 1, 2018, doi: 10.1088/1742-6596/1038/1/012012

Charlene Yang, Brian Friesen, Thorsten Kurth, Brandon Cook, Samuel Williams, "Toward Automated Application Profiling on Cray Systems", Cray User Group (CUG), May 2018,

Adrián P. Diéguez, Margarita Amor, Ramón Doallo, Akira Nukada, Satoshi Matsuoka, "Efficient Solving of Scan Primitive on Multi-GPU Systems", IEEE International Parallel and Distributed Processing Symposium (IPDPS), Vancouver, Canada, IEEE, May 21, 2018, 794-803, doi: 10.1109/IPDPS.2018.00089

D. Jones, J. Bopaiah, F. Alghamedy, M. Jacobs, H.L. Weiss, W.A. de Jong, S.R. Ellingson, "Polypharmacology Within the Full Kinome: a Machine Learning Approach", AMIA Jt Summits Transl Sci Proc, May 18, 2018, 2017:98-107,

Daniel R. Ladiges, John E. Sader, "Variational method enabling simplified solutions to the linearized Boltzmann equation for oscillatory gas flows", Physical Review Fluids, May 16, 2018, 3:053401,

Hannah E. Ross, Keri L. Dixon, Ilian T. Iliev, Garrelt Mellema, "New simulation of QSO X-ray heating during the Cosmic Dawn", Peering towards Cosmic Dawn, Proceedings of the International Astronomical Union, IAU Symposium, May 8, 2018, 333:34-38,

Houjun Tang, Suren Byna, Francois Tessier, Teng Wang, Bin Dong, Jingqing Mu, Quincey Koziol, Jerome Soumagne, Venkatram Vishwanath, Jialin Liu, and Richard Warren, "Toward Scalable and Asynchronous Object-centric Data Management for HPC", 18th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid) 2018, May 1, 2018,

F Alali, N Hanford, E Pouyoul, R Kettimuthu, M Kiran, B Mack-Crane, B Tierney, Y Kumar, D Ghosal, "Calibers: A bandwidth calendaring paradigm for science workflows", Future Generation Computer Systems, 2018, 89:736--745, doi: 10.1016/j.future.2018.07.030

G Conti, S Nemšák, C-T Kuo, M Gehlmann, C Conlon, A Keqi, A Rattanachata, O Karslıoğlu, J Mueller, J Sethian, H Bluhm, JE Rault, JP Rueff, H Fang, A Javey, CS Fadley, "Characterization of free-standing InAs quantum membranes by standing wave hard x-ray photoemission spectroscopy", APL Materials, May 1, 2018,

Nan Ding, Shiming Xu, Zhenya Song, Baoquan Zhang, Jingmei Li, Zhigao Zheng, "Using Hardware Counters-based Performance Model to Diagnose Scaling Issues of HPC Applications", NCAA'18, April 25, 2018,

T. Ke, A. S. Brewster, S. X. Yu, D. Ushizima, C. Yang, N. K. Sauter, "A convolutional neural network-based screening tool for X-ray serial crystallography", JOURNAL OF SYNCHROTRON RADIATION, April 24, 2018, 25:665-670, doi: 10.1107/S1600577518004873

Meiyue Shao, Felipe H. da Jornada, Lin Lin, Chao Yang, Jack Deslippe, Steven G. Louie, "A structure preserving Lanczos algorithm for computing the optical absorption spectrum", SIAM Journal on Matrix Analysis and Applications, 2018, 39:683--711, doi: 10.1137/16M1102641

E. O. Zavarygin, J. K. Webb, V. Dumont, S. Riemer-Sørensen, "The primordial deuterium abundance at z=2.504 from a high signal-to-noise spectrum of Q1009+2956", Monthly Notices of the Royal Astronomical Society, Volume 477, Issue 4, Pages 5536–5553, April 21, 2018, doi: 10.1093/mnras/sty1003

Haoyuan Xing, Sofoklis Floratos, Spyros Blanas, Suren Byna, Prabhat, Kesheng Wu, and Paul Brown,, "ArrayBridge: Interweaving declarative array processing with imperative high-performance computing", 34th IEEE International Conference on Data Engineering (ICDE) 2018, April 17, 2018,

Bharti Wadhwa, Suren Byna, Ali R. Butt, "Toward Transparent Data Management in Multi-layer Storage Hierarchy for HPC Systems", IEEE International Conference on Cloud Engineering 2018 (IC2E 2018), April 17, 2018,

Haoyuan Xing, Sofoklis Floratos, Spyros Blanas, Suren Byna, M Prabhat, Kesheng Wu, Paul Brown, "ArrayBridge: Interweaving declarative array processing in SciDB with imperative HDF5-based programs", 2018 IEEE 34th International Conference on Data Engineering (ICDE), 2018, 977--988,

A. S. Banerjee, L. Lin, P. Suryanarayana, C. Yang, J. E. Pask, "Two-level Chebyshev filter based complementary subspace method for pushing the envelope of large-scale electronic structure calculations", J. Chem. Theory Comput., April 16, 2018, 14:2930–2946, doi: 10.1021/acs.jctc.7b01243

K. E. Bouchard, J.B. Aimone, M. Chun, T. Dean, M. Denker, M. Diesmann, D. Donofrio, L.M. Frank, N. Kasthuri, C. Koch, O. Rübel, H. Simon, F. T. Sommer, Prabhat, "International Neuroscience Initiatives Through the Lens of High-Performance Computing", IEEE Computer, April 12, 2018, 51(4):50-59, doi: doi 10.1109/MC.2018.2141039

Dan Martin, Ice sheet model-dependence of persistent ice-cliff formation, European Geosciences Union General Assembly 2018, April 11, 2018,

Ariful Azad, Georgios A. Pavlopoulos, Christos A. Ouzounis, Nikos C. Kyrpides, Aydin Buluç, "HipMCL: A high-performance parallel implementation of the Markov cluster algorithm for large scale networks", Nucleic Acids Research, April 2018,

Saliya Ekanayake, "MIDAS", April 1, 2018,

Kadir Akbudak, R. Oguz Selvitopi, Cevdet Aykanat, "Partitioning Models for Scaling Parallel Sparse Matrix-Matrix Multiplication", ACM Transactions on Parallel Computing (TOPC), April 2018, 4, 3, doi: 10.1145/3155292

Sean Peisert, Keynote: Cybersecurity for HPC Systems: State of the Art and Looking to the Future, High-Performance Computing Security Workshop, National Institute of Standards and Technology (NIST), March 28, 2018,

Dan Bonachea, Paul Hargrove, "GASNet-EX Performance Improvements Due to Specialization for the Cray Aries Network (tech report version)", Lawrence Berkeley National Laboratory Tech Report, March 27, 2018, LBNL 2001134, doi: 10.2172/1430690

This document is a deliverable for milestone STPM17-6 of the Exascale Computing Project, delivered by WBS 2.3.1.14. It reports on the improvements in performance observed on Cray XC-series systems due to enhancements made to the GASNet-EX software. These enhancements, known as “specializations”, primarily consist of replacing network-independent implementations of several recently added features with implementations tailored to the Cray Aries network. Performance gains from specialization include (1) Negotiated-Payload Active Messages improve bandwidth of a ping-pong test by up to 14%, (2) Immediate Operations reduce running time of a synthetic benchmark by up to 93%, (3) non-bulk RMA Put bandwidth is increased by up to 32%, (4) Remote Atomic performance is 70% faster than the reference on a point-to-point test and allows a hot-spot test to scale robustly, and (5) non-contiguous RMA interfaces see up to 8.6x speedups for an intra-node benchmark and 26% for inter-node. These improvements are available in the GASNet-EX 2018.3.0 release.

John Bachan, Scott Baden, Dan Bonachea, Paul H. Hargrove, Steven Hofmeyr, Khaled Ibrahim, Mathias Jacquelin, Amir Kamil, Bryce Lelbach, Brian Van Straalen, "UPC++ Specification v1.0, Draft 6", Lawrence Berkeley National Laboratory Tech Report, March 26, 2018, LBNL 2001135, doi: 10.2172/1430689

UPC++ is a C++11 library providing classes and functions that support Partitioned Global Address Space (PGAS) programming. We are revising the library under the auspices of the DOE’s Exascale Computing Project, to meet the needs of applications requiring PGAS support. UPC++ is intended for implementing elaborate distributed data structures where communication is irregular or fine-grained. The UPC++ interfaces for moving non-contiguous data and handling memories with different optimal access methods are composable and similar to those used in conventional C++. The UPC++ programmer can expect communication to run at close to hardware speeds. The key facilities in UPC++ are global pointers, that enable the programmer to express ownership information for improving locality, one-sided communication, both put/get and RPC, futures and continuations. Futures capture data readiness state, which is useful in making scheduling decisions, and continuations provide for completion handling via callbacks. Together, these enable the programmer to chain together a DAG of operations to execute asynchronously as high-latency dependencies become satisfied.

John Bachan, Scott Baden, Dan Bonachea, Paul H. Hargrove, Steven Hofmeyr, Khaled Ibrahim, Mathias Jacquelin, Amir Kamil, Brian Van Straalen, "UPC++ Programmer’s Guide, v1.0-2018.3.0", Lawrence Berkeley National Laboratory Tech Report, March 2018, LBNL 2001136, doi: 10.2172/1430693

UPC++ is a C++11 library that provides Partitioned Global Address Space (PGAS) programming. It is designed for writing parallel programs that run efficiently and scale well on distributed-memory parallel computers. The PGAS model is single program, multiple-data (SPMD), with each separate thread of execution (referred to as a rank, a term borrowed from MPI) having access to local memory as it would in C++. However, PGAS also provides access to a global address space, which is allocated in shared segments that are distributed over the ranks. UPC++ provides numerous methods for accessing and using global memory. In UPC++, all operations that access remote memory are explicit, which encourages programmers to be aware of the cost of communication and data movement. Moreover, all remote-memory access operations are by default asynchronous, to enable programmers to write code that scales well even on hundreds of thousands of cores.

Adrián P. Diéguez, Margarita Amor, Ramón Doallo, "Solving Multiple Tridiagonal Systems on a Multi-GPU Platform", 2018 26th Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP), Cambridge, United Kingdom, IEEE, March 2018, 759-763, doi: 10.1109/PDP2018.2018.00123

M. Ferroni, JA Colmenares, S Hofmeyr, JD Kubiatowicz, MD Santambrogio, "Enabling power-awareness for the Xen Hypervisor", ACM SIGBED Review, March 20, 2018, 1:36-42,

J. M. Kasper, D. B. Williams-Young, E. Vecharynski, C. Yang, X. Li, "A Well-Tempered Hybrid Method for Solving Challenging Time-Dependent Density Functional Theory (TDDFT) Systems", J. Chem. Theory Comput., March 16, 2018, 14:2034–2041, doi: 10.1021/acs.jctc.8b00141

Blake Barker, Rose Nguyen, Björn Sandsted, Nathaniel Ventura, Colin Wahl, "Computing Evans functions numerically via boundary-value problems", Physica D: Nonlinear Phenomena, March 15, 2018, 367:1-10, doi: https://doi.org/10.1016/j.physd.2017.12.002

Xinfei Guo, Vaibhav Verma, Patricia Gonzalez-Guerrero, Mircea R Stan, "When “things” get older: exploring circuit aging in IoT applications", International Symposium on Quality Electronic Design (ISQED), Santa Clara, CA, USA, IEEE, March 13, 2018, doi: 10.1109/ISQED.2018.8357304

The Internet of Things (IoT) brings a paradigm where humans and “things” are connected. Reliability of these devices becomes extremely critical. Circuit aging has become a limiting factor in technology scaling and a significant challenge in designing IoT systems for reliability-critical applications. As IoT becomes a general-purpose technology which starts to adapt to the advanced process nodes, it is necessary to understand how and on what level aging affects different categories of IoT applications. Since aging is highly dependent on operating conditions and switching activities, this paper classifies the IoT applications based on the aging-related metrics and studies aging using the foundry-provided FinFET aging models. We show that for many IoT applications, aging will indeed add to the already tight design margin. As the expected chip lifetime in IoT devices becomes much longer and the failure tolerant requirements of these applications become much more strict, we conclude that aging needs to be considered in the full design cycle and the IoT lifetime estimation needs to incorporate aging as an important factor. We also present application-specific solutions to mitigate circuit aging in IoT systems.

Devarshi Ghoshal, "Deduce: Managing Data Change Pipelines", Conference on Data Analysis (CoDA 2018), 2018,

Sean Peisert, Eli Dart, William K. Barnett, James Cuff, Robert L. Grossman, Edward Balas, Ari Berman, Anurag Shankar, Brian Tierney, "The Medical Science DMZ: An Network Design Pattern for Data-Intensive Medical Science", Journal of the American Medical Informatics Association (JAMIA), March 2018, 25(3):267-274, doi: 10.1093/jamia/ocx104

Tuowen Zhao, Mary Hall, Protonu Basu, Samuel Williams, Hans Johansen, "SIMD code generation for stencils on brick decompositions", Proceedings of the 23rd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP), February 2018,

Bin Wang, John D Bachan, Cy P Chan, "ExaGridPF: A parallel power flow solver for transmission and unbalanced distribution systems", 2018 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT), February 22, 2018,

M. S. Waibel, C. L. Hulbe, C. S. Jackson, D. F. Martin, "Rate of Mass Loss Across the Instability Threshold for Thwaites Glacier Determines Rate of Mass Loss for Entire Basin", Geophysical Research Letters, February 19, 2018, 45:809-816, doi: 10.1002/2017GL076470

Daniel F Martin, Xylar Asay-Davis, Jan De Rydt,, "Sensitivity of Ice-Ocean coupling to interactions with subglacial hydrology", AGU 2018 Ocean Sciences Meeting,, February 14, 2018,

Samuel Williams, Introduction to the Roofline Model, ECP Annual Meeting, February 8, 2018,

Jack Deslippe, Guiding Optimization on KNL with the Roofline Model, ECP Annual Meeting, February 8, 2018,

Charlene Yang, LIKWID at NERSC, ECP Annual Meeting, February 8, 2018,

Protonu Basu, Using Empirical Roofline Toolkit and Nvidia nvprof, ECP Annual Meeting, February 8, 2018,

Charlene Yang, Intel Advisor on Cori, ECP Annual Meeting, February 8, 2018,

Samuel Williams, Advisor Hand-On: Stencil Example, ECP Annual Meeting, February 8, 2018,

Sean Peisert, Ciaran Roberts, Cyber Security of Power Distribution Systems Using Micro-Synchrophasor Measurements and Cyber-Reported SCADA, EPRI Power Delivery & Utilization Winter 2018 Program Advisory & Sector Council Meeting, February 7, 2018,

John Bachan, Scott Baden, Dan Bonachea, Paul Hargrove, Steven Hofmeyr, Khaled Ibrahim, Mathias Jacquelin, Amir Kamil, Brian van Straalen, "UPC++ and GASNet: PGAS Support for Exascale Apps and Runtimes (ECP'18)", Poster at Exascale Computing Project (ECP) Annual Meeting 2018, February 2018,

Scott Baden, Dan Bonachea, Paul Hargrove, "GASNet-EX: PGAS Support for Exascale Apps and Runtimes (ECP'18)", Poster at Exascale Computing Project (ECP) Annual Meeting 2018, February 2018,

M. Papadopoulos, R. Van Beeumen, S. François, G. Degrande, G. Lombaert, "Modal characteristics of structures considering dynamic soil-structure interaction effects", Soil Dynamics and Earthquake Engineering, 2018, 105:114-118, doi: 10.1016/j.soildyn.2017.11.012

Nan Ding, WeiXue, Zhenya Song, Haohuan Fub, Shiming Xu, WeiminZhenga, "An automatic performance model-based scheduling tool for coupled climate system models", JPDC, January 31, 2018,

Samuel Williams, Performance Modeling and Analysis, CS267 lecture, University of California at Berkeley, January 30, 2018,

A Bennaceur, A Cano, L Georgieva, M Kiran, M Salama, P Yadav, "Issues in gender diversity and equality in the UK", Proceedings - International Conference on Software Engineering, 2018, 5--9, doi: 10.1145/3195570.3195571

George Michelogiannakis, Open-Source Hardware in the Post Moore Era, NovelHPC: Beyond Exascale: Workshop on Novel HPC Architectures (HiPEAC 2018), January 2018,

George Michelogiannakis, An Architect’s Point of View of the Post Moore Era, 3rd International Workshop on Advanced Interconnect Solutions and Technologies for Emerging Computing Systems (AISTECS with HiPEAC 2018), January 2018,

B Mohammed, B Modu, KM Maiyama, H Ugail, I Awan, M Kiran, "Failure Analysis Modelling in an Infrastructure as a Service (Iaas) Environment", Electronic Notes in Theoretical Computer Science, 2018, 340:41--54, doi: 10.1016/j.entcs.2018.09.004

Yu-Hang Tang, Dongkun Zhang, George Em Karniadakis, "An atomistic fingerprint algorithm for learning ab initio molecular force fields", Journal of Chemical Physics, 2018, 148,

P Collaboration, Y Akrami, M Ashdown, J Aumont, C Baccigalupi, M Ballardini, AJ Banday, RB Barreiro, N Bartolo, S Basak, K Benabed, J-P Bernard, M Bersanelli, P Bielewicz, JR Bond, J Borrill, FR Bouchet, F Boulanger, A Bracco, M Bucher, C Burigana, E Calabrese, J-F Cardoso, J Carron, HC Chiang, C Combet, BP Crill, PD Bernardis, GD Zotti, J Delabrouille, J-M Delouis, ED Valentino, C Dickinson, JM Diego, A Ducout, X Dupac, G Efstathiou, F Elsner, TA Enßlin, E Falgarone, Y Fantaye, K Ferrière, F Finelli, F Forastieri, M Frailis, AA Fraisse, E Franceschi, A Frolov, S Galeotta, S Galli, K Ganga, RT Génova-Santos, T Ghosh, J González-Nuevo, KM Górski, A Gruppuso, JE Gudmundsson, V Guillet, W Handley, FK Hansen, D Herranz, Z Huang, AH Jaffe, WC Jones, E Keihänen, R Keskitalo, K Kiiveri, J Kim, N Krachmalnicoff, M Kunz, H Kurki-Suonio, J-M Lamarre, A Lasenby, ML Jeune, F Levrier, M Liguori, PB Lilje, V Lindholm, M López-Caniego, PM Lubin, Y-Z Ma, JF Macías-Pérez, G Maggio, D Maino, N Mandolesi, A Mangilli, PG Martin, E Martínez-González, S Matarrese, JD McEwen, PR Meinhold, A Melchiorri, M Migliaccio, M-A Miville-Deschênes, D Molinari, A Moneti, L Montier, G Morgante, P Natoli, L Pagano, D Paoletti, V Pettorino, F Piacentini, G Polenta, J-L Puget, JP Rachen, M Reinecke, M Remazeilles, A Renzi, G Rocha, C Rosset, G Roudier, JA Rubiño-Martín, B Ruiz-Granados, L Salvati, M Sandri, M Savelainen, D Scott, JD Soler, LD Spencer, JA Tauber, D Tavagnacco, L Toffolatti, M Tomasi, T Trombetti, J Valiviita, F Vansyngel, FV Tent, P Vielva, F Villa, N Vittorio, IK Wehus, A Zacchei, A Zonca, Planck 2018 results. XI. Polarized dust foregrounds, 2018,

P. Benner, H. Fessbender, C. Yang, "Some remarks on the complex J-symmetric eigenproblem", Linear Algebra and its Applications, January 14, 2018, 544:407-442, doi: 10.1016/j.laa.2018.01.014

O. Rübel, B. P. Bowen, "BASTet: Shareable and reproducible analysis and visualization of mass spectrometry imaging data via OpenMSI", IEEE Transactions on Visualization and Computer Graphics, January 12, 2018, 24,no. 1, doi: 10.1109/TVCG.2017.2744479

Shannon K. Jones, Amneet Pal Singh Bhalla, Georgios Katsikis, Boyce E. Griffith, Daphne Klotsa, "Transition in motility mechanism due to inertia in a model self-propelled two-sphere swimmer", January 11, 2018,

Patrick J. Lestrange, David B. Williams-Young, Alessio Petrone, Carlos A. Jimenez-Hoyos, Xiaosong Li, "Efficient Implementation of Variation after Projection Generalized Hartree-Fock", Journal of Chemical Theory and Computation, 2018, 14:588-596, doi: 10.1021/acs.jctc.7b00832

JL Vay, A Almgren, J Bell, L Ge, DP Grote, M Hogan, O Kononenko, R Lehe, A Myers, C Ng, J Park, R Ryne, O Shapoval, M Thévenet, W Zhang, "Warp-X: A new exascale computing platform for beam–plasma simulations", Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 2018, 909:476--479, doi: 10.1016/j.nima.2018.01.035

DK Dalakoti, A Krisman, B Savard, A Wehrfritz, H Wang, MS Day, JB Bell, ER Hawkes, "Structure and propagation of two-dimensional, partially premixed, laminar flames in diesel engine conditions", Proceedings of the Combustion Institute, 2018, doi: 10.1016/j.proci.2018.06.169

D Dasgupta, W Sun, MS Day, AJ Aspden, TC Lieuwen, "Investigation of turbulence effects on chemical pathways for n-dodecane", AIAA Aerospace Sciences Meeting, 2018, 2018, doi: 10.2514/6.2018-1426

FP Hamon, MS Day, ML Minion, "Concurrent implicit spectral deferred correction scheme for low-Mach number combustion with detailed chemistry", Combustion Theory and Modelling, 2018, doi: 10.1080/13647830.2018.1524156

A Nonaka, MS Day, JB Bell, "A conservative, thermodynamically consistent numerical approach for low Mach number combustion. Part I: Single-level integration", Combustion Theory and Modelling, 2018, 22:156--184, doi: 10.1080/13647830.2017.1390610

Adrián P. Diéguez, Margarita Amor, Jacobo Lobeiras, Ramón Doallo, "Solving Large Problem Sizes of Index-Digit Algorithms on GPU: FFT and Tridiagonal System Solvers", IEEE Transactions on Computers, January 1, 2018, 67:86-101, doi: 10.1109/TC.2017.2723879

P Koanantakool, A Ali, A Azad, A Buluç, D Morozov, L Oliker, KA Yelick, S-Y Oh, "Communication-Avoiding Optimization Methods for Distributed Massive-Scale Sparse Inverse Covariance Estimation.", Proceedings of Machine Learning Research, PMLR, 2018, 84:1376--1386,

Hongyuan Zhan, Gabriel Gomes, Xiaoye S Li, Kamesh Madduri, Alex Sim, Kesheng Wu, "Consensus ensemble system for traffic flow prediction", IEEE Transactions on Intelligent Transportation Systems, 2018, 19:3903--3914,

P Koanantakool, A Ali, A Azad, A Buluç, D Morozov, L Oliker, K Yelick, SY Oh, Communication-avoiding optimization methods for distributed massive-scale sparse inverse covariance estimation, International Conference on Artificial Intelligence and Statistics, AISTATS 2018, Pages: 1376--1386 2018,

Cecilia Dao, Xinyu Liu, Alex Sim, Craig Tull, Kesheng Wu, "Modeling data transfers: change point and anomaly detection", 2018 IEEE 38th International Conference on Distributed Computing Systems (ICDCS), 2018, 1589--1594,

Dáithí A Stone, Mark D Risser, Oliver M Angélil, Michael F Wehner, Shreyas Cholia, Noel Keen, Harinarayan Krishnan, Travis A O Brien, William D Collins, "A basis set for exploration of sensitivity to prescribed ocean conditions for estimating human contributions to extreme weather in CAM5. 1-1degree", Weather and climate extremes, 2018, 19:10--19,

Anubhav Jain, Joseph Montoya, Shyam Dwaraknath, Nils ER Zimmermann, John Dagdelen, Matthew Horton, Patrick Huck, Donny Winston, Shreyas Cholia, Shyue Ping Ong, others, "The Materials Project: Accelerating Materials Design Through Theory-Driven Data and Tools", Handbook of Materials Modeling: Methods: Theory and Modeling, (Springer: 2018) Pages: 1--34

Andrey Babichev, Dmitriy Morozov, Yuri Dabaghian, "Robust spatial memory maps encoded by networks with transient", PLoS computational biology, 2018, 14:e1006433,

Kesheng Wu, Horst D Simon, "High-Performance Computational Intelligence and Forecasting Technologies", 2018,

Junmin Gu, Scott Klasky, Norbert Podhorszki, Ji Qiang, Kesheng Wu, "Querying large scientific data sets with adaptable IO system ADIOS", Asian Conference on Supercomputing Frontiers, 2018, 51--69,

D Ghoshal, L Ramakrishnan, D Agarwal, "Dac-Man: Data Change Management for Scientific Datasets on HPC Systems", SC ’18, Piscataway, NJ, USA, IEEE Press, 2018, 72:1--72:1,

Rajkumar Kettimuthu, Zhengchun Liu, Ian Foster, Peter H Beckman, Alex Sim, Kesheng Wu, Wei-keng Liao, Qiao Kang, Ankit Agrawal, Alok Choudhary, "Towards autonomic science infrastructure: architecture, limitations, and open issues", Proceedings of the 1st International Workshop on Autonomous Infrastructure for Science, 2018, 1--9,

Quasar absorption lines are used extensively in astrophysics to place constraints on cosmological models. In this thesis, we focus on the measurement of two important parameters in cosmology, the electromagnetic coupling constant, or fine-structure constant, α≡e2/(4πεℏc), and the primordial deuterium-to-hydrogen ratio, D/H. Any cosmological variation of α will cause its value to be different in the early stage of the Universe, therefore impacting the production of the primordial light elements during Big Bang Nucleosynthesis. We provide updated ∆α/α measurements from 280 absorption systems previously published in the literature using the non-linear least-square Voigt Profile fitting program VPFIT10. We also investigate the impact of long-range wavelength-scale distortions on those measurements. We found that long-range distortions are unlikely to explain the 4.1σ evidence for an α dipole as reported in the literature even though they do impact on the α-dipole significance. The above work led us to examine the kinematics of each absorption system in our sample. We report a correlation between the complexity of the velocity structure of Damped Lyman-α systems and the apparent position of the Lyman limit break in quasar spectra. We develop a new technique, based on this correlation, to identify suitable Damped Lyman-α systems for D/H measurements.

Mengying Yang, Xinyu Liu, Wilko Kroeger, Alex Sim, Kesheng Wu, "Identifying anomalous file transfer events in LCLS workflow", Proceedings of the 1st International Workshop on Autonomous Infrastructure for Science, 2018, 1--4,

Kesheng Wu, Bin Dong, Surendra Byna, "Scientific Data Services Framework for Plasma Physics", APS, 2018, 2018:BM10--006,

Hongyuan Zhan, Gabriel Gomes, Xiaoye S Li, Kamesh Madduri, Kesheng Wu, "Efficient online hyperparameter learning for traffic flow prediction", 2018 21st International Conference on Intelligent Transportation Systems (ITSC), 2018, 164--169,

Michael Sullivan, Myles T Collins, Josh Schellenberg, Peter H Larsen, Estimating power system interruption costs: A guidebook for electric utilities, 2018,

M Morzfeld, MS Day, RW Grout, GSH Pau, SA Finsterle, JB Bell, "Iterative importance sampling algorithms for parameter estimation", SIAM Journal on Scientific Computing, 2018, 40:B329--B352, doi: 10.1137/16M1088417

Meiyue Shao, Hasan Metin Aktulga, Chao Yang, Esmond G. Ng, Pieter Maris, James P. Vary, "Accelerating nuclear configuration interaction calculations through a preconditioned block iterative eigensolver", Computer Physics Communications, 2018, 222:1--13, doi: 10.1016/j.cpc.2017.09.004

Changho Kim, Andy Nonaka, John B. Bell, Alejandro L. Garcia, Aleksandar Donev, "Fluctuating hydrodynamics of reactive liquid mixtures", The Journal of Chemical Physics, 2018, 149:084113, doi: 10.1063/1.5043428

Erich Lohrmann, Zarija Lukic, Dmitriy Morozov, Juliane Mueller, "Programmable In Situ System for Iterative Workflows", Lecture Notes in Computer Science, Cham, Springer International Publishing, January 1, 2018, 10773:122--131, doi: 10.1007/978-3-319-77398-8\_7

T Hasebe, S Kashima, PAR Ade, Y Akiba, D Alonso, K Arnold, J Aumont, C Baccigalupi, D Barron, S Basak, S Beckman, J Borrill, F Boulanger, M Bucher, E Calabrese, Y Chinone, HM Cho, A Cukierman, DW Curtis, T de Haan, M Dobbs, A Dominjon, T Dotani, L Duband, A Ducout, J Dunkley, JM Duval, T Elleflot, HK Eriksen, J Errard, J Fischer, T Fujino, T Funaki, U Fuskeland, K Ganga, N Goeckner-Wald, J Grain, NW Halverson, T Hamada, M Hasegawa, K Hattori, M Hattori, L Hayes, M Hazumi, N Hidehira, CA Hill, G Hilton, J Hubmayr, K Ichiki, T Iida, H Imada, M Inoue, Y Inoue, KD Irwin, H Ishino, O Jeong, H Kanai, D Kaneko, N Katayama, T Kawasaki, SA Kernasovskiy, R Keskitalo, A Kibayashi, Y Kida, K Kimura, T Kisner, K Kohri, E Komatsu, K Komatsu, CL Kuo, NA Kurinsky, A Kusaka, A Lazarian, AT Lee, D Li, E Linder, B Maffei, A Mangilli, M Maki, T Matsumura, S Matsuura, D Meilhan, S Mima, Y Minami, K Mitsuda, L Montier, M Nagai, T Nagasaki, R Nagata, M Nakajima, S Nakamura, T Namikawa, M Naruse, H Nishino, T Nitta, T Noguchi, H Ogawa, S Oguri, N Okada, A Okamoto, "Concept Study of Optical Configurations for High-Frequency Telescope for LiteBIRD", Journal of Low Temperature Physics, 2018, 193:841--850, doi: 10.1007/s10909-018-1915-2

B Westbrook, PAR Ade, M Aguilar, Y Akiba, K Arnold, C Baccigalupi, D Barron, D Beck, S Beckman, AN Bender, F Bianchini, D Boettger, J Borrill, S Chapman, Y Chinone, G Coppi, K Crowley, A Cukierman, T de Haan, R Dünner, M Dobbs, T Elleflot, J Errard, G Fabbian, SM Feeney, C Feng, G Fuller, N Galitzki, A Gilbert, N Goeckner-Wald, J Groh, NW Halverson, T Hamada, M Hasegawa, M Hazumi, CA Hill, W Holzapfel, L Howe, Y Inoue, G Jaehnig, A Jaffe, O Jeong, D Kaneko, N Katayama, B Keating, R Keskitalo, T Kisner, N Krachmalnicoff, A Kusaka, M Le Jeune, AT Lee, D Leon, E Linder, L Lowry, A Madurowicz, D Mak, F Matsuda, A May, NJ Miller, Y Minami, J Montgomery, M Navaroli, H Nishino, J Peloton, A Pham, L Piccirillo, D Plambeck, D Poletti, G Puglisi, C Raum, G Rebeiz, CL Reichardt, PL Richards, H Roberts, C Ross, KM Rotermund, Y Segawa, B Sherwin, M Silva-Feaver, P Siritanasak, R Stompor, A Suzuki, O Tajima, S Takakura, S Takatori, D Tanabe, R Tat, GP Teply, A Tikhomirov, T Tomaru, C Tsai, N Whitehorn, A Zahn, "The POLARBEAR-2 and Simons Array Focal Plane Fabrication Status", Journal of Low Temperature Physics, 2018, 193:758--770, doi: 10.1007/s10909-018-2059-0

M Gribaudo, M Iacono, M Kiran, "A performance modeling framework for lambda architecture based applications", Future Generation Computer Systems, 2018, 86:1032--1041, doi: 10.1016/j.future.2017.07.033

M Kiran, E Pouyoul, A Mercian, B Tierney, C Guok, I Monga, "Enabling intent to configure scientific networks for high performance demands", Future Generation Computer Systems, 2018, 79:205--214, doi: 10.1016/j.future.2017.04.020

RJ Pandolfi, DB Allan, E Arenholz, L Barroso-Luque, SI Campbell, TA Caswell, A Blair, F De Carlo, S Fackler, AP Fournier, G Freychet, M Fukuto, D Gürsoy, Z Jiang, H Krishnan, D Kumar, RJ Kline, R Li, C Liman, S Marchesini, A Mehta, AT N Diaye, DY Parkinson, H Parks, LA Pellouchoud, T Perciano, F Ren, S Sahoo, J Strzalka, D Sunday, CJ Tassone, D Ushizima, S Venkatakrishnan, KG Yager, P Zwart, JA Sethian, A Hexemer, "Xi-cam: a versatile interface for data visualization and analysis", Journal of Synchrotron Radiation, 2018, 25:1261--1270, doi: 10.1107/S1600577518005787

B Lessley, T Perciano, C Heinemann, D Camp, H Childs, EW Bethel, "DPP-PMRF: Rethinking Optimization for a Probabilistic Graphical Model Using Data-Parallel Primitives", The 8th IEEE Symposium on Large Data Analysis and Visualization - LDAV 2018, 2018,

C Heinemann, T Perciano, D Ushizima, EW Bethel, "Distributed memory parallel Markov random fields using graph partitioning", Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017, 2018, 2018-Jan:3332--3341, doi: 10.1109/BigData.2017.8258318

Weijie Zhao, Florin Rusu, Bin Dong, Kesheng Wu, Anna YQ Ho, Peter Nugent, "Distributed caching for processing raw arrays", Proceedings of the 30th International Conference on Scientific and Statistical Database Management, 2018, 1--12,

Y Akrami, F Argueso, M Ashdown, J Aumont, C Baccigalupi, M Ballardini, AJ Banday, RB Barreiro, N Bartolo, S Basak, K Benabed, J-P Bernard, M Bersanelli, P Bielewicz, L Bonavera, JR Bond, J Borrill, FR Bouchet, C Burigana, RC Butler, E Calabrese, J Carron, HC Chiang, C Combet, BP Crill, F Cuttaia, P de Bernardis, A de Rosa, G de Zotti, J Delabrouille, J-M Delouis, E Di Valentino, C Dickinson, JM Diego, A Ducout, X Dupac, G Efstathiou, F Elsner, TA Ensslin, HK Eriksen, Y Fantaye, F Finelli, M Frailis, AA Fraisse, E Franceschi, A Frolov, S Galeotta, S Galli, K Ganga, RT Genova-Santos, M Gerbino, T Ghosh, J Gonzalez-Nuevo, KM Gorski, S Gratton, A Gruppuso, JE Gudmundsson, W Handley, FK Hansen, D Herranz, E Hivon, Z Huang, AH Jaffe, WC Jones, E Keihanen, R Keskitalo, K Kiiveri, J Kim, TS Kisner, N Krachmalnicoff, M Kunz, H Kurki-Suonio, A Lahteenmaki, J-M Lamarre, A Lasenby, M Lattanzi, CR Lawrence, F Levrier, M Liguori, PB Lilje, V Lindholm, M Lopez-Caniego, Y-Z Ma, JF Macias-Perez, G Maggio, D Maino, N Mandolesi, A Mangilli, M Maris, PG Martin, E Martinez-Gonzalez, S Matarrese, JD McEwen, PR Meinhold, A Melchiorri, A Mennella, M Migliaccio, M-A Miville-Deschenes, D Molinari, A Moneti, L Montier, G Morgante, P Natoli, CA Oxborrow, L Pagano, D Paoletti, B Partridge, G Patanchon, TJ Pearson, V Pettorino, F Piacentini, G Polenta, J-L Puget, JP Rachen, B Racine, M Reinecke, M Remazeilles, A Renzi, G Rocha, G Roudier, JA Rubino-Martin, L Salvati, M Sandri, M Savelainen, D Scott, A-S Suur-Uski, JA Tauber, D Tavagnacco, L Toffolatti, M Tomasi, T Trombetti, M Tucci, J Valiviita, B Van Tent, P Vielva, F Villa, N Vittorio, IK Wehus, A Zacchei, A Zonca, P Collaboration, "Planck intermediate results LIV. The Planck multi-frequency catalogue of non-thermal sources", ASTRONOMY \& ASTROPHYSICS, 2018, 619, doi: 10.1051/0004-6361/201832888

Sowmya Balasubramanian, Dipak Ghosal, Kamala Narayanan Balasubramanian Sharath, Eric Pouyoul, Alex Sim, Kesheng Wu, Brian Tierney, "Auto-tuned publisher in a pub/sub system: Design and performance evaluation", 2018 IEEE International Conference on Autonomic Computing (ICAC), 2018, 21--30,

C Li, C Michel, L Seland Graff, I Bethke, G Zappa, TJ Bracegirdle, E Fischer, BJ Harvey, T Iversen, MP King, H Krishnan, L Lierhammer, D Mitchell, J Scinocca, H Shiogama, DA Stone, JJ Wettstein, Midlatitude atmospheric circulation responses under 1.5 and 2.0g°C warming and implications for regional impacts, Earth System Dynamics, Pages: 359--382 2018, doi: 10.5194/esd-9-359-2018

Y Sekimoto, P Ade, K Arnold, J Aumont, J Austermann, C Baccigalupi, A Banday, R Banerji, S Basak, S Beckman, M Bersanelli, J Borrill, F Boulanger, ML Brown, M Bucher, E Calabrese, FJ Casas, A Challinor, Y Chinone, F Columbro, A Cukierman, D Curtis, P De Bernardis, M De Petris, M Dobbs, T Dotani, L Duband, JM Duval, A Ducout, K Ebisawa, T Elleot, H Eriksen, J Errard, R Flauger, C Franceschet, U Fuskeland, K Ganga, RJ Gao, T Ghigna, J Grain, A Gruppuso, N Halverson, P Hargrave, T Hasebe, M Hasegawa, M Hattori, M Hazumi, S Henrot-Versille, C Hill, Y Hirota, E Hivon, TD Hoang, J Hubmayr, K Ichiki, H Imada, H Ishino, G Jaehnig, H Kanai, S Kashima, Y Kataoka, N Katayama, T Kawasaki, R Keskitalo, A Kibayashi, T Kikuchi, K Kimura, T Kisner, Y Kobayashi, N Kogiso, K Kohri, E Komatsu, K Komatsu, K Konishi, N Krachmalnicoff, LC Kuo, N Kurinsky, A Kushino, L Lamagna, TA Lee, E Linder, B Maffei, M Maki, A Mangilli, E Martinez-Gonzalez, S Masi, T Matsumura, A Mennella, Y Minami, K Mistuda, D Molinari, L Montier, G Morgante, B Mot, Y Murata, A Murphy, M Nagai, R Nagata, S Nakamura, T Namikawa, P Natoli, "Concept design of the LiteBIRD satellite for CMB B-mode polarization", Proceedings of SPIE - The International Society for Optical Engineering, 2018, 10698, doi: 10.1117/12.2313432

Jonathan Wang, Kesheng Wu, Alex Sim, Seongwook Hwangbo, "Feature Engineering and Classification Models for Partial Discharge in Power Transformers", Mij, 2018, 1001:60,

M Wehner, D Stone, D Mitchell, H Shiogama, E Fischer, LS Graff, VV Kharin, L Lierhammer, B Sanderson, H Krishnan, Changes in extremely hot days under stabilized 1.5 and 2.0 °c global warming scenarios as simulated by the HAPPI multi-model ensemble, Earth System Dynamics, Pages: 299--311 2018, doi: 10.5194/esd-9-299-2018

MF Wehner, KA Reed, B Loring, D Stone, H Krishnan, "Changes in tropical cyclones under stabilized 1.5 and 2.0°C global warming scenarios as simulated by the Community Atmospheric Model under the HAPPI protocols", Earth System Dynamics, 2018, 9:187--195, doi: 10.5194/esd-9-187-2018

A Suzuki, PAR Ade, Y Akiba, D Alonso, K Arnold, J Aumont, C Baccigalupi, D Barron, S Basak, S Beckman, J Borrill, F Boulanger, M Bucher, E Calabrese, Y Chinone, S Cho, B Crill, A Cukierman, DW Curtis, T de Haan, M Dobbs, A Dominjon, T Dotani, L Duband, A Ducout, J Dunkley, JM Duval, T Elleflot, HK Eriksen, J Errard, J Fischer, T Fujino, T Funaki, U Fuskeland, K Ganga, N Goeckner-Wald, J Grain, NW Halverson, T Hamada, T Hasebe, M Hasegawa, K Hattori, M Hattori, L Hayes, M Hazumi, N Hidehira, CA Hill, G Hilton, J Hubmayr, K Ichiki, T Iida, H Imada, M Inoue, Y Inoue, KD Irwin, H Ishino, O Jeong, H Kanai, D Kaneko, S Kashima, N Katayama, T Kawasaki, SA Kernasovskiy, R Keskitalo, A Kibayashi, Y Kida, K Kimura, T Kisner, K Kohri, E Komatsu, K Komatsu, CL Kuo, NA Kurinsky, A Kusaka, A Lazarian, AT Lee, D Li, E Linder, B Maffei, A Mangilli, M Maki, T Matsumura, S Matsuura, D Meilhan, S Mima, Y Minami, K Mitsuda, L Montier, M Nagai, T Nagasaki, R Nagata, M Nakajima, S Nakamura, T Namikawa, M Naruse, H Nishino, T Nitta, T Noguchi, H Ogawa, S Oguri, "The LiteBIRD Satellite Mission: Sub-Kelvin Instrument", Journal of Low Temperature Physics, 2018, 193:1048--1056, doi: 10.1007/s10909-018-1947-7

JJ Billings, AR Bennett, J Deyton, K Gammeltoft, J Graham, D Gorin, H Krishnan, M Li, AJ McCaskey, T Patterson, R Smith, GR Watson, A Wojtowicz, The eclipse integrated computational environment, SoftwareX, Pages: 234--244 2018, doi: 10.1016/j.softx.2018.07.004

Terry Benzel and Sean Peisert, Selected Papers from the 2017 IEEE Symposium on Security and Privacy [Guest editors' introduction], IEEE Security & Privacy, Pages: 10-11 January 2018, doi: 10.1109/MSP.2018.1331038

M Wehner, D Stone, H Shiogama, P Wolski, A Ciavarella, N Christidis, H Krishnan, Early 21st century anthropogenic changes in extremely hot days as simulated by the C20C+ detection and attribution multi-model ensemble, Weather and Climate Extremes, Pages: 1--8 2018, doi: 10.1016/j.wace.2018.03.001

DA Stone, MD Risser, OM Angélil, MF Wehner, S Cholia, N Keen, H Krishnan, TA O Brien, WD Collins, A basis set for exploration of sensitivity to prescribed ocean conditions for estimating human contributions to extreme weather in CAM5.1-1degree, Weather and Climate Extremes, Pages: 10--19 2018, doi: 10.1016/j.wace.2017.12.003

KA Fischer, R Trivedi, V Ramasesh, I Siddiqi, J Vuckovic, "Scattering into one-dimensional waveguides from a coherently-driven quantum-optical system", Quantum, 2018, 2, doi: 10.22331/q-2018-05-28-69

A Eddins, S Schreppler, DM Toyli, LS Martin, S Hacohen-Gourgy, LCG Govia, H Ribeiro, AA Clerk, I Siddiqi, "Stroboscopic Qubit Measurement with Squeezed Illumination.", Physical review letters, 2018, 120:040505, doi: 10.1103/physrevlett.120.040505

A Chantasri, J Atalaya, S Hacohen-Gourgy, LS Martin, I Siddiqi, AN Jordan, "Simultaneous continuous measurement of noncommuting observables: Quantum state correlations", Physical Review A, 2018, 97, doi: 10.1103/PhysRevA.97.012118

S Hacohen-Gourgy, LP García-Pintos, LS Martin, J Dressel, I Siddiqi, "Incoherent Qubit Control Using the Quantum Zeno Effect.", Physical review letters, 2018, 120:020505, doi: 10.1103/physrevlett.120.020505

T. M. C. Abbott, F. B. Abdalla, S. Allam, A. Amara, J. Annis, J. Asorey, S. Avila, O. Ballester, M. Banerji, W. Barkhouse, L. Baruah, M. Baumer, K. Bechtol, M. R. Becker, A. Benoit-L\ evy, G. M. Bernstein, E. Bertin, J. Blazek, S. Bocquet, D. Brooks, D. Brout, E. Buckley-Geer, D. L. Burke, V. Busti, R. Campisano, L. Cardiel-Sas, A. Carnero Rosell, M. Carrasco Kind, J. Carretero, F. J. Castander, R. Cawthon, C. Chang, X. Chen, C. Conselice, G. Costa, M. Crocce, C. E. Cunha, C. B. D Andrea, L. N. da Costa, R. Das, G. Daues, T. M. Davis, C. Davis, J. De Vicente, D. L. DePoy, J. DeRose, S. Desai, H. T. Diehl, J. P. Dietrich, S. Dodelson, P. Doel, A. Drlica-Wagner, T. F. Eifler, A. E. Elliott, A. E. Evrard, A. Farahi, A. Fausti Neto, E. Fernandez, D. A. Finley, B. Flaugher, R. J. Foley, P. Fosalba, D. N. Friedel, J. Frieman, J. Garc\ \ia-Bellido, E. Gaztanaga, D. W. Gerdes, T. Giannantonio, M. S. S. Gill, K. Glazebrook, D. A. Goldstein, M. Gower, D. Gruen, R. A. Gruendl, J. Gschwend, R. R. Gupta, G. Gutierrez, S. Hamilton, W. G. Hartley, S. R. Hinton, J. M. Hislop, D. Hollowood, K. Honscheid, B. Hoyle, D. Huterer, B. Jain, D. J. James, T. Jeltema, M. W. G. Johnson, M. D. Johnson, T. Kacprzak, S. Kent, G. Khullar, M. Klein, A. Kovacs, A. M. G. Koziol, E. Krause, A. Kremin, R. Kron, K. Kuehn, S. Kuhlmann, N. Kuropatkin, O. Lahav, J. Lasker, T. S. Li, R. T. Li, A. R. Liddle, M. Lima, H. Lin, P. L\ opez-Reyes, N. MacCrann, M. A. G. Maia, J. D. Maloney, M. Manera, M. March, J. Marriner, J. L. Marshall, P. Martini, T. McClintock, T. McKay, R. G. McMahon, P. Melchior, F. Menanteau, C. J. Miller, R. Miquel, J. J. Mohr, E. Morganson, J. Mould, E. Neilsen, R. C. Nichol, F. Nogueira, B. Nord, P. Nugent, L. Nunes, R. L. C. Ogando, L. Old, A. B. Pace, A. Palmese, F. Paz-Chinch\ on, H. V. Peiris, W. J. Percival, D. Petravick, A. A. Plazas, J. Poh, C. Pond, A. Porredon, A. Pujol, A. Refregier, K. Reil, P. M. Ricker, R. P. Rollins, A. K. Romer, A. Roodman, P. Rooney, A. J. Ross, E. S. Rykoff, M. Sako, M. L. Sanchez, E. Sanchez, B. Santiago, A. Saro, V. Scarpine, D. Scolnic, S. Serrano, I. Sevilla-Noarbe, E. Sheldon, N. Shipp, M. L. Silveira, M. Smith, R. C. Smith, J. A. Smith, M. Soares-Santos, F. Sobreira, J. Song, A. Stebbins, E. Suchyta, M. Sullivan, M. E. C. Swanson, G. Tarle, J. Thaler, D. Thomas, R. C. Thomas, M. A. Troxel, D. L. Tucker, V. Vikram, A. K. Vivas, A. R. Walker, R. H. Wechsler, J. Weller, W. Wester, R. C. Wolf, H. Wu, B. Yanny, A. Zenteno, Y. Zhang, J. Zuntz, DES Collaboration, S. Juneau, M. Fitzpatrick, R. Nikutta, D. Nidever, K. Olsen, A. Scott, NOAO Data Lab, "The Dark Energy Survey: Data Release 1", Astrophysical Journal Supplement, 2018, 239:18, doi: 10.3847/1538-4365/aae9f0

T. M. C. Abbott, F. B. Abdalla, J. Annis, K. Bechtol, J. Blazek, B. A. Benson, R. A. Bernstein, G. M. Bernstein, E. Bertin, D. Brooks, D. L. Burke, A. Carnero Rosell, M. Carrasco Kind, J. Carretero, F. J. Castander, C. L. Chang, T. M. Crawford, C. E. Cunha, C. B. D Andrea, L. N. da Costa, C. Davis, J. DeRose, S. Desai, H. T. Diehl, J. P. Dietrich, P. Doel, A. Drlica-Wagner, A. E. Evrard, E. Fernandez, B. Flaugher, P. Fosalba, J. Frieman, J. Garc\ \ia-Bellido, E. Gaztanaga, D. W. Gerdes, T. Giannantonio, D. Gruen, R. A. Gruendl, J. Gschwend, G. Gutierrez, W. G. Hartley, J. W. Henning, K. Honscheid, B. Hoyle, D. Huterer, B. Jain, D. J. James, M. Jarvis, T. Jeltema, M. D. Johnson, M. W. G. Johnson, E. Krause, K. Kuehn, S. Kuhlmann, N. Kuropatkin, O. Lahav, A. R. Liddle, M. Lima, H. Lin, N. MacCrann, M. A. G. Maia, A. Manzotti, M. March, J. L. Marshall, R. Miquel, J. J. Mohr, T. Natoli, P. Nugent, R. L. C. Ogando, Y. Park, A. A. Plazas, C. L. Reichardt, K. Reil, A. Roodman, A. J. Ross, E. Rozo, E. S. Rykoff, E. Sanchez, V. Scarpine, M. Schubnell, D. Scolnic, I. Sevilla-Noarbe, E. Sheldon, M. Smith, R. C. Smith, M. Soares-Santos, F. Sobreira, E. Suchyta, G. Tarle, D. Thomas, M. A. Troxel, A. R. Walker, R. H. Wechsler, J. Weller, W. Wester, W. L. K. Wu, J. Zuntz, Dark Energy Survey Collaboration, South Pole Telescope Collaboration, "Dark Energy Survey Year 1 Results: A Precise H$_0$ Estimate from DES Y1, BAO, and D/H Data", Monthly Notices of the RAS, 2018, 480:3879-3888, doi: 10.1093/mnras/sty1939

C. E. Harris, P. E. Nugent, A. Horesh, J. S. Bright, R. P., M. L. Graham, K. Maguire, M. Smith, N., S. Valenti, A. V. Filippenko, O. Fox, A. Goobar, P. L. Kelly, K. J. Shen, "Don't Blink: Constraining the Circumstellar Environment of the Interacting Type Ia Supernova 2015cp", Astrophysical Journal, 2018, 868:21, doi: 10.3847/1538-4357/aae521

K. De, M. M. Kasliwal, E. O. Ofek, T. J. Moriya, J. Burke, Y. Cao, S. B. Cenko, G. B. Doran, G. E. Duggan, R. P. Fender, C. Fransson, A. Gal-Yam, A. Horesh, S. R. Kulkarni, R. R. Laher, R. Lunnan, I. Manulis, F. Masci, P. A. Mazzali, P. E. Nugent, D. A. Perley, T. Petrushevska, A. L. Piro, C. Rumsey, J. Sollerman, M. Sullivan, F. Taddia, "A hot and fast ultra-stripped supernova that likely formed a compact neutron star binary", Science, 2018, 362:201-206, doi: 10.1126/science.aas8693

T. Hung, S. Gezari, S. B. Cenko, S. van Velzen, N. Blagorodnova, Lin Yan, S. R. Kulkarni, R. Lunnan, T. Kupfer, G. Leloudas, A. K. H. Kong, P. E. Nugent, C. Fremling, Russ R. Laher, F. J. Masci, Y. Cao, R. Roy, T. Petrushevska, "Sifting for Sapphires: Systematic Selection of Tidal Disruption Events in iPTF", Astrophysical Journal Supplement, 2018, 238:15, doi: 10.3847/1538-4365/aad8b1

Kishalay De, Mansi M. Kasliwal, Therese Cantwell, Yi Cao, S. Bradley Cenko, Avishay Gal-Yam, Joel Johansson, Albert Kong, Shrinivas R. Kulkarni, Ragnhild Lunnan, Frank Masci, Matt Matuszewski, Kunal P. Mooley, James D. Neill, Peter E. Nugent, Eran O. Ofek, Yvette Perrott, Umaa D. Rebbapragada, Adam Rubin, Donal O Sullivan, Ofer Yaron, "iPTF 16hgs: A Double-peaked Ca-rich Gap Transient in a Metal-poor, Star-forming Dwarf Galaxy", Astrophysical Journal, 2018, 866:72, doi: 10.3847/1538-4357/aadf8e

C. Fremling, J. Sollerman, M. M. Kasliwal, S. R. Kulkarni, C. Barbarino, M. Ergon, E. Karamehmetoglu, F. Taddia, I. Arcavi, S. B. Cenko, K. Clubb, A. De Cia, G. Duggan, A. V. Filippenko, A. Gal-Yam, M. L. Graham, A. Horesh, G. Hosseinzadeh, D. A. Howell, D. Kuesters, R. Lunnan, T. Matheson, P. E. Nugent, D. A. Perley, R. M. Quimby, C. Saunders, Oxygen and helium in stripped-envelope supernovae, Astronomy and Astrophysics, Pages: A37 2018, doi: 10.1051/0004-6361/201731701

Y Akrami, F Arguëso, M Ashdown, J Aumont, C Baccigalupi, M Ballardini, AJ Banday, RB Barreiro, N Bartolo, S Basak, K Benabed, JP Bernard, M Bersanelli, P Bielewicz, L Bonavera, JR Bond, J Borrill, FR Bouchet, C Burigana, RC Butler, E Calabrese, J Carron, HC Chiang, C Combet, BP Crill, F Cuttaia, P De Bernardis, A De Rosa, G De Zotti, J Delabrouille, JM Delouis, E Di Valentino, C Dickinson, JM Diego, A Ducout, X Dupac, G Efstathiou, F Elsner, TA Enßlin, HK Eriksen, Y Fantaye, F Finelli, M Frailis, AA Fraisse, E Franceschi, A Frolov, S Galeotta, S Galli, K Ganga, RT Génova-Santos, M Gerbino, T Ghosh, J González-Nuevo, KM Górski, S Gratton, A Gruppuso, JE Gudmundsson, W Handley, FK Hansen, D Herranz, E Hivon, Z Huang, AH Jaffe, WC Jones, E Keihänen, R Keskitalo, K Kiiveri, J Kim, TS Kisner, N Krachmalnicoff, M Kunz, H Kurki-Suonio, A Lähteenmäki, JM Lamarre, A Lasenby, M Lattanzi, CR Lawrence, F Levrier, M Liguori, PB Lilje, V Lindholm, M López-Caniego, YZ Ma, JF MacIás-Pérez, G Maggio, D Maino, N Mandolesi, A Mangilli, M Maris, PG Martin, E Martínez-González, S Matarrese, JD McEwen, PR Meinhold, A Melchiorri, A Mennella, M Migliaccio, MA Miville-Deschênes, D Molinari, A Moneti, "Planck intermediate results: LIV. the Planck multi-frequency catalogue of non-thermal sources", Astronomy and Astrophysics, 2018, 619, doi: 10.1051/0004-6361/201832888

R. Lunnan, C. Fransson, P. M. Vreeswijk, S. E. Woosley, G. Leloudas, D. A. Perley, R. M. Quimby, Lin Yan, N. Blagorodnova, B. D. Bue, S. B. Cenko, A. De Cia, D. O. Cook, C. U. Fremling, P. Gatkine, A. Gal-Yam, M. M. Kasliwal, S. R. Kulkarni, F. J. Masci, P. E. Nugent, A. Nyholm, A. Rubin, N. Suzuki, P. Wozniak, A UV resonance line echo from a shell around a hydrogen-poor superluminous supernova, Nature Astronomy, Pages: 887-895 2018, doi: 10.1038/s41550-018-0568-z

N Aghanim, Y Akrami, M Ashdown, J Aumont, C Baccigalupi, M Ballardini, AJ Banday, RB Barreiro, N Bartolo, S Basak, R Battye, K Benabed, JP Bernard, M Bersanelli, P Bielewicz, JR Bond, J Borrill, FR Bouchet, C Burigana, E Calabrese, J Carron, HC Chiang, B Comis, D Contreras, BP Crill, A Curto, F Cuttaia, P De Bernardis, A De Rosa, G De Zotti, J Delabrouille, E Di Valentino, C Dickinson, JM Diego, O Doré, A Ducout, X Dupac, F Elsner, TA Enßlin, HK Eriksen, E Falgarone, Y Fantaye, F Finelli, F Forastieri, M Frailis, AA Fraisse, E Franceschi, A Frolov, S Galeotta, S Galli, K Ganga, M Gerbino, KM Górski, A Gruppuso, JE Gudmundsson, W Handley, FK Hansen, D Herranz, E Hivon, Z Huang, AH Jaffe, E Keihänen, R Keskitalo, K Kiiveri, J Kim, TS Kisner, N Krachmalnicoff, M Kunz, H Kurki-Suonio, JM Lamarre, A Lasenby, M Lattanzi, CR Lawrence, M Le Jeune, F Levrier, M Liguori, PB Lilje, V Lindholm, M López-Caniego, PM Lubin, YZ Ma, JF MacÍas-Pérez, G Maggio, D Maino, N Mandolesi, A Mangilli, PG Martin, E Martínez-González, S Matarrese, N Mauri, JD McEwen, A Melchiorri, A Mennella, M Migliaccio, MA Miville-Deschênes, D Molinari, A Moneti, L Montier, G Morgante, P Natoli, "Planck intermediate results: LIII. Detection of velocity dispersion from the kinetic Sunyaev-Zeldovich effect", Astronomy and Astrophysics, 2018, 617, doi: 10.1051/0004-6361/201731489

T. M. C. Abbott, F. B. Abdalla, A. Alarcon, J. Aleksi\ c, S. Allam, S. Allen, A. Amara, J. Annis, J. Asorey, S. Avila, D. Bacon, E. Balbinot, M. Banerji, N. Banik, W. Barkhouse, M. Baumer, E. Baxter, K. Bechtol, M. R. Becker, A. Benoit-L\ evy, B. A. Benson, G. M. Bernstein, E. Bertin, J. Blazek, S. L. Bridle, D. Brooks, D. Brout, E. Buckley-Geer, D. L. Burke, M. T. Busha, A. Campos, D. Capozzi, A. Carnero Rosell, M. Carrasco Kind, J. Carretero, F. J. Castander, R. Cawthon, C. Chang, N. Chen, M. Childress, A. Choi, C. Conselice, R. Crittenden, M. Crocce, C. E. Cunha, C. B. D Andrea, L. N. da Costa, R. Das, T. M. Davis, C. Davis, J. De Vicente, D. L. DePoy, J. DeRose, S. Desai, H. T. Diehl, J. P. Dietrich, S. Dodelson, P. Doel, A. Drlica-Wagner, T. F. Eifler, A. E. Elliott, F. Elsner, J. Elvin-Poole, J. Estrada, A. E. Evrard, Y. Fang, E. Fernandez, A. Fert\ e, D. A. Finley, B. Flaugher, P. Fosalba, O. Friedrich, J. Frieman, J. Garc\ \ia-Bellido, M. Garcia-Fernandez, M. Gatti, E. Gaztanaga, D. W. Gerdes, T. Giannantonio, M. S. S. Gill, K. Glazebrook, D. A. Goldstein, D. Gruen, R. A. Gruendl, J. Gschwend, G. Gutierrez, S. Hamilton, W. G. Hartley, S. R. Hinton, K. Honscheid, B. Hoyle, D. Huterer, B. Jain, D. J. James, M. Jarvis, T. Jeltema, M. D. Johnson, M. W. G. Johnson, T. Kacprzak, S. Kent, A. G. Kim, A. King, D. Kirk, N. Kokron, A. Kovacs, E. Krause, C. Krawiec, A. Kremin, K. Kuehn, S. Kuhlmann, N. Kuropatkin, F. Lacasa, O. Lahav, T. S. Li, A. R. Liddle, C. Lidman, M. Lima, H. Lin, N. MacCrann, M. A. G. Maia, M. Makler, M. Manera, M. March, J. L. Marshall, P. Martini, R. G. McMahon, P. Melchior, F. Menanteau, R. Miquel, V. Miranda, D. Mudd, J. Muir, A. M\ oller, E. Neilsen, R. C. Nichol, B. Nord, P. Nugent, R. L. C. Ogando, A. Palmese, J. Peacock, H. V. Peiris, J. Peoples, W. J. Percival, D. Petravick, A. A. Plazas, A. Porredon, J. Prat, A. Pujol, M. M. Rau, A. Refregier, P. M. Ricker, N. Roe, R. P. Rollins, A. K. Romer, A. Roodman, R. Rosenfeld, A. J. Ross, E. Rozo, E. S. Rykoff, M. Sako, A. I. Salvador, S. Samuroff, C. S\ anchez, E. Sanchez, B. Santiago, V. Scarpine, R. Schindler, D. Scolnic, L. F. Secco, S. Serrano, I. Sevilla-Noarbe, E. Sheldon, R. C. Smith, M. Smith, J. Smith, M. Soares-Santos, F. Sobreira, E. Suchyta, G. Tarle, D. Thomas, M. A. Troxel, D. L. Tucker, B. E. Tucker, S. A. Uddin, T. N. Varga, P. Vielzeuf, V. Vikram, A. K. Vivas, A. R. Walker, M. Wang, R. H. Wechsler, J. Weller, W. Wester, R. C. Wolf, B. Yanny, F. Yuan, A. Zenteno, B. Zhang, Y. Zhang, J. Zuntz, Dark Energy Survey Collaboration, Dark Energy Survey year 1 results: Cosmological constraints from galaxy clustering and weak lensing, Physical Review D, Pages: 043526 2018, doi: 10.1103/PhysRevD.98.043526

K.-G. Lee, A. Krolewski, M. White, D. Schlegel, P. E., J. F. Hennawi, T. M\ uller, R., J. X. Prochaska, A. Font-Ribera, N. Suzuki, K., G. G. Kacprzak, J. S. Kartaltepe, A. M., O. Le F\ evre, B. C. Lemaux, C., T. Nanayakkara, R. M. Rich, D. B. Sanders, M. Salvato, L. Tasca, K.-V. H. Tran, First Data Release of the COSMOS Ly$\alpha$ Mapping and Tomography Observations: 3D Ly$\alpha$ Forest Tomography at 2.05 $\lt$ z $\lt$ 2.55, Astrophysical Journal Supplement, Pages: 31 2018, doi: 10.3847/1538-4365/aace58

A. Krolewski, K.-G. Lee, M. White, J. F. Hennawi, D. J., P. E. Nugent, Z. Lukic, C. W., A. M. Koekemoer, O. Le F\ evre, B. C., C. Maier, R. M. Rich, M. Salvato, L. Tasca, "Detection of z \tilde 2.3 Cosmic Voids from 3D Ly$\alpha$ Forest Tomography in the COSMOS Field", Astrophysical Journal, 2018, 861:60, doi: 10.3847/1538-4357/aac829

Carlos Contreras, M. M. Phillips, Christopher R. Burns, Anthony L. Piro, B. J. Shappee, Maximilian D. Stritzinger, C. Baltay, Peter J. Brown, Emmanuel Conseil, Alain Klotz, Peter E. Nugent, Damien Turpin, Stu Parker, D. Rabinowitz, Eric Y. Hsiao, Nidia Morrell, Abdo Campillay, Sergio Castell\ on, Carlos Corco, Consuelo Gonz\ alez, Kevin Krisciunas, Jacqueline Ser\ on, Brad E. Tucker, E. S. Walker, E. Baron, C. Cain, Michael J. Childress, Gast\ on Folatelli, Wendy L. Freedman, Mario Hamuy, P. Hoeflich, S. E. Persson, Richard Scalzo, Brian Schmidt, Nicholas B. Suntzeff, SN 2012fr: Ultraviolet, Optical, and Near-infrared Light Curves of a Type Ia Supernova Observed within a Day of Explosion, Astrophysical Journal, Pages: 24 2018, doi: 10.3847/1538-4357/aabaf8

Chris Frohmaier, Mark Sullivan, Kate Maguire, Peter Nugent, "The Volumetric Rate of Calcium-rich Transients in the Local Universe", Astrophysical Journal, 2018, 858:50, doi: 10.3847/1538-4357/aabc0b

M. Rigault, Y. Copin, G. Aldering, P. Antilogus, C., S. Bailey, C. Baltay, S. Bongard, C., A. Canto, F. Cellier-Holzem, M. Childress, N., H. K. Fakhouri, U. Feindt, M. Fleury, E., P. Greskovic, J. Guy, A. G. Kim, M., S. Lombardo, J. Nordin, P. Nugent, R., E. P\ econtal, R. Pereira, S. Perlmutter, D., K. Runge, C. Saunders, R. Scalzo, G., C. Tao, R. C. Thomas, B. A. Weaver, Nearby Supernova Factory, "Evidence of environmental dependencies of Type Ia supernovae from the Nearby Supernova Factory indicated by local H$\alpha$ (Corrigendum)", Astronomy and Astrophysics, 2018, 612:C1, doi: 10.1051/0004-6361/201322104e

DA Shapiro, R Celestre, B Enders, J Joseph, H Krishnan, MA Marcus, K Nowrouzi, H Padmore, J Park, A Warwick, Y-S Yu, The COSMIC Imaging Beamline at the Advanced Light Source: a new facility for spectro-microscopy of nano-materials, Microscopy and Microanalysis, Pages: 8--11 2018, doi: 10.1017/s1431927618012485

S. M. Adams, N. Blagorodnova, M. M. Kasliwal, R. Amanullah, T. Barlow, B. Bue, M. Bulla, Y. Cao, S. B. Cenko, D. O. Cook, R. Ferretti, O. D. Fox, C. Fremling, S. Gezari, A. Goobar, A. Y. Q. Ho, T. Hung, E. Karamehmetoglu, S. R. Kulkarni, T. Kupfer, R. R. Laher, F. J. Masci, A. A. Miller, J. D. Neill, P. E. Nugent, J. Sollerman, F. Taddia, R. Walters, "iPTF Survey for Cool Transients", Publications of the ASP, 2018, 130:034202, doi: 10.1088/1538-3873/aaa356

B Enders, K Nowrouzi, H Krishnan, S Marchesini, J Park, Y-S Yu, DA Shapiro, Dataflow at the COSMIC Beamline - Stream Processing and Supercomputing, Microscopy and Microanalysis, Pages: 58--59 2018, doi: 10.1017/s1431927618012710

Daniel A. Goldstein, Peter E. Nugent, Daniel N. Kasen, Thomas E. Collett, "Precise Time Delays from Strongly Gravitationally Lensed Type Ia Supernovae with Chromatically Microlensed Images", Astrophysical Journal, 2018, 855:22, doi: 10.3847/1538-4357/aaa975

Robert M. Quimby, Annalisa De Cia, Avishay Gal-Yam, Giorgos Leloudas, Ragnhild Lunnan, Daniel A. Perley, Paul M. Vreeswijk, Lin Yan, Joshua S. Bloom, S. Bradley Cenko, Jeff Cooke, Richard Ellis, Alexei V. Filippenko, Mansi M. Kasliwal, Io K. W. Kleiser, Shrinivas R. Kulkarni, Thomas Matheson, Peter E. Nugent, Yen-Chen Pan, Jeffrey M. Silverman, Assaf Sternberg, Mark Sullivan, Ofer Yaron, Spectra of Hydrogen-poor Superluminous Supernovae from the Palomar Transient Factory, Astrophysical Journal, Pages: 2 2018, doi: 10.3847/1538-4357/aaac2f

Anna Y. Q. Ho, S. R. Kulkarni, Peter E. Nugent, Weijie Zhao, Florin Rusu, S. Bradley Cenko, Vikram Ravi, Mansi M. Kasliwal, Daniel A. Perley, Scott M. Adams, Eric C. Bellm, Patrick Brady, Christoffer Fremling, Avishay Gal-Yam, David Alexander Kann, David Kaplan, Russ R. Laher, Frank Masci, Eran O. Ofek, Jesper Sollerman, Alex Urban, "iPTF Archival Search for Fast Optical Transients", Astrophysical Journal Letters, 2018, 854:L13, doi: 10.3847/2041-8213/aaaa62

M. Smith, M. Sullivan, R. C. Nichol, L. Galbany, C. B. D Andrea, C. Inserra, C. Lidman, A. Rest, M. Schirmer, A. V. Filippenko, W. Zheng, S. Bradley Cenko, C. R. Angus, P. J. Brown, T. M. Davis, D. A. Finley, R. J. Foley, S. Gonz\ alez-Gait\ an, C. P. Guti\ errez, R. Kessler, S. Kuhlmann, J. Marriner, A. M\ oller, P. E. Nugent, S. Prajs, R. Thomas, R. Wolf, A. Zenteno, T. M. C. Abbott, F. B. Abdalla, S. Allam, J. Annis, K. Bechtol, A. Benoit-L\ evy, E. Bertin, D. Brooks, D. L. Burke, A. Carnero Rosell, M. Carrasco Kind, J. Carretero, F. J. Castander, M. Crocce, C. E. Cunha, L. N. da Costa, C. Davis, S. Desai, H. T. Diehl, P. Doel, T. F. Eifler, B. Flaugher, P. Fosalba, J. Frieman, J. Garc\ \ia-Bellido, E. Gaztanaga, D. W. Gerdes, D. A. Goldstein, D. Gruen, R. A. Gruendl, J. Gschwend, G. Gutierrez, K. Honscheid, D. J. James, M. W. G. Johnson, K. Kuehn, N. Kuropatkin, T. S. Li, M. Lima, M. A. G. Maia, J. L. Marshall, P. Martini, F. Menanteau, C. J. Miller, R. Miquel, R. L. C. Ogando, D. Petravick, A. A. Plazas, A. K. Romer, E. S. Rykoff, M. Sako, E. Sanchez, V. Scarpine, R. Schindler, M. Schubnell, I. Sevilla-Noarbe, R. C. Smith, M. Soares-Santos, F. Sobreira, E. Suchyta, M. E. C. Swanson, G. Tarle, A. R. Walker, DES Collaboration, Studying the Ultraviolet Spectrum of the First Spectroscopically Confirmed Supernova at Redshift Two, Astrophysical Journal, Pages: 37 2018, doi: 10.3847/1538-4357/aaa126

D. Scolnic, R. Kessler, D. Brout, P. S. Cowperthwaite, M. Soares-Santos, J. Annis, K. Herner, H. -Y. Chen, M. Sako, Z. Doctor, R. E. Butler, A. Palmese, H. T. Diehl, J. Frieman, D. E. Holz, E. Berger, R. Chornock, V. A. Villar, M. Nicholl, R. Biswas, R. Hounsell, R. J. Foley, J. Metzger, A. Rest, J. Garc\ \ia-Bellido, A. M\ oller, P. Nugent, T. M. C. Abbott, F. B. Abdalla, S. Allam, K. Bechtol, A. Benoit-L\ evy, E. Bertin, D. Brooks, E. Buckley-Geer, A. Carnero Rosell, M. Carrasco Kind, J. Carretero, F. J. Castander, C. E. Cunha, C. B. D Andrea, L. N. da Costa, C. Davis, P. Doel, A. Drlica-Wagner, T. F. Eifler, B. Flaugher, P. Fosalba, E. Gaztanaga, D. W. Gerdes, D. Gruen, R. A. Gruendl, J. Gschwend, G. Gutierrez, W. G. Hartley, K. Honscheid, D. J. James, M. W. G. Johnson, M. D. Johnson, E. Krause, K. Kuehn, S. Kuhlmann, O. Lahav, T. S. Li, M. Lima, M. A. G. Maia, M. March, J. L. Marshall, F. Menanteau, R. Miquel, E. Neilsen, A. A. Plazas, E. Sanchez, V. Scarpine, M. Schubnell, I. Sevilla-Noarbe, M. Smith, R. C. Smith, F. Sobreira, E. Suchyta, M. E. C. Swanson, G. Tarle, R. C. Thomas, D. L. Tucker, A. R. Walker, DES Collaboration, "How Many Kilonovae Can Be Found in Past, Present, and Future Survey Data Sets?", Astrophysical Journal Letters, 2018, 852:L3, doi: 10.3847/2041-8213/aa9d82

E Deelman, T Peterka, I Altintas, CD Carothers, KK van Dam, K Moreland, M Parashar, L Ramakrishnan, M Taufer, J Vetter, "The future of scientific workflows", International Journal of High Performance Computing Applications, 2018, 32:159--175, doi: 10.1177/1094342017704893

A. A. Miller, Y. Cao, A. L. Piro, N. Blagorodnova, B. D. Bue, S. B. Cenko, S. Dhawan, R. Ferretti, O. D. Fox, C. Fremling, A. Goobar, D. A. Howell, G. Hosseinzadeh, M. M. Kasliwal, R. R. Laher, R. Lunnan, F. J. Masci, C. McCully, P. E. Nugent, J. Sollerman, F. Taddia, S. R. Kulkarni, "Early Observations of the Type Ia Supernova iPTF 16abc: A Case of Interaction with Nearby, Unbound Material and/or Strong Ejecta Mixing", Astrophysical Journal, 2018, 852:100, doi: 10.3847/1538-4357/aaa01f

F. Taddia, J. Sollerman, C. Fremling, E. Karamehmetoglu, R. M. Quimby, A. Gal-Yam, O. Yaron, M. M. Kasliwal, S. R. Kulkarni, P. E. Nugent, G. Smadja, C. Tao, "PTF11mnb: First analog of supernova 2005bf. Long-rising, double-peaked supernova Ic from a massive progenitor", Astronomy and Astrophysics, 2018, 609:A106, doi: 10.1051/0004-6361/201629874

GP Rodrigo, PO Östberg, E Elmroth, K Antypas, R Gerber, L Ramakrishnan, "Towards understanding HPC users and systems: A NERSC case study", Journal of Parallel and Distributed Computing, 2018, 111:206--221, doi: 10.1016/j.jpdc.2017.09.002

GP Rodrigo, E Elmroth, P-O Ostberg, L Ramakrishnan, "ScSF: A Scheduling Simulation Framework", Job Scheduling Strategies for Parallel Processing, Cham, Springer International Publishing, 2018, 152--173,

Tal Shachaf, Alexander Sim, Kesheng Wu, Wilko Kroeger, "Detecting Anomalies in the LCLS Workflow", 2018 IEEE International Conference on Big Data (Big Data), 2018, 3256--3260,

SubFlow: Modeling geological sequestration of carbon dioxide with mimetic discretization methods, Joint Mathematics Meetings (ACM), 2018,

Alina Lazar, Kesheng Wu, Alex Sim, "Predicting Network Traffic Using TCP Anomalies", 2018 IEEE International Conference on Big Data (Big Data), Pages: 5369--5371 2018,

D Barron, Y Chinone, A Kusaka, J Borril, J Errard, S Feeney, S Ferraro, R Keskitalo, AT Lee, NA Roe, BD Sherwin, A Suzuki, "Optimization study for the experimental configuration of CMB-S4", Journal of Cosmology and Astroparticle Physics, 2018, 2018, doi: 10.1088/1475-7516/2018/02/009

M Zingale, AS Almgren, MG Barrios Sazo, VE Beckner, JB Bell, B Friesen, AM Jacobs, MP Katz, CM Malone, AJ Nonaka, DE Willcox, W Zhang, "Meeting the Challenges of Modeling Astrophysical Thermonuclear Explosions: Castro, Maestro, and the AMReX Astrophysics Suite", Journal of Physics: Conference Series, 2018, 1031, doi: 10.1088/1742-6596/1031/1/012024

E. Rebrova, G. Chavez, Y. Liu, P. Ghysels, X. S. Li, "A Study of Clustering Techniques and Hierarchical Matrix Formats for Kernel Ridge Regression", IEEE IPDPSW, 2018,

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A. C. Yucel, W. Sheng, C. Zhou, Y. Liu, H. Bagci, E. Michielssen, "An FMM-FFT Accelerated SIE Simulator for Analyzing EM Wave Propagation in Mine Environments Loaded With Conductors", IEEE Journal on Multiscale and Multiphysics Computational Techniques, 2018, 3:3-15,

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H. Guo, Y. Liu, J. Hu, E. Michielssen, "A butterfly-based direct solver using hierarchical LU factorization for Poggio-Miller-Chang-Harrington-Wu-Tsai equations", Microwave and Optical Technology Letters, 2018, 60:1381-1387,

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Yang Liu, Mathias Jacquelin, Pieter Ghysels, Xiaoye S Li, "Highly scalable distributed-memory sparse triangular solution algorithms", 2018 Proceedings of the Seventh SIAM Workshop on Combinatorial Scientific Computing, 2018, 87--96,

Kesheng Wu, Surendra Byna, Bin Dong, others, VPIC IO utilities, 2018,

JR Stevens, N Goeckner-Wald, R Keskitalo, N McCallum, A Ali, J Borrill, ML Brown, Y Chinone, PA Gallardo, A Kusaka, AT Lee, J McMahon, MD Niemack, L Page, G Puglisi, M Salatino, SYD Mak, G Teply, DB Thomas, EM Vavagiakis, EJ Wollack, Z Xu, N Zhu, "Designs for next generation CMB survey strategies from Chile", Proceedings of SPIE - The International Society for Optical Engineering, 2018, 10708, doi: 10.1117/12.2313898

M Driscoll, B Brock, F Ong, J Tamir, HY Liu, M Lustig, A Fox, K Yelick, Indigo: A domain-specific language for fast, portable image reconstruction, Proceedings - 2018 IEEE 32nd International Parallel and Distributed Processing Symposium, IPDPS 2018, Pages: 495--504 2018, doi: 10.1109/IPDPS.2018.00059

E Georganas, R Egan, SA Hofmeyr, E Goltsman, B Arndt, A Tritt, A Buluç, L Oliker, KA Yelick, Extreme scale de novo metagenome assembly., SC, Pages: 10:1--10:1 2018,

Knut Sverdrup, Nikolaos Nikiforakis, Ann S. Almgren, "Highly parallelisable simulations of time-dependent viscoplastic fluid flow simulations with structured adaptive mesh refinement", Physics of Fluids, 30:9, 2018,

K.-S. Kim, M.H. Han, C. Kim, Z. Li, G.E. Karniadakis, E.K. Lee, "Nature of intrinsic uncertainties in equilibrium molecular dynamics estimation of shear viscosity for simple and complex fluids", J. Chem. Phys. 149, 044510, 2018,

E. Motheau, M. Duarte, A. Almgren, J. Bell,, "A Hybrid Adaptive Low-Mach-Number/Compressible Method: Euler Equations", J. Comp. Phys., Vol 372, Pages 1027-1047, 2018,

J Atalaya, S Hacohen-Gourgy, LS Martin, I Siddiqi, AN Korotkov, "Multitime correlators in continuous measurement of qubit observables", Physical Review A, 2018, 97, doi: 10.1103/PhysRevA.97.020104

A. Donev, C.-Y. Yang, C. Kim, "Efficient reactive Brownian dynamics", J. Chem. Phys. 148, 034103, 2018,

J Atalaya, S Hacohen-Gourgy, LS Martin, I Siddiqi, AN Korotkov, "Correlators in simultaneous measurement of non-commuting qubit observables", npj Quantum Information, 2018, 4, doi: 10.1038/s41534-018-0091-1

D. J. Gardner, J. E. Guerra, F. P. Hamon, D. R. Reynolds, P. A. Ullrich, C. S. Woodward, "Implicit-Explicit Runge-Kutta Methods for Non-Hydrostatic Atmospheric Models", Geosci. Model Dev., 11(4), pp 1497-1515, 2018,

F. P. Hamon, B. T. Mallison, H. A. Tchelepi, "Implicit Hybrid Upwinding for Two-Phase Flow in Heterogeneous Porous Media with Buoyancy and Capillarity", omput. Methods in Appl. Mech. Eng., 331, pp 701-727, 2018,

C Imes, S Hofmeyr, H Hofmann, "Energy-efficient application resource scheduling using machine learning classifiers", ACM International Conference Proceeding Series, 2018, doi: 10.1145/3225058.3225088

L Di Tucci, D Conficconi, A Comodi, S Hofmeyr, D Donofrio, MD Santambrogio, "A parallel, energy efficient hardware architecture for the merAligner on FPGA using chisel HCL", Proceedings - 2018 IEEE 32nd International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2018, 2018, 214--217, doi: 10.1109/IPDPSW.2018.00041

JI Colless, VV Ramasesh, D Dahlen, MS Blok, ME Kimchi-Schwartz, JR McClean, J Carter, WA De Jong, I Siddiqi, "Computation of Molecular Spectra on a Quantum Processor with an Error-Resilient Algorithm", Physical Review X, 2018, 8, doi: 10.1103/PhysRevX.8.011021

RM Richard, C Bertoni, JS Boschen, K Keipert, B Pritchard, EF Valeev, RJ Harrison, WA De Jong, TL Windus, "Developing a Computational Chemistry Framework for the Exascale Era", Computing in Science and Engineering, 2018, doi: 10.1109/MCSE.2018.2884921

JK Gibson, WA de Jong, MJ van Stipdonk, J Martens, G Berden, J Oomens, "Equatorial coordination of uranyl: Correlating ligand charge donation with the O<inf>yl</inf>-U-O<inf>yl</inf> asymmetric stretch frequency", Journal of Organometallic Chemistry, 2018, 857:94--100, doi: 10.1016/j.jorganchem.2017.10.010

Huibin Chang, Stefano Marchesini, "Denoising Poisson phaseless measurements via orthogonal dictionary learning", Optics express, 2018, 26:19773--197,

Huibin Chang, Pablo Enfedaque, Yifei Lou, Stefano Marchesini, "Partially Coherent Ptychography by Gradient Decomposition of the Probe", Acta Cryst. A74, 2018, 157-169,

P Enfedaque, H Chang, H Krishnan, S Marchesini, "GPU-based implementation of ptycho-ADMM for high performance x-ray imaging", Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2018, 10860 LN:540--553, doi: 10.1007/978-3-319-93698-7_41

Huibin Chang, Yifei Lou, Yuping Duan, Stefano Marchesini, "Total Variation--Based Phase Retrieval for Poisson Noise Removal", SIAM Journal on Imaging Sciences, 2018, 11:24--55,

Huibin Chang, Stefano Marchesini, Yifei Lou, Tieyong Zeng, "Variational phase retrieval with globally convergent preconditioned proximal algorithm", SIAM Journal on Imaging Sciences, 2018, 11:56--93,

Yao Lu, Nelson Leung, Srivatsan Chakram, Ravi Naik, Nathan Earnest, Robert Cook, Kurt Jacobs, Andrew Cleland, David Schuster, Remote communication between two superconducting qubit modules 2, APS March Meeting Abstracts, Pages: F39--005 2018,

YS Yu, M Farmand, C Kim, Y Liu, CP Grey, FC Strobridge, T Tyliszczak, R Celestre, P Denes, J Joseph, H Krishnan, FRNC Maia, ALD Kilcoyne, S Marchesini, TPC Leite, T Warwick, H Padmore, J Cabana, DA Shapiro, Three-dimensional localization of nanoscale battery reactions using soft X-ray tomography, Nature Communications, 2018, doi: 10.1038/s41467-018-03401-x

M Minion, S Goetschel, "Parallel-in-Time for Parabolic Optimal Control Problems Using PFASST", Domain Decomposition Methods in Science and Engineering XXIV, (Springer: 2018)

Nathan Earnest, Srivatsan Chakram, Yao Lu, Nicholas Irons, Ravi K Naik, Nelson Leung, Leo Ocola, David A Czaplewski, Brian Baker, Jay Lawrence, others, "Realization of a $\Lambda$ system with metastable states of a capacitively shunted fluxonium", Physical Review Letters, 2018, 120:150504, doi: 10.1103/PhysRevLett.120.150504

GP Rodrigo, M Henderson, GH Weber, C Ophus, K Antypas, L Ramakrishnan, "ScienceSearch: Enabling Search through Automatic Metadata Generation", 2018 IEEE 14th International Conference on e-Science (e-Science), IEEE, 2018, doi: 10.1109/escience.2018.00025

Victor Wen-zhe Yu, Fabiano Corsetti, Alberto Garcia, William P Huhn, Mathias Jacquelin, Weile Jia, Bjorn Lange, Lin Lin, Jianfeng Lu, Wenhui Mi, others, "ELSI: A unified software interface for Kohn--Sham electronic structure solvers", Computer Physics Communications, 2018, 222:267--285,

Xin Xing, Bin Dong, Jonathan Ajo-Franklin, Kesheng Wu, "Automated Parallel Data Processing Engine with Application to Large-Scale Feature Extraction", 2018 IEEE/ACM Machine Learning in HPC Environments (MLHPC), January 1, 2018, 37--46,

Bin Dong, Teng Wang, Houjun Tang, Quincey Koziol, Kesheng Wu, Suren Byna, "ARCHIE: Data analysis acceleration with array caching in hierarchical storage", 2018 IEEE International Conference on Big Data (Big Data), January 1, 2018, 211--220,

Srivatsan Chakram, RK Naik, Nelson Leung, Yao Lu, Akash Dixit, Nathan Earnest, Peter Groszkowski, David McKay, Jens Koch, David Schuster, Random access quantum information processing in multimode cavities 2, APS March Meeting Abstracts, Pages: A33--005 2018,

William Huhn, Alberto Garcia, Luigi Genovese, Ville Havu, Mathias Jacquelin, Weile Jia, Murat Keceli, Raul Laasner, Yingzhou Li, Lin Lin, others, "Unified Access To Kohn-Sham DFT Solvers for Different Scales and HPC: The ELSI Project", Bulletin of the American Physical Society, American Physical Society, 2018,

Mathias Jacquelin, Lin Lin, Chao Yang, "PSelInv--A distributed memory parallel algorithm for selected inversion: The non-symmetric case", Parallel Computing, 2018, 74:84--98,

Peter Groszkowski, Srivatsan Chakram, Ravi Naik, Nelson Leung, Yao Lu, David Schuster, Jens Koch, Quantum information processing with multimode cavity systems using parametrically modulated components, APS March Meeting Abstracts, Pages: P33--005 2018,

Akash Dixit, S Chakram, R Naik, A Agrawal, J Kudler-Flam, A Chou, DI Schuster, Searching for Axion Dark Matter using Superconducting Qubits, APS March Meeting Abstracts, Pages: P39--012 2018,

Grey Ballard, James Demmel, Laura Grigori, Mathias Jacquelin, Nicholas Knight, "A 3D Parallel Algorithm for QR Decomposition", SPAA '18, 2018,

DC Miller, JD Siirola, D Agarwal, AP Burgard, A Lee, JC Eslick, B Nicholson, C Laird, LT Biegler, D Bhattacharyya, NV Sahinidis, IE Grossmann, CE Gounaris, D Gunter, "Next Generation Multi-Scale Process Systems Engineering Framework", Computer Aided Chemical Engineering, 2018, 44:2209--2214, doi: 10.1016/B978-0-444-64241-7.50363-3

Mathias Jacquelin, Esmond G Ng, Barry W Peyton, "Fast and effective reordering of columns within supernodes using partition refinement", 2018 Proceedings of the Seventh SIAM Workshop on Combinatorial Scientific Computing, 2018, 76--86,

Ravi Naik, Srivatsan Chakram, Akash Dixit, Nelson Leung, Yao Lu, Nathan Earnest, Carolyn Zhang, Peter Groszkowski, David McKay, Jens Koch, others, Random access quantum information processing in multimode cavities 1, APS March Meeting Abstracts, Pages: A33--004 2018,

Nelson Leung, Yao Lu, Srivatsan Chakram, Ravi Naik, Nathan Earnest, Robert Cook, Kurt Jacobs, Andrew Cleland, David Schuster, Remote communication between two superconducting qubit modules 1, APS March Meeting Abstracts, Pages: F39--004 2018,

Ankur Agrawal, Akash Dixit, Srivatsan Chakram, Ravi Naik, Jonah Kudler-Flam, Aaron Chou, David I Schuster, ADMX Collaboration, others, Axion Dark Matter Detection using Superconducting Qubits, APS April Meeting Abstracts, Pages: X09--004 2018,

Mathias Jacquelin, Lin Lin, Weile Jia, Yonghua Zhao, Chao Yang, "A Left-Looking Selected Inversion Algorithm and Task Parallelism on Shared Memory Systems", Proceedings of the International Conference on High Performance Computing in Asia-Pacific Region, January 1, 2018, 54--63,

RK Naik, N Leung, S Chakram, Peter Groszkowski, Y Lu, N Earnest, DC McKay, Jens Koch, DI Schuster, Publisher Correction: Random access quantum information processors using multimode circuit quantum electrodynamics, Nature communications, Pages: 1--1 2018,

H. Hiss, M. Walther, J. F. Hennawi, J. Onorbe, J. M. O\rsquoMeara, A. Rorai, Z. Lukic, "A New Measurement of the Temperature\ndashdensity Relation of the IGM from Voigt Profile Fitting", Astrophysical Journal, 2018, 865:42, doi: 10.3847/1538-4357/aada86

F. B. Davies, J. F. Hennawi, E. Banados, Z., R. Decarli, X. Fan, E. P. Farina, C., H.-W. Rix, B. P. Venemans, F. Walter, F. Wang, J. Yang, "Quantitative Constraints on the Reionization History from the IGM Damping Wing Signature in Two Quasars at z > 7", The Astrophysical Journal, 2018, 864:142, doi: 10.3847/1538-4357/aad6dc

Nathan Earnest, Srivatsan Chakram, Yao Lu, Nicholas Irons, Ravi Naik, Nelson Leung, Leonidas Ocola, David Czaplewski, Brian Baker, Walter Lawrence, others, Raman Transitions in a Capacitively shunted Fluxonium Circuit, APS March Meeting Abstracts, Pages: L33--010 2018,

V. Khaire, M. Walther, J. F. Hennawi, J. O\ norbe, Z., J. X. Prochaska, T. M. Tripp, J. N. Burchett, C. Rodriguez, The Power Spectrum of the Lyman-$\alpha$ Forest at z $\lt$ 0.5, arXiv e-prints, 2018,

T. M. Schmidt, J. F. Hennawi, G. Worseck, F. B. Davies, Z. Lukic, J. Onorbe, "Modeling the He II Transverse Proximity Effect: Constraints on Quasar Lifetime and Obscuration", Astrophysical Journal, 2018, 861:122, doi: 10.3847/1538-4357/aac8e4

D. Sorini, J. Onorbe, J. F. Hennawi, Z. Lukic, "A Fundamental Test for Galaxy Formation Models: Matching the Lyman-$\alpha$ Absorption Profiles of Galactic Halos Over Three Decades in Distance", Astrophysical Journal, 2018, 859:125, doi: 10.3847/1538-4357/aabb52

Y.-Y. Mao, E. Kovacs, K. Heitmann, T. D. Uram, A. J., D. Campbell, S. A. Cora, J. DeRose, T. Matteo, S. Habib, A. P. Hearin, J. Bryce Kalmbach, K. S., F. Lanusse, Z. Lukic, R., J. A. Newman, N. Padilla, E. Paillas, A., P. M. Ricker, A. N. Ruiz, A. Tenneti, C. A., R. H. Wechsler, R. Zhou, Y. Zu, LSST Dark Energy Science Collaboration, "DESCQA: An Automated Validation Framework for Synthetic Sky Catalogs", Astrophysical Journal Supplement, 2018, 234:36, doi: 10.3847/1538-4365/aaa6c3

Gunther H. Weber, Colin Ophus, Lavanya Ramakrishnan, "Automated Labeling of Electron Microscopy Images Using Deep Learning", Proc. IEEE/ACM Machine Learning in HPC Environments (MLHPC), 2018, 26--36, doi: 10.1109/MLHPC.2018.8638633

Multimode Circuit Quantum Electrodynamics, Ravi Kaushik Naik, PhD, 2018, doi: 10.6082/uchicago.1391

D. Broberg, B. Medasani, N.E.R. Zimmermann, G. Yu, A. Canning, M. Haranczyk, M. Asta, G. Hautier, "PyCDT: A Python toolkit for modeling point defects in semiconductors and insulators", Computer Physics Communications, 2018, 226:165-179, doi: 10.1016/j.cpc.2018.01.004

EM Stewart, P Top, M Chertkov, D Deka, S Backhaus, A Lokhov, C Roberts, V Hendrix, S Peisert, A Florita, TJ King, MJ Reno, "Integrated multi-scale data analytics and machine learning for the distribution grid", 2017 IEEE International Conference on Smart Grid Communications, SmartGridComm 2017, 2018, 2018-Jan:423--429, doi: 10.1109/SmartGridComm.2017.8340693

B Faybishenko, F Molz, D Agarwal, "Nonlinear dynamics simulations of microbial ecological processes: Model, diagnostic parameters of deterministic chaos, and sensitivity analysis", Springer Proceedings in Mathematics and Statistics, ( 2018) Pages: 437--465 doi: 10.1007/978-3-030-02825-1_19

C. E. Harris, P. E. Nugent, A. Horesh, J. S. Bright, R. P. Fender, M. L. Graham, K. Maguire, M. Smith, N. Butler, S. Valenti, A. V. Filippenko, O. Fox, A. Goobar, P. L. Kelly, K. J. Shen, Don\textquoterightt Blink: Constraining the Circumstellar Environment of the Interacting Type Ia Supernova 2015cp, Astrophysical Journal, Pages: 21 2018, doi: 10.3847/1538-4357/aae521

Tom Liebmann, Gunther H. Weber, Gerik Scheuermann, "Hierarchical Correlation Clustering in Multiple 2D Scalar Fields", Computer Graphics Forum (Special Issue, Proceedings Symposium on Visualization), 2018, 37, doi: 10.1111/cgf.13396

Khee-Gan Lee, Alex Krolewski, Martin White, David Schlegel, Peter E. Nugent, Joseph F. Hennawi, Thomas M\ uller, Richard Pan, J. Xavier Prochaska, Andreu Font-Ribera, Nao Suzuki, Karl Glazebrook, Glenn G. Kacprzak, Jeyhan S. Kartaltepe, Anton M. Koekemoer, Olivier Le F\ evre, Brian C. Lemaux, Christian Maier, Themiya Nanayakkara, R. Michael Rich, D. B. Sanders, Mara Salvato, Lidia Tasca, Kim-Vy H. Tran, First Data Release of the COSMOS Ly\ensuremath\alpha Mapping and Tomography Observations: 3D Ly\ensuremath\alpha Forest Tomography at 2.05 < z < 2.55, Astrophysical Journal Supplement, Pages: 31 2018, doi: 10.3847/1538-4365/aace58

K Beketayev, D Yeliussizov, D Morozov, GH Weber, B Hamann, "Measuring the Error in Approximating the Sub-Level Set Topology of Sampled Scalar Data", International Journal of Computational Geometry and Applications, 2018, 28:57--77, doi: 10.1142/S0218195918500036

Alex Krolewski, Khee-Gan Lee, Martin White, Joseph F. Hennawi, David J. Schlegel, Peter E. Nugent, Zarija Luki\ c, Casey W. Stark, Anton M. Koekemoer, Olivier Le F\ evre, Brian C. Lemaux, Christian Maier, R. Michael Rich, Mara Salvato, Lidia Tasca, Detection of z \ensuremath\sim 2.3 Cosmic Voids from 3D Ly\ensuremath\alpha Forest Tomography in the COSMOS Field, Astrophysical Journal, Pages: 60 2018, doi: 10.3847/1538-4357/aac829

M. Rigault, Y. Copin, G. Aldering, P. Antilogus, C. Aragon, S. Bailey, C. Baltay, S. Bongard, C. Buton, A. Canto, F. Cellier-Holzem, M. Childress, N. Chotard, H. K. Fakhouri, U. Feindt, M. Fleury, E. Gangler, P. Greskovic, J. Guy, A. G. Kim, M. Kowalski, S. Lombardo, J. Nordin, P. Nugent, R. Pain, E. P\ econtal, R. Pereira, S. Perlmutter, D. Rabinowitz, K. Runge, C. Saunders, R. Scalzo, G. Smadja, C. Tao, R. C. Thomas, B. A. Weaver, Nearby Supernova Factory, Evidence of environmental dependencies of Type Ia supernovae from the Nearby Supernova Factory indicated by local H\ensuremath\alpha (Corrigendum), Astronomy and Astrophysics, Pages: C1 2018, doi: 10.1051/0004-6361/201322104e

Taehoon Kim, Jaesik Choi, Dongeun Lee, Alex Sim, C Anna Spurlock, Annika Todd, Kesheng Wu, "Predicting baseline for analysis of electricity pricing", International Journal of Big Data Intelligence, 2018, 5:3--20,

S Swaid, M Maat, H Krishnan, D Ghoshal, L Ramakrishnan, "Usability heuristic evaluation of scientific data analysis and visualization tools", Advances in Intelligent Systems and Computing, 2018, 607:471--482, doi: 10.1007/978-3-319-60492-3_45

2017

B Mohammed, S Moyo, KM Maiyama, S Kinteh, ANMK Al-Shaidy, MA Kamala, M Kiran, "Technical Report on Deploying a highly secured OpenStack Cloud Infrastructure using BradStack as a Case Study", 2017,

George Michelogiannakis, John Shalf, "Last Level Collective Hardware Prefetching For Data-Parallel Applications", IEEE 24th International Conference on High Performance Computing, IEEE, December 2017,

George Michelogiannakis, John Shalf, Last Level Collective Hardware Prefetching For Data-Parallel Applications, IEEE 24th International Conference on High Performance Computing, December 18, 2017,

Shashanka Ubaru, Kesheng Wu, Kristofer E. Bouchard, "UoI-NMF Cluster: A Robust Nonnegative Matrix Factorization Algorithm for Improved Parts-Based Decomposition and Reconstruction of Noisy Data", the 16th IEEE International Conference on Machine Learning and Applications (ICMLA 2017), 2017, 241-248, doi: 10.1109/ICMLA.2017.0-152

John Bachan, Scott Baden, Dan Bonachea, Paul Hargrove, Steven Hofmeyr, Khaled Ibrahim, Mathias Jacquelin, Amir Kamil, Brian Van Straalen, "UPC++: a PGAS C++ Library", The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC'17) Research Poster, November 2017,

Glenn Lockwood, Shane Snyder, Wucherl Yoo, Kevin Harms, Zachary Nault, Suren Byna, Philip Carns, Nicholas Wright, "UMAMI: A Recipe for Generating Meaningful Metrics through Holistic I/O Performance Analysis", 2nd Joint International Workshop on Parallel Data Storage & Data Intensive Scalable Computing Systems (PDSW-DISCS), 2017 (Held in conjunction with SC17), November 14, 2017,

Brian Van Straalen, David Trebotich, Andrey Ovsyannikov, Daniel T. Graves, "Scalable Structured Adaptive Mesh Refinement with Complex Geometry", Exascale Scientific Applications: Scalability and Performance Portability, edited by Tjerk P. Straatsma, Katerina B. Antypas, Timothy J. Williams, (Chapman and Hall/CRC: November 13, 2017) doi: 10.1201/b21930

John Bachan, Dan Bonachea, Paul H Hargrove, Steve Hofmeyr, Mathias Jacquelin, Amir Kamil, Brian van Straalen, Scott B Baden, "The UPC++ PGAS library for Exascale Computing", Proceedings of the Second Annual PGAS Applications Workshop (PAW17), November 13, 2017, doi: 10.1145/3144779.3169108

We describe UPC++ V1.0, a C++11 library that supports APGAS programming. UPC++ targets distributed data structures where communication is irregular or fine-grained. The key abstractions are global pointers, asynchronous programming via RPC, and futures. Global pointers incorporate ownership information useful in optimizing for locality. Futures capture data readiness state, are useful for scheduling and also enable the programmer to chain operations to execute asynchronously as high-latency dependencies become satisfied, via continuations. The interfaces for moving non-contiguous data and handling memories with different optimal access methods are composable and closely resemble those used in modern C++. Communication in UPC++ runs at close to hardware speeds by utilizing the low-overhead GASNet-EX communication library.

E. Georganas, S. Hofmeyr, L. Oliker, R. Egan, D. Rokhsar, A. Buluc, K. Yelick, "Extreme-scale de novo genome assembly", Exascale Scientific Applications: Scalability and Performance Portability, edited by T.P. Straatsma, K. B. Antypas, T. J. Williams, ( November 13, 2017) doi: https://doi.org/10.1201/b21930

Erik Paulson, Dan Bonachea, Paul Hargrove, GASNet ofi-conduit, Presentation at the Open Fabrics Interface BoF at Supercomputing 2017, November 2017,

Haohuan Fu, Junfeng Liao, Nan Ding, Xiaohui Duan, Lin Gan,Yishuang Liang,Xinliang Wang,Jinzhe Yang,Yan Zheng,Weiguo Liu,Lanning Wang,Guangwen Yang, "Redesigning CAM-SE for peta-scale climate modeling performance and ultra-high resolution on Sunway TaihuLight (ACM Gordon Bell Prize Finalist)", SC'17, November 12, 2017,

Yang You, Aydin Buluc, James Demmel, "Scaling deep learning on GPU and Knights Landing clusters", Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC'17), 2017,

Samuel Williams, Introduction to the Roofline Model, Roofline Training, November 2017,

B. Van Straalen, D. Trebotich, A. Ovsyannikov and D.T. Graves, "Scalable Structured Adaptive Mesh Refinement with Complex Geometry", Exascale Scientific Applications: Programming Approaches for Scalability, Performance, and Portability, edited by Straatsma, T., Antypas, K., Williams, T., (Chapman and Hall/CRC: November 9, 2017)

E. J. Bylaska, E. Apra, K. Kowalski, M. Jacquelin, W.A. de Jong, A. Vishnu, B. Palmer, J. Daily, T.P. Straatsma, J.R. Hammond, M. Klemm, "Transitioning NWChem to the Next Generation of Many Core Machines", Exascale Scientific Applications Scalability and Performance Portability, edited by Tjerk P. Straatsma, Katerina B. Antypas, Timothy J. Williams, (Taylor & Francis: November 9, 2017)

David Hatchell, Patrick Miller, Michael Coleman, Sean Peisert, Cybersecurity for the Electricity Grid", Bits & Watts Annual Conference, November 6, 2017,

Tze Meng Low, Varun Nagaraj Rao, Matthew Lee, Doru Thom Popovici, Franz Franchetti Scott McMillan, "First look: Linear algebra-based triangle counting without matrix multiplication", HPEC, 2017,

Doru Thom Popovici, Franz Franchetti, Tze Meng Low, "Mixed data layout kernels for vectorized complex arithmetic", HPEC, 2017,

Colin A. MacLean, HonWai Leong, Jeremy Enos, "Improving the start-up time of python applications on large scale HPC systems", Proceedings of HPCSYSPROS 2017, Denver, CO, November 2017, doi: 10.1145/3155105.3155107

N. Sanderson, E. Shugerman, S. Molnar, J. Meiss E. Bradley, "Computational Topology Techniques for Characterizing Time-Series Data", Advances in Intelligent Data Analysis XVI 16th International Symposium, IDA 2017, London, UK, October 26–28, 2017, Proceedings, October 2017, pp.284-296, doi: 10.1007/978-3-319-68765-0_24

Topological data analysis (TDA), while abstract, allows a characterization of time-series data obtained from nonlinear and complex dynamical systems. Though it is surprising that such an abstract measure of structure—counting pieces and holes—could be useful for real-world data, TDA lets us compare different systems, and even do membership testing or change-point detection. However, TDA is computationally expensive and involves a number of free parameters. This complexity can be obviated by coarse-graining, using a construct called the witness complex. The parametric dependence gives rise to the concept of persistent homology: how shape changes with scale. Its results allow us to distinguish time-series data from different systems—e.g., the same note played on different musical instruments.

Philip C. Roth, Hongzhang Shan, David Riegner, Nikolas Antolin, Sarat Sreepathi, Leonid Oliker, Samuel Williams, Shirley Moore, Wolfgang Windl, "Performance Analysis and Optimization of the RAMPAGE Metal Alloy Potential Generation Software", SIGPLAN International Workshop on Software Engineering for Parallel Systems (SEPS), October 2017,

E.J. Bylaska, J. Hammond, M. Jacquelin, W.A. de Jong, M. Klemm, "Performance Evaluation of NWChem Ab-Initio Molecular Dynamics (AIMD) Simulations on the Intel® Xeon Phi© Processor", High Performance Computing. ISC High Performance 2017. Lecture Notes in Computer Science, Springer, Cham, October 21, 2017, 404-418, doi: 10.1007/978-3-319-67630-2_30

Shreyas Cholia, Matthew Henderson, Oliver Evans, Demo: Extending Jupyter to Support Interactive High Performance Computing, Science Gateways 2017, October 2017, doi: 10.6084/m9.figshare.5501137.v1

Patricia Gonzalez-Guerrero, Mircea Stan, "Ultra-low-power dual-phase latch based digital accelerator for continuous monitoring of wheezing episodes", SOI-3D-Subthreshold Microelectronics Technology Unified Conference (S3S), Burlingame, CA, USA, IEEE, October 16, 2017, doi: 10.1109/S3S.2017.8308752

We designed an ultra-low-power accelerator for the calculation of the Short Time Fourier Transform (STFT) optimized for wheezing detection. The low power consumption of our accelerator relies on optimizations at different stages of the design process. Post-layout simulations show that at the minimum energy point our accelerator consumes 3.3 pJ/cycle at 0.5 V and 163 KHz. We compare the energy consumption of our implementation with its flip-flop version. Simulations show that we can save up to 50% in energy consumption for a latch based design vs. a flip-flop based design, making dual-phase latch based implementations excellent candidates for ultra-low-power devices.

W. Hu, L. Lin, R. Zhang, C. Yang, J. Yang, "Highly efficient photocatalytic water splitting over edge-modified phosphorene nanoribbons", J. Am. Chem. Soc., October 13, 2017, 139:15429–1543, doi: 10.1021/jacs.7b08474

Lorenzo Di Tucci, Giulia Guidi, Sara Notargiacomo, Luca Cerina, Alberto Scolari, Marco D. Santambrogio, "HUGenomics: A Support to Personalized Medicine Research", 2017 IEEE 3rd International Forum on Research and Technologies for Society and Industry (RTSI), October 12, 2017,

Sean Peisert, Security in High Performance Computing Environments, Computing Sciences/NERSC Security Seminar, October 5, 2017,

Meiyue Shao and Chao Yang, "Properties of Definite Bethe--Salpeter Eigenvalue Problems", Eigenvalue Problems: Algorithms, Software and Applications in Petascale Computing. EPASA 2015. Lecture Notes in Computational Science and Engineering, vol 117., 2017, 91--105, doi: 10.1007/978-3-319-62426-6_7

Sean Peisert, Matt Bishop, Ed Talbot,, "A Model of Owner Controlled, Full-Provenance, Non-Persistent, High-Availability Information Sharing", Proceedings of the 2017 New Security Paradigms Workshop (NSPW), Santa Cruz, CA, October 2017, 80-89, doi: 10.1145/3171533.3171536

Sean Peisert, Security and Privacy in Data-Intensive, High-Performance Computing Contexts, Berkeley Institute for Data Science (BIDS), October 2, 2017,

Jean-Philippe Peraud, Andrew J. Nonaka, John B. Bell, Aleksandar Donev, Alejandro L. Garcia, "Fluctuation-enhanced electric conductivity in electrolyte solutions", Proceedings of the National Academy of Sciences, 2017, 114:10829--108, doi: 10.1073/pnas.1714464114

John Bachan, Scott Baden, Dan Bonachea, Paul Hargrove, Steven Hofmeyr, Khaled Ibrahim, Mathias Jacquelin, Amir Kamil, Brian van Straalen, "UPC++ Programmer’s Guide, v1.0-2017.9", Lawrence Berkeley National Laboratory Tech Report, September 2017, LBNL 2001065, doi: 10.2172/1398522

UPC++ is a C++11 library that provides Asynchronous Partitioned Global Address Space (APGAS) programming. It is designed for writing parallel programs that run efficiently and scale well on distributed-memory parallel computers. The APGAS model is single program, multiple-data (SPMD), with each separate thread of execution (referred to as a rank, a term borrowed from MPI) having access to local memory as it would in C++. However, APGAS also provides access to a global address space, which is allocated in shared segments that are distributed over the ranks. UPC++ provides numerous methods for accessing and using global memory. In UPC++, all operations that access remote memory are explicit, which encourages programmers to be aware of the cost of communication and data movement. Moreover, all remote-memory access operations are by default asynchronous, to enable programmers to write code that scales well even on hundreds of thousands of cores.

John Bachan, Scott Baden, Dan Bonachea, Paul H. Hargrove, Steven Hofmeyr, Khaled Ibrahim, Mathias Jacquelin, Amir Kamil, Bryce Lelbach, Brian Van Straalen, "UPC++ Specification v1.0, Draft 4", Lawrence Berkeley National Laboratory Tech Report, September 27, 2017, LBNL 2001066, doi: 10.2172/1398521

UPC++ is a C++11 library providing classes and functions that support Asynchronous Partitioned Global Address Space (APGAS) programming. We are revising the library under the auspices of the DOE’s Exascale Computing Project, to meet the needs of applications requiring PGAS support. UPC++ is intended for implementing elaborate distributed data structures where communication is irregular or fine-grained. The UPC++ interfaces for moving non-contiguous data and handling memories with different optimal access methods are composable and similar to those used in conventional C++. The UPC++ programmer can expect communication to run at close to hardware speeds. The key facilities in UPC++ are global pointers, that enable the programmer to express ownership information for improving locality, one-sided communication, both put/get and RPC, futures and continuations. Futures capture data readiness state, which is useful in making scheduling decisions, and continuations provide for completion handling via callbacks. Together, these enable the programmer to chain together a DAG of operations to execute asynchronously as high-latency dependencies become satisfied.

Matthew S. Barclay, Timothy J. Quincy, David B. Williams-Young, Marco Caricato, Christopher G. Elles, "Accurate Assignments of Excited-State Resonance Raman Spectra: A Benchmark Study Combining Experiment and Theory", Journal of Physical Chemistry A, 2017, 121:7937-7946, doi: 10.1021/acs.jpca.7b09467

Jonathan Ganz, Sean Peisert, "ASLR: How Robust is the Randomness", Proceedings of the IEEE Secure Development Conference (SecDev), Cambridge, MA, IEEE Computer Society, September 24, 2017, doi: 10.1109/SecDev.2017.19

Mahdi Jamei, Anna Scaglione, Ciaran Roberts, Emma Stewart, Sean Peisert, Chuck McParland, Alex McEachern, "Anomaly Detection Using μPMU Measurements in Distribution Grids", IEEE Transactions on Power Systems, 2017, doi: 10.1109/TPWRS.2017.2764882

V. Yu. F. Corsetti, A. García, W. P. Huhn, M. Jacquelin, W. Jia, B. Lange, L. Lin, J. Lu, W. Mi, A. Seifitokaldan, Á. Vazquez-Mayagoitia, C. Yang, H. Yang, V. Blum, "ELSI: A unified software interface for Kohn–Sham electronic structure solvers", Computer Physics Communications, September 7, 2017, 222:267-285, doi: 10.1016/j.cpc.2017.09.007

Houjun Tang, Suren Byna, Bin Dong, Jialin Liu, and Quincey Koziol, "SoMeta: Scalable Object-centric Metadata Management for High Performance Computing", IEEE Cluster 2017, September 5, 2017,

R. Kantharaj, I. Srivastava, K. R. Thaker, A. U. Gaitonde, A. Bruce, J. Howarter, T. S. Fisher, A. M. Marconnet, "Thermal Conduction in Graphite Flake-Epoxy Composites using Infrared Microscopy", 2017 Intersociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems (ITHERM), September 4, 2017, 1-7, doi: 10.1109/ITHERM.2017.8023960

Sean Peisert, "Security in High-Performance Computing Environments", Communications of the ACM (CACM), September 2017, 60(9):72-80, doi: 10.1145/3096742

Xinfei Guo, Vaibhav Verma, Patricia Gonzalez-Guerrero, Sergiu Mosanu, Mircea R Stan, "Back to the future: Digital circuit design in the finfet era", Journal of Low Power Electronics, September 1, 2017, doi: https://doi.org/10.1166/jolpe.2017.1489

It has been almost a decade since FinFET devices were introduced to full production; they allowed scaling below 20 nm, thus helping to extend Moore's law by a precious decade with another decade likely in the future when scaling to 5 nm and below. Due to superior electrical parameters and unique structure, these 3-D transistors offer significant performance improvements and power reduction compared to planar CMOS devices. As we are entering into the sub-10 nm era, FinFETs have become dominant in most of the high-end products; as the transition from planar to FinFET technologies is still ongoing, it is important for digital circuit designers to understand the challenges and opportunities brought in by the new technology characteristics. In this paper, we study these aspects from the device to the circuit level, and we make detailed comparisons across multiple technology nodes ranging from conventional bulk to advanced planar technology nodes such as Fully Depleted Silicon-on-Insulator (FDSOI), to FinFETs. In the simulations we used both state-of-art industry-standard models for current nodes, and also predictive models for future nodes. Our study shows that besides the performance and power benefits, FinFET devices show significant reduction of short-channel effects and extremely low leakage, and many of the electrical characteristics are close to ideal as in old long-channel technology nodes; FinFETs seem to have put scaling back on track! However, the combination of the new device structures, double/multi-patterning, many more complex rules, and unique thermal/reliability behaviors are creating new technical challenges. Moving forward, FinFETs still offer a bright future and are an indispensable technology for a wide range of applications from high-end performance-critical computing to energy-constraint mobile applications and smart Internet-of-Things (IoT) devices.

Jose Oñorbe, Joseph F. Hennawi, Zarija Lukić, and Michael Walther, "Constraining Reionization with the z ~ 5-6 Lyman-alpha Forest Power Spectrum: the Outlook after Planck", The Astrophysical Journal, 2017,

R. Van Beeumen, D.B. Williams-Young, J.M. Kasper, C. Yang, E.G. Ng, X. Li, "Model order reduction algorithm for estimating the absorption spectrum", Journal of Chemical Theory and Computation, 2017, 13:4950-4961, doi: 10.1021/acs.jctc.7b00402

Dan Bonachea, Paul Hargrove, "GASNet Specification, v1.8.1", Lawrence Berkeley National Laboratory Tech Report, August 31, 2017, LBNL 2001064, doi: 10.2172/1398512

GASNet is a language-independent, low-level networking layer that provides network-independent, high-performance communication primitives tailored for implementing parallel global address space SPMD languages and libraries such as UPC, UPC++, Co-Array Fortran, Legion, Chapel, and many others. The interface is primarily intended as a compilation target and for use by runtime library writers (as opposed to end users), and the primary goals are high performance, interface portability, and expressiveness. GASNet stands for "Global-Address Space Networking".

Muammar El Khatib, Alireza Khorshidi, Andrew A Peterson, Acceleration of Saddle-Point Searches Assisted by Machine Learning, 68 th Annual Meeting of the International Society of Electro-chemistry, August 31, 2017,

Frederick B. Davies, Joseph F. Hennawi, Anna-Christina Eilers, and Zarija Lukić, "A New Method to Measure the Post-Reionization Ionizing Background from the Joint Distribution of Lyman-α and Lyman-β Forest Transmission", The Astrophysical Journal, 2017,

Jack Deslippe, Doug Doerfler, Brandon Cook, Tareq Malas, Samuel Williams, Sudip Dosanjh, "Optimizing science applications for the Cori, Knights Landing, System at NERSC", Advances in Parallel Computing, New Frontiers in High Performance Computing and Big Data, August 2017, 30, doi: 10.3233/978-1-61499-816-7-235

Daniel Martin, Stephen Cornford, Antony Payne, Millennial-Scale Vulnerability of the Antarctic Ice Sheet to localized subshelf warm-water forcing, International Symposium on Polar Ice, Polar Climate, Polar Change, August 18, 2017,

Seher Acer, R. Oguz Selvitopi, Cevdet Aykanat, "Addressing Volume and Latency Overheads in 1D-parallel Sparse Matrix-Vector Multiplication", European Conference on Parallel Processing (Euro-Par), Springer, August 2017, 625-637, doi: 10.1007/978-3-319-64203-1_45

J Muller, "SOCEMO: Surrogate Optimization of Computationally Expensive Multiobjective Problems", INFORMS Journal on Computing, July 31, 2017, 29:581-596,

Jinoh Kim, Alex Sim, "A New Approach to Online, Multivariate Network Traffic Analysis", 2nd Workshop on Network Security Analytics and Automation (NSAA), in conjunction with the 26th International Conference on Computer Communications and Networks (ICCCN 2017), 2017, doi: 10.1109/ICCCN.2017.8038520

Alireza Khorshidi, Muammar El Khatib, Andrew A Peterson*, Amp: The Atomistic Machine-learning Package v0.6, https://bitbucket.org/andrewpeterson/amp, July 31, 2017,