Careers | Phone Book | A - Z Index

2019 Publications


A. Syal, A. Lazar, J. Kim, K. Wu, A. Sim, "Automatic Detection of Network Traffic Anomalies and Changes", the 2nd International Workshop on Systems and Network Telemetry and Analytics (SNTA 2019), in conjunction with ACM International Symposium on High-Performance Parallel and Distributed Computing (HPDC 2019), 2019, doi: 10.1145/3322798.3329255

O. Del Guercio, R. Orozco, A. Sim, K. Wu, "Similarity-based Compression with Multidimensional Pattern Matching", the 2nd International Workshop on Systems and Network Telemetry and Analytics (SNTA 2019), in conjunction with ACM International Symposium on High-Performance Parallel and Distributed Computing (HPDC 2019), 2019, doi: 10.1145/3322798.3329252

M. jin, Y. Homma, A. Sim, W. Kroeger, K. Wu, "Performance Prediction for Data Transfers in LCLS Workflow", the 2nd International Workshop on Systems and Network Telemetry and Analytics (SNTA 2019), in conjunction with ACM International Symposium on High-Performance Parallel and Distributed Computing (HPDC 2019), 2019, doi: 10.1145/3322798.3329254

H. Sung, J. Bang, A. Sim, K. Wu, H. Eom, "Understanding Parallel I/O Performance Trends Under Various HPC Configurations", the 2nd International Workshop on Systems and Network Telemetry and Analytics (SNTA 2019), in conjunction with ACM International Symposium on High-Performance Parallel and Distributed Computing (HPDC 2019), 2019, doi: 10.1145/3322798.3329258

Bin Dong, Kesheng Wu, Suren Byna, Houjun Tang, "SLOPE: Structural Locality-aware Programming Model for Composing Array Data Analysis", ISC 2019 ((Acceptance rate:24%),), June 16, 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", IEEE International Conference on Fog and Mobile Edge Computing (FMEC2019), 2019,

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.

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,

Weiqun Zhang, Ann Almgren, Vince Beckner, John Bell, Johannes Blashke, Cy Chan, Marcus Day, Brian Friesen, Kevin Gott, Daniel Groves, 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

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,

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

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, May 2019, doi: 10.1093/mnras/stz1220

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

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

Sean Peisert, "Some Experiences in Developing Security Technology That Actually Get Used", IEEE Security & Privacy, April 2019, 17(2):4–7, doi: 10.1109/MSEC.2019.2899711

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

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

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

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,

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 15, 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.

A. Lazar, L. Jin, C. A. Spurlock, K. Wu, A. Sim, A. Todd, "Evaluating the Effects of Missing Values and Mixed Data Types on Social Sequence Clustering Using t-SNE Visualization", ACM Journal of Data and Information Quality, 2019, 11:7:1-7:22, doi: 10.1145/3301294

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,

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

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:

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:

Beytullah Yildiz, Kesheng Wu, Suren Byna, and Arie Shoshani, "Parallel membership queries on very large scientific data sets using bitmap indexes", Concurrency and Computation: Practice and Experience, January 28, 2019,

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,

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

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

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:

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

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

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

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

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, January 9, 2019,

Screen Shot 2019 02 25 at 8.59.45 AM

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


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.

C. Varadharajan, S. Cholia, C. Snavely, V. Hendrix, C. Procopiou, D. Swantek, W. J. Riley, and D. A. Agarwal, "Launching an accessible archive of environmental data", Eos, 100, January 8, 2019, doi:

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

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

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,

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:

Y. Liu, W. Sid-Lakhdar, E. Rebrova, P. Ghysels, X. Sherry Li, "A Hierarchical Low-Rank Decomposition Algorithm Based on Blocked Adaptive Cross Approximation Algorithms", arXiv e-prints, January 1, 2019,

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,

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,

E. Y. Hsiao, M. M. Phiilips, G. H. Marion, R. P., N. Morrell, D. J. Sand, C. R. Burns, C., P. Hoeflich, M. D. Stritzinger, S., J. P. Anderson, C. Ashall, C. Baltay, E., D. P. K. Banerjee, S. Davis, T. R. Diamond, G., W. L. Freedman, F. Foerster, L., C. Gall, S. Gonzalez-Gaitan, A., M. Hamuy, S. Holmbo, M. M. Kasliwal, K., S. Kumar, C. Lidman, J. Lu, P. E., S. Perlmutter, S. E. Persson, A. L., D. Rabinowitz, M. Roth, S. D. Ryder, B. P., 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

J Muller, M Day, "Surrogate Optimization of Computationally Expensive Black-box Problems with Hidden Constraints", INFORMS Journal on Computing, 2019,

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), 2019,

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

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