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2018 Publications

Deb Agarwal

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

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

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,

Hadia Ahmed

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), November 13, 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.

Hasan Metin Aktulga

2018

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

Ann S. Almgren

2018

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

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

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,

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,

Ariful Azad

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,

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,

John Bachan

2018

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,

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), November 13, 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.

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,

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 26, 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.

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.

J Bachan, S Baden, D Bonachea, PH Hargrove, S Hofmeyr, K Ibrahim, M Jacquelin, A Kamil, B van Straalen, "UPC++ Programmer’s Guide, v1.0-2018.3.0", March 31, 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.

J Bachan, S Baden, D Bonachea, P Hargrove, S Hofmeyr, K Ibrahim, M Jacquelin, A Kamil, B Lelbach, B van Straalen, "UPC++ Specification v1.0, Draft 6", 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.

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,

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", Poster at Exascale Computing Project (ECP) Annual Meeting 2018., February 2018,

Scott Baden

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), November 13, 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.

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 26, 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.

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.

J Bachan, S Baden, D Bonachea, PH Hargrove, S Hofmeyr, K Ibrahim, M Jacquelin, A Kamil, B van Straalen, "UPC++ Programmer’s Guide, v1.0-2018.3.0", March 31, 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.

J Bachan, S Baden, D Bonachea, P Hargrove, S Hofmeyr, K Ibrahim, M Jacquelin, A Kamil, B Lelbach, B van Straalen, "UPC++ Specification v1.0, Draft 6", 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.

Scott Baden, Dan Bonachea, Paul Hargrove, "GASNet-EX: PGAS Support for Exascale Apps and Runtimes", ECP Annual Meeting 2018, February 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", Poster at Exascale Computing Project (ECP) Annual Meeting 2018., February 2018,

Zhaojun Bai

2018

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

Protonu Basu

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,

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,

Protonu Basu, Using Empirical Roofline Toolkit and Nvidia nvprof, ECP Annual Meeting, February 8, 2018,

John B. Bell

2018

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

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

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

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

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

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,

E. Wes Bethel

2018

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

B Loring, A Myers, D Camp, EW Bethel, "Python-based in situ analysis and visualization", Proceedings of the Workshop on In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization - ISAV 18, ACM Press, 2018, doi: 10.1145/3281464.3281465

Amneet Pal Singh Bhalla

2018

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,

Dan Bonachea

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: 10.1109/PAW-ATM.2018.00008

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.

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), November 13, 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.

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.

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 26, 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.

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.

J Bachan, S Baden, D Bonachea, PH Hargrove, S Hofmeyr, K Ibrahim, M Jacquelin, A Kamil, B van Straalen, "UPC++ Programmer’s Guide, v1.0-2018.3.0", March 31, 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.

Dan Bonachea, Paul Hargrove, "GASNet-EX Performance Improvements Due to Specialization for the Cray Aries Network", 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.

J Bachan, S Baden, D Bonachea, P Hargrove, S Hofmeyr, K Ibrahim, M Jacquelin, A Kamil, B Lelbach, B van Straalen, "UPC++ Specification v1.0, Draft 6", 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.

Scott Baden, Dan Bonachea, Paul Hargrove, "GASNet-EX: PGAS Support for Exascale Apps and Runtimes", ECP Annual Meeting 2018, February 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", Poster at Exascale Computing Project (ECP) Annual Meeting 2018., February 2018,

Julian Borrill

2018

KN Abazajian, P Adshead, Z Ahmed, SW Allen, D Alonso, KS Arnold, C Baccigalupi, JG Bartlett, N Battaglia, BA Benson, CA Bischoff, J Borrill, V Buza, E Calabrese, R Caldwell, JE Carlstrom, CL Chang, TM Crawford, F-Y Cyr-Racine, FD Bernardis, TD Haan, SDS Alighieri, J Dunkley, C Dvorkin, J Errard, G Fabbian, S Feeney, S Ferraro, JP Filippini, R Flauger, GM Fuller, V Gluscevic, D Green, D Grin, E Grohs, JW Henning, JC Hill, R Hlozek, G Holder, W Holzapfel, W Hu, KM Huffenberger, R Keskitalo, L Knox, A Kosowsky, J Kovac, ED Kovetz, C-L Kuo, A Kusaka, ML Jeune, AT Lee, M Lilley, M Loverde, MS Madhavacheril, A Mantz, DJE Marsh, J McMahon, PD Meerburg, J Meyers, AD Miller, JB Munoz, HN Nguyen, MD Niemack, M Peloso, J Peloton, L Pogosian, C Pryke, M Raveri, CL Reichardt, G Rocha, A Rotti, E Schaan, MM Schmittfull, D Scott, N Sehgal, S Shandera, BD Sherwin, TL Smith, L Sorbo, GD Starkman, KT Story, AV Engelen, JD Vieira, S Watson, N Whitehorn, WLK Wu, CMB-S4 Science Book, First Edition, 2018,

S Takakura, MAO Aguilar-Faúndez, 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, 2018,

TSO Collaboration, 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, H-MS Cho, S Choi, G Coppi, NF Cothard, K Coughlin, D Crichton, KD Crowley, KT Crowley, A Cukierman, MD Ewart, R Dünner, TD Haan, M Devlin, S Dicker, J Didier, M Dobbs, B Dober, C Duell, S Duff, A Duivenvoorden, J Dunkley, J Dusatko, J Errard, G Fabbian, S Feeney, S Ferraro, P Fluxà, K Freese, J 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, S Henderson, C Hervias-Caimapo, CA Hill, JC Hill, G Hilton, M Hilton, AD Hincks, G Hinshaw, R Hložek, S Ho, S-PP Ho, L Howe, Z Huang, J Hubmayr, K Huffenberger, JP Hughes, A Ijjas, M Ikape, K Irwin, AH Jaffe, B Jain, O Jeong, D Kaneko, E Karpel, N Katayama, B Keating, S Kernasovski, R Keskitalo, T Kisner, K Kiuchi, J Klein, K Knowles, B Koopman, A Kosowsky, N Krachmalnicoff, S Kuenstner, C-L Kuo, A Kusaka, J Lashner, A Lee, E Lee, D Leon, JS-Y Leung, A Lewis, Y Li, Z Li, M Limon, E Linder, C Lopez-Caraballo, T Louis, L Lowry, M Lungu, M Madhavacheril, D Mak, F Maldonado, H Mani, B Mates, F Matsuda, L Maurin, P Mauskopf, A May, N McCallum, C McKenney, J McMahon, PD Meerburg, J Meyers, A Miller, M Mirmelstein, K Moodley, M Munchmeyer, C Munson, S Naess, F Nati, M Navaroli, L Newburgh, HN Nguyen, M Niemack, H Nishino, J Orlowski-Scherer, L Page, B Partridge, J Peloton, F Perrotta, L Piccirillo, G Pisano, D Poletti, R Puddu, G Puglisi, C Raum, CL Reichardt, M Remazeilles, Y Rephaeli, D Riechers, F Rojas, A Roy, S Sadeh, Y Sakurai, M Salatino, MS Rao, E Schaan, M Schmittfull, N Sehgal, J Seibert, U Seljak, B Sherwin, M Shimon, C Sierra, J Sievers, P Sikhosana, M Silva-Feaver, SM Simon, A Sinclair, P Siritanasak, K Smith, S Smith, D Spergel, S Staggs, G Stein, JR Stevens, R Stompor, R Sudiwala, A Suzuki, O Tajima, S Takakura, G Teply, DB Thomas, B Thorne, R Thornton, H Trac, C Tsai, C Tucker, J Ullom, S Vagnozzi, AV Engelen, JV Lanen, DV Winkle, EM Vavagiakis, C Vergès, M Vissers, K Wagoner, J Ward, B Westbrook, N Whitehorn, J Williams, J Williams, EJ Wollack, Z Xu, J Ye, B Yu, C Yu, F Zago, H Zhang, N Zhu, The Simons Observatory: Science goals and forecasts, 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,

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,

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, "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, "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

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, "The LiteBIRD Satellite Mission: Sub-Kelvin Instrument", Journal of Low Temperature Physics, 2018, 193:1048--1056, doi: 10.1007/s10909-018-1947-7

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, "Planck intermediate results: LIV. the Planck multi-frequency catalogue of non-thermal sources", Astronomy and Astrophysics, 2018, 619, doi: 10.1051/0004-6361/201832888

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, "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

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

JF Macìas-Pérez, J Delabrouille, P De Bernardis, FR Bouchet, A Achúcarro, PAR Ade, R Allison, F Arroja, E Artal, M Ashdown, C Baccigalupi, M Ballardini, AJ Banday, R Banerji, D Barbosa, J Bartlett, N Bartolo, S Basak, JJA Baselmans, K Basu, ES Battistelli, R Battye, D Baumann, A Benoít, M Bersanelli, A Bideaud, M Biesiada, M Bilicki, A Bonaldi, M Bonato, J Borrill, F Boulanger, T Brinckmann, ML Brown, M Bucher, C Burigana, A Buzzelli, G Cabass, ZY Cai, M Calvo, A Caputo, CS Carvalho, FJ Casas, G Castellano, A Catalano, A Challinor, I Charles, J Chluba, DL Clements, S Clesse, S Colafrancesco, I Colantoni, D Contreras, A Coppolecchia, M Crook, G D Alessandro, G D Amico, AD Silva, M De Avillez, G De Gasperis, MD Petris, G De Zotti, L Danese, FX Désert, V Desjacques, ED Valentino, C Dickinson, JM Diego, S Doyle, R Durrer, "Exploring cosmic origins with CORE: Survey requirements and mission design", Journal of Cosmology and Astroparticle Physics, 2018, 2018, doi: 10.1088/1475-7516/2018/04/014

P Natoli, M Ashdown, R Banerji, J Borrill, A Buzzelli, G De Gasperis, J Delabrouille, E Hivon, D Molinari, G Patanchon, L Polastri, M Tomasi, FR Bouchet, S Henrot-Versillé, DT Hoang, R Keskitalo, K Kiiveri, T Kisner, V Lindholm, D McCarthy, F Piacentini, O Perdereau, G Polenta, M Tristram, A Achucarro, P Ade, R Allison, C Baccigalupi, M Ballardini, AJ Banday, J Bartlett, N Bartolo, S Basak, D Baumann, M Bersanelli, A Bonaldi, M Bonato, F Boulanger, T Brinckmann, M Bucher, C Burigana, ZY Cai, M Calvo, CS Carvalho, MG Castellano, A Challinor, J Chluba, S Clesse, I Colantoni, A Coppolecchia, M Crook, G D Alessandro, P De Bernardis, GD Zotti, ED Valentino, JM Diego, J Errard, S Feeney, R Fernandez-Cobos, F Finelli, F Forastieri, S Galli, R Genova-Santos, "Exploring cosmic origins with CORE: Mitigation of systematic effects", Journal of Cosmology and Astroparticle Physics, 2018, 2018, doi: 10.1088/1475-7516/2018/04/022

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

Kristofer Bouchard

2018

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

Maximilian Bremer

2018

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,

Aydin Buluç

2018

Giulia Guidi, Marquita Ellis, Daniel Rokhsar, Katherine Yelick, Aydın Buluç, "BELLA: Berkeley Efficient Long-Read to Long-Read Aligner and Overlapper (Preprint)", Submitted, 2018, doi: https://doi.org/10.1101/464420

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,

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,

Anastasiia Butko

2018

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

Surendra Byna

2018

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,

Bin Dong, Teng Wang, Houjun Tang, Quincey Koziol, Kesheng Wu, and Suren Byna, "ARCHIE: Data Analysis Acceleration with Array Caching in Hierarchical Storage", IEEE BigData, 2018, December 10, 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,

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,

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,

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,

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, 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,

Teng Wang, Suren Byna, Bin Dong, and Houjun Tang, "UniviStor: Integrated Hierarchical and Distributed Storage for HPC", IEEE Cluster 2018., September 1, 2018,

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,

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,

Kesheng Wu, Surendra Byna, Bin Dong, others, VPIC IO utilities, 2018,

David Camp

2018

B Loring, A Myers, D Camp, EW Bethel, "Python-based in situ analysis and visualization", Proceedings of the Workshop on In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization - ISAV 18, ACM Press, 2018, doi: 10.1145/3281464.3281465

Andrew Canning

2018

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

Jonathan Carter

2018

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

Cy Chan

2018

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,

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,

Cy Chan, Vesselin Drensky, Alan Edelman, Raymond Kan, Plamen Koev, "On Computing Schur Functions and Series Thereof", Journal of Algebraic Combinatorics, October 20, 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,

You-Wei Cheah

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,

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

Shreyas Cholia

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,

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

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,

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

Gustavo Chávez

2018

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,

Phillip Colella

2018

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

Frederick Davies

2018

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

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

Marcus S. Day

2018

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

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

Mauro Del Ben

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

James Demmel

2018

Grey Ballard, James Demmel, Laura Grigori, Mathias Jacquelin, Nicholas Knight, "A 3D Parallel Algorithm for QR Decomposition", SPAA '18, 2018,

Nan Ding

2018

Nan Ding, Victor W Lee, Wei Xue, Weimin Zheng, "Understanding Potential Performance Issues Using Resource-based Alongside Time Models", SC'18, November 13, 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,

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,

Bin Dong

2018

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,

Bin Dong, Teng Wang, Houjun Tang, Quincey Koziol, Kesheng Wu, and Suren Byna, "ARCHIE: Data Analysis Acceleration with Array Caching in Hierarchical Storage", IEEE BigData, 2018, December 10, 2018,

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) in SC 2018, November 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,

Weijie Zhao, Florin Rusu, Bin Dong, Kesheng Wu, Anna Ho, and Peter Nugent, "Distributed Caching for Processing Raw Arrays", SSDBM, 2018,

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,

Kesheng Wu, Surendra Byna, Bin Dong, others, VPIC IO utilities, 2018,

David Donofrio

2018

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

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

Saliya Ekanayake

2018

Saliya Ekanayake, "MIDAS", April 1, 2018,

Muammar El Khatib

2018

Alireza Khorshidi, Muammar El Khatib, Andrew A Peterson, Amp: The Atomistic Machine-learning Package v0.6.1, August 1, 2018,

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,

Marquita Ellis

2018

Giulia Guidi, Marquita Ellis, Daniel Rokhsar, Katherine Yelick, Aydın Buluç, "BELLA: Berkeley Efficient Long-Read to Long-Read Aligner and Overlapper (Preprint)", Submitted, 2018, doi: https://doi.org/10.1101/464420

Farzad Fatollahi-Fard

2018

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

Devarshi Ghoshal

2018

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

Devarshi Ghoshal, "Deduce: Managing Data Change Pipelines", Conference on Data Analysis (CoDA 2018), 2018,

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

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,

Pieter Ghysels

2018

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,

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,

Anna Giannakou

2018

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

Junmin Gu

2018

Junmin Gu, Scott Klasky, Norbert Podhorszki, Ji Qiang, Kesheng Wu, "Querying Large Scientific Data Sets with Adaptable IO System ADIOS", Supercomputing Frontiers (Best Paper Award), Springer International Publishing, 2018, 51-69,

Ming Gu

2018

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

Giulia Guidi

2018

Giulia Guidi, Marquita Ellis, Daniel Rokhsar, Katherine Yelick, Aydın Buluç, "BELLA: Berkeley Efficient Long-Read to Long-Read Aligner and Overlapper (Preprint)", Submitted, 2018, doi: https://doi.org/10.1101/464420

Daniel Gunter

2018

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

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

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

Francois Hamon

2018

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

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,

Maciej Haranczyk

2018

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

Paul H. Hargrove

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: 10.1109/PAW-ATM.2018.00008

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.

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), November 13, 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.

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.

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 26, 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.

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.

J Bachan, S Baden, D Bonachea, PH Hargrove, S Hofmeyr, K Ibrahim, M Jacquelin, A Kamil, B van Straalen, "UPC++ Programmer’s Guide, v1.0-2018.3.0", March 31, 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.

Dan Bonachea, Paul Hargrove, "GASNet-EX Performance Improvements Due to Specialization for the Cray Aries Network", 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.

J Bachan, S Baden, D Bonachea, P Hargrove, S Hofmeyr, K Ibrahim, M Jacquelin, A Kamil, B Lelbach, B van Straalen, "UPC++ Specification v1.0, Draft 6", 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.

Scott Baden, Dan Bonachea, Paul Hargrove, "GASNet-EX: PGAS Support for Exascale Apps and Runtimes", ECP Annual Meeting 2018, February 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", Poster at Exascale Computing Project (ECP) Annual Meeting 2018., February 2018,

Matthew Henderson

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,

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

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,

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

Valerie Hendrix

2018

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

Steven Hofmeyr

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), November 13, 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.

E Georganas, R Egan, S Hofmeyr, E Goltsman, B Arnt, A Tritt, A Buluc, L Oliker, K Yelick, "Extreme Scale De Novo Metagenome Assembly", International Conference for High Performance Computing, Networking, Storage, and Analysis (SC18), 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 26, 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.

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.

J Bachan, S Baden, D Bonachea, PH Hargrove, S Hofmeyr, K Ibrahim, M Jacquelin, A Kamil, B van Straalen, "UPC++ Programmer’s Guide, v1.0-2018.3.0", March 31, 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.

J Bachan, S Baden, D Bonachea, P Hargrove, S Hofmeyr, K Ibrahim, M Jacquelin, A Kamil, B Lelbach, B van Straalen, "UPC++ Specification v1.0, Draft 6", 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.

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,

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", Poster at Exascale Computing Project (ECP) Annual Meeting 2018., February 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

J Bachan, S Baden, D Bonachea, M Jacquelin, P Hargrove, S Hofmeyr, A Kamil, "Performance and Implementation of UPC++ - A C++ Library for PGAS Programming", 2018,

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

Wei Hu

2018

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

Khaled Ibrahim

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,

J Bachan, S Baden, D Bonachea, PH Hargrove, S Hofmeyr, K Ibrahim, M Jacquelin, A Kamil, B van Straalen, "UPC++ Programmer’s Guide, v1.0-2018.3.0", March 31, 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.

J Bachan, S Baden, D Bonachea, P Hargrove, S Hofmeyr, K Ibrahim, M Jacquelin, A Kamil, B Lelbach, B van Straalen, "UPC++ Specification v1.0, Draft 6", 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 Hargrove, Steven Hofmeyr, Khaled Ibrahim, Mathias Jacquelin, Amir Kamil, Brian van Straalen, "UPC++ and GASNet: PGAS Support for Exascale Apps and Runtimes", Poster at Exascale Computing Project (ECP) Annual Meeting 2018., February 2018,

Mathias Jacquelin

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), November 13, 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.

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 26, 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.

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.

J Bachan, S Baden, D Bonachea, PH Hargrove, S Hofmeyr, K Ibrahim, M Jacquelin, A Kamil, B van Straalen, "UPC++ Programmer’s Guide, v1.0-2018.3.0", March 31, 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.

J Bachan, S Baden, D Bonachea, P Hargrove, S Hofmeyr, K Ibrahim, M Jacquelin, A Kamil, B Lelbach, B van Straalen, "UPC++ Specification v1.0, Draft 6", 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 Hargrove, Steven Hofmeyr, Khaled Ibrahim, Mathias Jacquelin, Amir Kamil, Brian van Straalen, "UPC++ and GASNet: PGAS Support for Exascale Apps and Runtimes", Poster at Exascale Computing Project (ECP) Annual Meeting 2018., February 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,

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,

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,

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,

Grey Ballard, James Demmel, Laura Grigori, Mathias Jacquelin, Nicholas Knight, "A 3D Parallel Algorithm for QR Decomposition", SPAA '18, 2018,

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,

Hans Johansen

2018

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,

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,

Amir Kamil

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), November 13, 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.

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 26, 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.

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.

J Bachan, S Baden, D Bonachea, PH Hargrove, S Hofmeyr, K Ibrahim, M Jacquelin, A Kamil, B van Straalen, "UPC++ Programmer’s Guide, v1.0-2018.3.0", March 31, 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.

J Bachan, S Baden, D Bonachea, P Hargrove, S Hofmeyr, K Ibrahim, M Jacquelin, A Kamil, B Lelbach, B van Straalen, "UPC++ Specification v1.0, Draft 6", 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 Hargrove, Steven Hofmeyr, Khaled Ibrahim, Mathias Jacquelin, Amir Kamil, Brian van Straalen, "UPC++ and GASNet: PGAS Support for Exascale Apps and Runtimes", Poster at Exascale Computing Project (ECP) Annual Meeting 2018., February 2018,

Reijo Keskitalo

2018

KN Abazajian, P Adshead, Z Ahmed, SW Allen, D Alonso, KS Arnold, C Baccigalupi, JG Bartlett, N Battaglia, BA Benson, CA Bischoff, J Borrill, V Buza, E Calabrese, R Caldwell, JE Carlstrom, CL Chang, TM Crawford, F-Y Cyr-Racine, FD Bernardis, TD Haan, SDS Alighieri, J Dunkley, C Dvorkin, J Errard, G Fabbian, S Feeney, S Ferraro, JP Filippini, R Flauger, GM Fuller, V Gluscevic, D Green, D Grin, E Grohs, JW Henning, JC Hill, R Hlozek, G Holder, W Holzapfel, W Hu, KM Huffenberger, R Keskitalo, L Knox, A Kosowsky, J Kovac, ED Kovetz, C-L Kuo, A Kusaka, ML Jeune, AT Lee, M Lilley, M Loverde, MS Madhavacheril, A Mantz, DJE Marsh, J McMahon, PD Meerburg, J Meyers, AD Miller, JB Munoz, HN Nguyen, MD Niemack, M Peloso, J Peloton, L Pogosian, C Pryke, M Raveri, CL Reichardt, G Rocha, A Rotti, E Schaan, MM Schmittfull, D Scott, N Sehgal, S Shandera, BD Sherwin, TL Smith, L Sorbo, GD Starkman, KT Story, AV Engelen, JD Vieira, S Watson, N Whitehorn, WLK Wu, CMB-S4 Science Book, First Edition, 2018,

S Takakura, MAO Aguilar-Faúndez, 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, 2018,

TSO Collaboration, 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, H-MS Cho, S Choi, G Coppi, NF Cothard, K Coughlin, D Crichton, KD Crowley, KT Crowley, A Cukierman, MD Ewart, R Dünner, TD Haan, M Devlin, S Dicker, J Didier, M Dobbs, B Dober, C Duell, S Duff, A Duivenvoorden, J Dunkley, J Dusatko, J Errard, G Fabbian, S Feeney, S Ferraro, P Fluxà, K Freese, J 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, S Henderson, C Hervias-Caimapo, CA Hill, JC Hill, G Hilton, M Hilton, AD Hincks, G Hinshaw, R Hložek, S Ho, S-PP Ho, L Howe, Z Huang, J Hubmayr, K Huffenberger, JP Hughes, A Ijjas, M Ikape, K Irwin, AH Jaffe, B Jain, O Jeong, D Kaneko, E Karpel, N Katayama, B Keating, S Kernasovski, R Keskitalo, T Kisner, K Kiuchi, J Klein, K Knowles, B Koopman, A Kosowsky, N Krachmalnicoff, S Kuenstner, C-L Kuo, A Kusaka, J Lashner, A Lee, E Lee, D Leon, JS-Y Leung, A Lewis, Y Li, Z Li, M Limon, E Linder, C Lopez-Caraballo, T Louis, L Lowry, M Lungu, M Madhavacheril, D Mak, F Maldonado, H Mani, B Mates, F Matsuda, L Maurin, P Mauskopf, A May, N McCallum, C McKenney, J McMahon, PD Meerburg, J Meyers, A Miller, M Mirmelstein, K Moodley, M Munchmeyer, C Munson, S Naess, F Nati, M Navaroli, L Newburgh, HN Nguyen, M Niemack, H Nishino, J Orlowski-Scherer, L Page, B Partridge, J Peloton, F Perrotta, L Piccirillo, G Pisano, D Poletti, R Puddu, G Puglisi, C Raum, CL Reichardt, M Remazeilles, Y Rephaeli, D Riechers, F Rojas, A Roy, S Sadeh, Y Sakurai, M Salatino, MS Rao, E Schaan, M Schmittfull, N Sehgal, J Seibert, U Seljak, B Sherwin, M Shimon, C Sierra, J Sievers, P Sikhosana, M Silva-Feaver, SM Simon, A Sinclair, P Siritanasak, K Smith, S Smith, D Spergel, S Staggs, G Stein, JR Stevens, R Stompor, R Sudiwala, A Suzuki, O Tajima, S Takakura, G Teply, DB Thomas, B Thorne, R Thornton, H Trac, C Tsai, C Tucker, J Ullom, S Vagnozzi, AV Engelen, JV Lanen, DV Winkle, EM Vavagiakis, C Vergès, M Vissers, K Wagoner, J Ward, B Westbrook, N Whitehorn, J Williams, J Williams, EJ Wollack, Z Xu, J Ye, B Yu, C Yu, F Zago, H Zhang, N Zhu, The Simons Observatory: Science goals and forecasts, 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,

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,

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, "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, "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

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, "The LiteBIRD Satellite Mission: Sub-Kelvin Instrument", Journal of Low Temperature Physics, 2018, 193:1048--1056, doi: 10.1007/s10909-018-1947-7

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, "Planck intermediate results: LIV. the Planck multi-frequency catalogue of non-thermal sources", Astronomy and Astrophysics, 2018, 619, doi: 10.1051/0004-6361/201832888

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, "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

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

JF Macìas-Pérez, J Delabrouille, P De Bernardis, FR Bouchet, A Achúcarro, PAR Ade, R Allison, F Arroja, E Artal, M Ashdown, C Baccigalupi, M Ballardini, AJ Banday, R Banerji, D Barbosa, J Bartlett, N Bartolo, S Basak, JJA Baselmans, K Basu, ES Battistelli, R Battye, D Baumann, A Benoít, M Bersanelli, A Bideaud, M Biesiada, M Bilicki, A Bonaldi, M Bonato, J Borrill, F Boulanger, T Brinckmann, ML Brown, M Bucher, C Burigana, A Buzzelli, G Cabass, ZY Cai, M Calvo, A Caputo, CS Carvalho, FJ Casas, G Castellano, A Catalano, A Challinor, I Charles, J Chluba, DL Clements, S Clesse, S Colafrancesco, I Colantoni, D Contreras, A Coppolecchia, M Crook, G D Alessandro, G D Amico, AD Silva, M De Avillez, G De Gasperis, MD Petris, G De Zotti, L Danese, FX Désert, V Desjacques, ED Valentino, C Dickinson, JM Diego, S Doyle, R Durrer, "Exploring cosmic origins with CORE: Survey requirements and mission design", Journal of Cosmology and Astroparticle Physics, 2018, 2018, doi: 10.1088/1475-7516/2018/04/014

P Natoli, M Ashdown, R Banerji, J Borrill, A Buzzelli, G De Gasperis, J Delabrouille, E Hivon, D Molinari, G Patanchon, L Polastri, M Tomasi, FR Bouchet, S Henrot-Versillé, DT Hoang, R Keskitalo, K Kiiveri, T Kisner, V Lindholm, D McCarthy, F Piacentini, O Perdereau, G Polenta, M Tristram, A Achucarro, P Ade, R Allison, C Baccigalupi, M Ballardini, AJ Banday, J Bartlett, N Bartolo, S Basak, D Baumann, M Bersanelli, A Bonaldi, M Bonato, F Boulanger, T Brinckmann, M Bucher, C Burigana, ZY Cai, M Calvo, CS Carvalho, MG Castellano, A Challinor, J Chluba, S Clesse, I Colantoni, A Coppolecchia, M Crook, G D Alessandro, P De Bernardis, GD Zotti, ED Valentino, JM Diego, J Errard, S Feeney, R Fernandez-Cobos, F Finelli, F Forastieri, S Galli, R Genova-Santos, "Exploring cosmic origins with CORE: Mitigation of systematic effects", Journal of Cosmology and Astroparticle Physics, 2018, 2018, doi: 10.1088/1475-7516/2018/04/022

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

Changho Kim

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,

A. Donev, C.-Y. Yang, C. Kim, "Efficient reactive Brownian dynamics", J. Chem. Phys. 148, 034103, 2018,

Mariam Kiran

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

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

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

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

Ted Kisner

2018

KN Abazajian, P Adshead, Z Ahmed, SW Allen, D Alonso, KS Arnold, C Baccigalupi, JG Bartlett, N Battaglia, BA Benson, CA Bischoff, J Borrill, V Buza, E Calabrese, R Caldwell, JE Carlstrom, CL Chang, TM Crawford, F-Y Cyr-Racine, FD Bernardis, TD Haan, SDS Alighieri, J Dunkley, C Dvorkin, J Errard, G Fabbian, S Feeney, S Ferraro, JP Filippini, R Flauger, GM Fuller, V Gluscevic, D Green, D Grin, E Grohs, JW Henning, JC Hill, R Hlozek, G Holder, W Holzapfel, W Hu, KM Huffenberger, R Keskitalo, L Knox, A Kosowsky, J Kovac, ED Kovetz, C-L Kuo, A Kusaka, ML Jeune, AT Lee, M Lilley, M Loverde, MS Madhavacheril, A Mantz, DJE Marsh, J McMahon, PD Meerburg, J Meyers, AD Miller, JB Munoz, HN Nguyen, MD Niemack, M Peloso, J Peloton, L Pogosian, C Pryke, M Raveri, CL Reichardt, G Rocha, A Rotti, E Schaan, MM Schmittfull, D Scott, N Sehgal, S Shandera, BD Sherwin, TL Smith, L Sorbo, GD Starkman, KT Story, AV Engelen, JD Vieira, S Watson, N Whitehorn, WLK Wu, CMB-S4 Science Book, First Edition, 2018,

S Takakura, MAO Aguilar-Faúndez, 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, 2018,

TSO Collaboration, 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, H-MS Cho, S Choi, G Coppi, NF Cothard, K Coughlin, D Crichton, KD Crowley, KT Crowley, A Cukierman, MD Ewart, R Dünner, TD Haan, M Devlin, S Dicker, J Didier, M Dobbs, B Dober, C Duell, S Duff, A Duivenvoorden, J Dunkley, J Dusatko, J Errard, G Fabbian, S Feeney, S Ferraro, P Fluxà, K Freese, J 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, S Henderson, C Hervias-Caimapo, CA Hill, JC Hill, G Hilton, M Hilton, AD Hincks, G Hinshaw, R Hložek, S Ho, S-PP Ho, L Howe, Z Huang, J Hubmayr, K Huffenberger, JP Hughes, A Ijjas, M Ikape, K Irwin, AH Jaffe, B Jain, O Jeong, D Kaneko, E Karpel, N Katayama, B Keating, S Kernasovski, R Keskitalo, T Kisner, K Kiuchi, J Klein, K Knowles, B Koopman, A Kosowsky, N Krachmalnicoff, S Kuenstner, C-L Kuo, A Kusaka, J Lashner, A Lee, E Lee, D Leon, JS-Y Leung, A Lewis, Y Li, Z Li, M Limon, E Linder, C Lopez-Caraballo, T Louis, L Lowry, M Lungu, M Madhavacheril, D Mak, F Maldonado, H Mani, B Mates, F Matsuda, L Maurin, P Mauskopf, A May, N McCallum, C McKenney, J McMahon, PD Meerburg, J Meyers, A Miller, M Mirmelstein, K Moodley, M Munchmeyer, C Munson, S Naess, F Nati, M Navaroli, L Newburgh, HN Nguyen, M Niemack, H Nishino, J Orlowski-Scherer, L Page, B Partridge, J Peloton, F Perrotta, L Piccirillo, G Pisano, D Poletti, R Puddu, G Puglisi, C Raum, CL Reichardt, M Remazeilles, Y Rephaeli, D Riechers, F Rojas, A Roy, S Sadeh, Y Sakurai, M Salatino, MS Rao, E Schaan, M Schmittfull, N Sehgal, J Seibert, U Seljak, B Sherwin, M Shimon, C Sierra, J Sievers, P Sikhosana, M Silva-Feaver, SM Simon, A Sinclair, P Siritanasak, K Smith, S Smith, D Spergel, S Staggs, G Stein, JR Stevens, R Stompor, R Sudiwala, A Suzuki, O Tajima, S Takakura, G Teply, DB Thomas, B Thorne, R Thornton, H Trac, C Tsai, C Tucker, J Ullom, S Vagnozzi, AV Engelen, JV Lanen, DV Winkle, EM Vavagiakis, C Vergès, M Vissers, K Wagoner, J Ward, B Westbrook, N Whitehorn, J Williams, J Williams, EJ Wollack, Z Xu, J Ye, B Yu, C Yu, F Zago, H Zhang, N Zhu, The Simons Observatory: Science goals and forecasts, 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,

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,

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, "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, "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

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, "The LiteBIRD Satellite Mission: Sub-Kelvin Instrument", Journal of Low Temperature Physics, 2018, 193:1048--1056, doi: 10.1007/s10909-018-1947-7

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, "Planck intermediate results: LIV. the Planck multi-frequency catalogue of non-thermal sources", Astronomy and Astrophysics, 2018, 619, doi: 10.1051/0004-6361/201832888

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, "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

JF Macìas-Pérez, J Delabrouille, P De Bernardis, FR Bouchet, A Achúcarro, PAR Ade, R Allison, F Arroja, E Artal, M Ashdown, C Baccigalupi, M Ballardini, AJ Banday, R Banerji, D Barbosa, J Bartlett, N Bartolo, S Basak, JJA Baselmans, K Basu, ES Battistelli, R Battye, D Baumann, A Benoít, M Bersanelli, A Bideaud, M Biesiada, M Bilicki, A Bonaldi, M Bonato, J Borrill, F Boulanger, T Brinckmann, ML Brown, M Bucher, C Burigana, A Buzzelli, G Cabass, ZY Cai, M Calvo, A Caputo, CS Carvalho, FJ Casas, G Castellano, A Catalano, A Challinor, I Charles, J Chluba, DL Clements, S Clesse, S Colafrancesco, I Colantoni, D Contreras, A Coppolecchia, M Crook, G D Alessandro, G D Amico, AD Silva, M De Avillez, G De Gasperis, MD Petris, G De Zotti, L Danese, FX Désert, V Desjacques, ED Valentino, C Dickinson, JM Diego, S Doyle, R Durrer, "Exploring cosmic origins with CORE: Survey requirements and mission design", Journal of Cosmology and Astroparticle Physics, 2018, 2018, doi: 10.1088/1475-7516/2018/04/014

P Natoli, M Ashdown, R Banerji, J Borrill, A Buzzelli, G De Gasperis, J Delabrouille, E Hivon, D Molinari, G Patanchon, L Polastri, M Tomasi, FR Bouchet, S Henrot-Versillé, DT Hoang, R Keskitalo, K Kiiveri, T Kisner, V Lindholm, D McCarthy, F Piacentini, O Perdereau, G Polenta, M Tristram, A Achucarro, P Ade, R Allison, C Baccigalupi, M Ballardini, AJ Banday, J Bartlett, N Bartolo, S Basak, D Baumann, M Bersanelli, A Bonaldi, M Bonato, F Boulanger, T Brinckmann, M Bucher, C Burigana, ZY Cai, M Calvo, CS Carvalho, MG Castellano, A Challinor, J Chluba, S Clesse, I Colantoni, A Coppolecchia, M Crook, G D Alessandro, P De Bernardis, GD Zotti, ED Valentino, JM Diego, J Errard, S Feeney, R Fernandez-Cobos, F Finelli, F Forastieri, S Galli, R Genova-Santos, "Exploring cosmic origins with CORE: Mitigation of systematic effects", Journal of Cosmology and Astroparticle Physics, 2018, 2018, doi: 10.1088/1475-7516/2018/04/022

Penporn Koanantakool

2018

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,

Harinarayan Krishnan

2018

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

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

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

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,

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

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

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

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

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

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

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 Ladiges

2018

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,

Bryce Lelbach

2018

J Bachan, S Baden, D Bonachea, P Hargrove, S Hofmeyr, K Ibrahim, M Jacquelin, A Kamil, B Lelbach, B van Straalen, "UPC++ Specification v1.0, Draft 6", 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.

Xiaoye Li

2018

H. Zhan, G. Gomes, X. S. Li, K. Madduri, A. Sim, K. Wu, "Consensus Ensemble System for Traffic Flow Prediction", IEEE Transactions on Intelligent Transportation Systems, 2018, doi: 10.1109/TITS.2018.2791505

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,

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,

Lin Lin

2018

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

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

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

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,

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,

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,

Yang Liu

2018

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,

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,

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,

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,

Burlen Loring

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

B Loring, A Myers, D Camp, EW Bethel, "Python-based in situ analysis and visualization", Proceedings of the Workshop on In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization - ISAV 18, ACM Press, 2018, doi: 10.1145/3281464.3281465

Zarija Lukic

2018

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,

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

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

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

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

Stefano Marchesini

2018

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,

Osni Marques

2018

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

Daniel F. Martin

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,

Dan Martin, Ice sheet model-dependence of persistent ice-cliff formation, European Geosciences Union General Assembly 2018, April 11, 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,

Jarrod McClean

2018

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

George Michelogiannakis

2018

George Michelogiannakis, How Open Source Hardware Will Drive the Next Generation of HPC Systems, CROSS Symposium at UCSC, October 2018,

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,

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,

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,

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,

Michael Minion

2018

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

M Minion, S Goetschel, "Parallel-in-Time for Parabolic Optimal Control Problems Using PFASST", Domain Decomposition Methods in Science and Engineering XXIV, (Springer: 2018)

Bashir Mohammed

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

Dmitriy Morozov

2018

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

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

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,

Andrey Babichev, Dmitriy Morozov, Yuri Dabaghian, "Robust spatial memory maps encoded by networks with transient", PLoS computational biology, 2018, 14:e1006433,

Emmanuel Motheau

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,

Juliane Mueller

2018

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,

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

Andrew Myers

2018

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

B Loring, A Myers, D Camp, EW Bethel, "Python-based in situ analysis and visualization", Proceedings of the Workshop on In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization - ISAV 18, ACM Press, 2018, doi: 10.1145/3281464.3281465

Esmond G. Ng

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,

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

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,

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

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,

Andy Nonaka

2018

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

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

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

Peter Nugent

2018

Weijie Zhao, Florin Rusu, Bin Dong, Kesheng Wu, Anna Ho, and Peter Nugent, "Distributed Caching for Processing Raw Arrays", SSDBM, 2018,

T. M. C. Abbott, F. B. Abdalla, S. Allam, A., J. Annis, J. Asorey, S. Avila, O., M. Banerji, W. Barkhouse, L. Baruah, M., K. Bechtol, M. R. Becker, A. Benoit-L\ evy, G. M., E. Bertin, J. Blazek, S. Bocquet, D., D. Brout, E. Buckley-Geer, D. L. Burke, V., R. Campisano, L. Cardiel-Sas, A. Carnero Rosell, M. Kind, J. Carretero, F. J. Castander, R., C. Chang, X. Chen, C. Conselice, G., M. Crocce, C. E. Cunha, C. B. D\rsquoAndrea, L. N. Costa, R. Das, G. Daues, T. M. Davis, C., J. De Vicente, D. L. DePoy, J. DeRose, S., H. T. Diehl, J. P. Dietrich, S. Dodelson, P., A. Drlica-Wagner, T. F. Eifler, A. E. Elliott, A. E., A. Farahi, A. Fausti Neto, E. Fernandez, D. A., B. Flaugher, R. J. Foley, P. Fosalba, D. N., J. Frieman, J. Garc\ \ia-Bellido, E., D. W. Gerdes, T. Giannantonio, M. S. S., K. Glazebrook, D. A. Goldstein, M., D. Gruen, R. A. Gruendl, J. Gschwend, R. R., G. Gutierrez, S. Hamilton, W. G. Hartley, S. R., J. M. Hislop, D. Hollowood, K., B. Hoyle, D. Huterer, B. Jain, D. J., T. Jeltema, M. W. G. Johnson, M. D., T. Kacprzak, S. Kent, G. Khullar, M., A. Kovacs, A. M. G. Koziol, E. Krause, A., R. Kron, K. Kuehn, S. Kuhlmann, N., O. Lahav, J. Lasker, T. S. Li, R. T., A. R. Liddle, M. Lima, H. Lin, P., N. MacCrann, M. A. G. Maia, J. D., M. Manera, M. March, J. Marriner, J. L., P. Martini, T. McClintock, T., R. G. McMahon, P. Melchior, F. Menanteau, C. J., R. Miquel, J. J. Mohr, E. Morganson, J., E. Neilsen, R. C. Nichol, F. Nogueira, B., P. Nugent, L. Nunes, R. L. C. Ogando, L., A. B. Pace, A. Palmese, F. Paz-Chinch\ on, H. V., W. J. Percival, D. Petravick, A. A., J. Poh, C. Pond, A. Porredon, A., A. Refregier, K. Reil, P. M. Ricker, R. P., A. K. Romer, A. Roodman, P. Rooney, A. J., E. S. Rykoff, M. Sako, M. L. Sanchez, E., B. Santiago, A. Saro, V. Scarpine, D., S. Serrano, I. Sevilla-Noarbe, E., N. Shipp, M. L. Silveira, M. Smith, R. C., J. A. Smith, M. Soares-Santos, F., J. Song, A. Stebbins, E. Suchyta, M., M. E. C. Swanson, G. Tarle, J. Thaler, D., R. C. Thomas, M. A. Troxel, D. L. Tucker, V., A. K. Vivas, A. R. Walker, R. H. Wechsler, J., W. Wester, R. C. Wolf, H. Wu, B., A. Zenteno, Y. Zhang, J. Zuntz, Collaboration, S. Juneau, M. Fitzpatrick, R., D. Nidever, K. Olsen, A. Scott, N. 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., J. Blazek, B. A. Benson, R. A. Bernstein, G. M., E. Bertin, D. Brooks, D. L. Burke, A. Rosell, M. Carrasco Kind, J. Carretero, F. J., C. L. Chang, T. M. Crawford, C. E., C. B. D Andrea, L. N. da Costa, C., J. DeRose, S. Desai, H. T. Diehl, J. P., P. Doel, A. Drlica-Wagner, A. E., E. Fernandez, B. Flaugher, P. Fosalba, J., J. Garc\ \ia-Bellido, E. Gaztanaga, D. W., T. Giannantonio, D. Gruen, R. A. Gruendl, J., G. Gutierrez, W. G. Hartley, J. W., K. Honscheid, B. Hoyle, D. Huterer, B., D. J. James, M. Jarvis, T. Jeltema, M. D., M. W. G. Johnson, E. Krause, K., S. Kuhlmann, N. Kuropatkin, O. Lahav, A. R., M. Lima, H. Lin, N. MacCrann, M. A. G., A. Manzotti, M. March, J. L. Marshall, R., J. J. Mohr, T. Natoli, P. Nugent, R. L. C., Y. Park, A. A. Plazas, C. L. Reichardt, K., A. Roodman, A. J. Ross, E. Rozo, E. S., E. Sanchez, V. Scarpine, M. Schubnell, D., I. Sevilla-Noarbe, E. Sheldon, M., R. C. Smith, M. Soares-Santos, F. Sobreira, E., G. Tarle, D. Thomas, M. A. Troxel, A. R., R. H. Wechsler, J. Weller, W. Wester, W. L. K. Wu, J. Zuntz, "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., Y. Cao, S. B. Cenko, G. B. Doran, G. E., R. P. Fender, C. Fransson, A. Gal-Yam, A., S. R. Kulkarni, R. R. Laher, R. Lunnan, I., F. Masci, P. A. Mazzali, P. E. Nugent, D. A., T. Petrushevska, A. L. Piro, C., 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., L. Yan, S. R. Kulkarni, R. Lunnan, T., G. Leloudas, A. K. H. Kong, P. E. Nugent, C., R. 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

K. De, M. M. Kasliwal, T. Cantwell, Y. Cao, S. B., A. Gal-Yam, J. Johansson, A. Kong, S. R., R. Lunnan, F. Masci, M. Matuszewski, K. P., J. D. Neill, P. E. Nugent, E. O. Ofek, Y., U. D. Rebbapragada, A. Rubin, D. O\rsquo Sullivan, O. 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

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

C. Frohmaier, M. Sullivan, K. Maguire, P. 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

S. M. Adams, N. Blagorodnova, M. M. Kasliwal, R., T. Barlow, B. Bue, M. Bulla, Y., S. B. Cenko, D. O. Cook, R. Ferretti, O. D., C. Fremling, S. Gezari, A. Goobar, A. Y. Q., T. Hung, E. Karamehmetoglu, S. R. Kulkarni, T., R. R. Laher, F. J. Masci, A. A. Miller, J. D., 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

D. A. Goldstein, P. E. Nugent, D. N. Kasen, T. 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

A. Y. Q. Ho, S. R. Kulkarni, P. E. Nugent, W., F. Rusu, S. B. Cenko, V. Ravi, M. M., D. A. Perley, S. M. Adams, E. C., P. Brady, C. Fremling, A. Gal-Yam, D. A., D. Kaplan, R. R. Laher, F. Masci, E. O. Ofek, J. Sollerman, A. Urban, "iPTF Archival Search for Fast Optical Transients", Astrophysical Journal Letters, 2018, 854:L13, doi: 10.3847/2041-8213/aaaa62

D. Scolnic, R. Kessler, D. Brout, P. S. Cowperthwaite, M., J. Annis, K. Herner, H.-Y. Chen, M., Z. Doctor, R. E. Butler, A. Palmese, H. T., J. Frieman, D. E. Holz, E. Berger, R., V. A. Villar, M. Nicholl, R. Biswas, R., R. J. Foley, J. Metzger, A. Rest, J., A. M\ oller, P. Nugent, T. M. C., F. B. Abdalla, S. Allam, K., A. Benoit-L\ evy, E. Bertin, D., E. Buckley-Geer, A. Carnero Rosell, M. Kind, J. Carretero, F. J. Castander, C. E., C. B. D Andrea, L. N. da Costa, C., P. Doel, A. Drlica-Wagner, T. F. Eifler, B., P. Fosalba, E. Gaztanaga, D. W. Gerdes, D., R. A. Gruendl, J. Gschwend, G. Gutierrez, W. G., K. Honscheid, D. J. James, M. W. G., M. D. Johnson, E. Krause, K., S. Kuhlmann, O. Lahav, T. S. Li, M., M. A. G. Maia, M. March, J. L. Marshall, F., R. Miquel, E. Neilsen, A. A. Plazas, E., V. Scarpine, M. Schubnell, I. Sevilla-Noarbe, M., R. C. Smith, F. Sobreira, E. Suchyta, M. E. C., 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

A. A. Miller, Y. Cao, A. L. Piro, N. Blagorodnova, B. D., S. B. Cenko, S. Dhawan, R. Ferretti, O. D., C. Fremling, A. Goobar, D. A. Howell, G., M. M. Kasliwal, R. R. Laher, R., 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., A. Gal-Yam, O. Yaron, M. M. Kasliwal, S. R., 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

Fianna O'Brien

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,

Sang-Yun Oh

2018

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,

Leonid Oliker

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,

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,

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,

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,

Drew Paine

2018

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

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

Sean Peisert

2018

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

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,

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

Sean Peisert, Security Concerns of an NRP, Second National Research Platform (NRP) Workshop, August 6, 2018,

"A Holistic Approach to Distribution Grid Intrusion Detection Systems", Ciaran Roberts, Anna Scaglione Sean Peisert,, EnergyCentral, July 18, 2018,

Sean Peisert, Cyber Security Challenges and Opportunities in High-Performance Computing Environments, International Supercomputing Conference, June 26, 2018,

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,

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

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,

Terry Benzel and Sean Peisert, Selected Papers from the 2017 IEEE Symposium on Security and Privacy [Guest editors' introduction], IEEE Security and Privacy, Pages: 10-11 January 2018,

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

Talita Perciano

2018

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

Fernando Perez

2018

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

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

Doru Thom Popovici

2018

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,

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,

Doru Thom Popovici, Tze Meng Low, Franz Franchetti, "Large Bandwidth-Efficient FFTs on Multicore and Multi-socket Systems", IPDPS, 2018,

Prabhat

2018

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,

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

Lavanya Ramakrishnan

2018

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

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

GH Weber, C Ophus, L Ramakrishnan, "Automated Labeling of Electron Microscopy Images Using Deep Learning", Proc. 4th Workshop of Machine Learning in HPC Environments (MLHPC), 2018,

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

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,

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

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,

Hannah Ross

2018

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,

Florin Rusu

2018

Weijie Zhao, Florin Rusu, Bin Dong, Kesheng Wu, Anna Ho, and Peter Nugent, "Distributed Caching for Processing Raw Arrays", SSDBM, 2018,

A. Y. Q. Ho, S. R. Kulkarni, P. E. Nugent, W., F. Rusu, S. B. Cenko, V. Ravi, M. M., D. A. Perley, S. M. Adams, E. C., P. Brady, C. Fremling, A. Gal-Yam, D. A., D. Kaplan, R. R. Laher, F. Masci, E. O. Ofek, J. Sollerman, A. Urban, "iPTF Archival Search for Fast Optical Transients", Astrophysical Journal Letters, 2018, 854:L13, doi: 10.3847/2041-8213/aaaa62

Chris Rycroft

2018

Daniel Fortunato, Chris H. Rycroft, Robert Saye, "Efficient operator-coarsening multigrid schemes for local discontinuous Galerkin methods", arXiv:1808.05320, August 16, 2018,

Oliver Rübel

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

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

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

Robert Saye

2018

Daniel Fortunato, Chris H. Rycroft, Robert Saye, "Efficient operator-coarsening multigrid schemes for local discontinuous Galerkin methods", arXiv:1808.05320, August 16, 2018,

Anna Scaglione

2018

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

Oguz Selvitopi

2018

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

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

John M. Shalf

2018

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, 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,

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,

Hongzhang Shan

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,

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,

Meiyue Shao

2018

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

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

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

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

Alex Sim

2018

Tal Shachaf, Alexander Sim, Kesheng Wu, Wilko Kroeger, "Detecting Anomalies in the LCLS Workflow", 3rd workshop on Open Science in Big Data (OSBD 2018), in conjunction with IEEE International Conference on Big Data (Big Data 2018), 2018, doi: 10.1109/bigdata.2018.8622334

A. Lazar, K. Wu, A. Sim, "Predicting Network Traffic Using TCP Anomalies", IEEE International Conference on Big Data (Big Data 2018), 2018, doi: 10.1109/bigdata.2018.8622522

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

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,

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

S. Balasubramanian, D. Ghosal, K. N. Balasubramanian, E. Pouyoul, A. Sim, K. Wu, B. Tierney, "Auto-tuned Publisher in a Pub/Sub System: Design and Performance Evaluation", the 15th IEEE International Conference on Autonomic Computing (ICAC 2018), 2018, doi: 10.1109/icac.2018.00012

J. Wang, K. Wu, A. Sim, S. Hwangbo, "Feature Engineering and Classification Models for Partial Discharge in Power Transformers", Joint Workshop on Deep Learning for Safety-Critical in Engineering Systems (DISE1), in conjunction with ICML, AAMAS, IJCAI, and ECAI 2018, 2018,

C. Dao, X. Liu, J. Jiang, A. Sim, C. E. Tull, K. Wu, "Modeling Data Transfers: Change Point and Anomaly Detection", 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.2018.00177

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

R. Kettimuthu, Z. Liu, I. Foster, P. Beckman, A. Sim, K. Wu, W. Liao, Q. Kang, A. Agrawal, A. Choudhary, "Towards Autonomic Science Infrastructure: Architecture, Limitations, and Open Issues", Workshop in Autonomous Infrastructure for Science (AI-Science 2018), 2018, in conjunction with the 27th International Symposium on High-Performance Parallel and Distributed Computing (ACM HPDC 2018), 2018, doi: 10.1145/3217197.3217205

M. Yang, X. Liu, W. Kroeger, A. Sim, K. Wu, "Identifying Anomalous File Transfer Events in LCLS Workflow", Workshop in Autonomous Infrastructure for Science (AI-Science 2018), 2018, in conjunction with the 27th International Symposium on High-Performance Parallel and Distributed Computing (ACM HPDC 2018), 2018, doi: 10.1145/3217197.3217203

H. Zhan, G. Gomes, X. S. Li, K. Madduri, A. Sim, K. Wu, "Consensus Ensemble System for Traffic Flow Prediction", IEEE Transactions on Intelligent Transportation Systems, 2018, doi: 10.1109/TITS.2018.2791505

T. Kim, J. Choi, D. Lee, A. Sim, C. A. Spurlock, A. Todd, K. Wu, "Predicting Baseline for Analysis of Electricity Pricing", International Journal of Big Data Intelligence. Special issue on Data to Decision, 2018, 5:3-20, doi: 10.1504/IJBDI.2018.10008133

Horst D. Simon

2018

Kesheng Wu, Horst D Simon, "High-Performance Computational Intelligence and Forecasting Technologies", Lawrence Berkeley National Laboratory, 2018,

Houjun Tang

2018

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,

Bin Dong, Teng Wang, Houjun Tang, Quincey Koziol, Kesheng Wu, and Suren Byna, "ARCHIE: Data Analysis Acceleration with Array Caching in Hierarchical Storage", IEEE BigData, 2018, December 10, 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,

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,

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,

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,

Yu-Hang Tang

2018

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,

Rollin Thomas

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,

David Trebotich

2018

roughness cropped

Hang Deng, Sergi Molins, David Trebotich, Carl Steefel, Donald DePaolo, "Pore-scale numerical investigation of the impacts of surface roughness: Up-scaling of reaction rates in rough fractures", Geochimica et Cosmochimica Acta, October 15, 2018, 239:374-389, doi: 10.1016/j.gca.2018.08.005

Craig Tull

2018

C. Dao, X. Liu, J. Jiang, A. Sim, C. E. Tull, K. Wu, "Modeling Data Transfers: Change Point and Anomaly Detection", 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.2018.00177

Miroslav Urbanek

2018

Miroslav Urbanek, Pavel Soldán, "Equilibration in two-dimensional Bose systems with disorders", European Physical Journal D, 2018, 72:114, doi: 10.1140/epjd/e2018-80733-7

Daniela Ushizima

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

Roel Van Beeumen

2018

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

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

Brian Van Straalen

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), November 13, 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.

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 26, 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.

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.

J Bachan, S Baden, D Bonachea, PH Hargrove, S Hofmeyr, K Ibrahim, M Jacquelin, A Kamil, B van Straalen, "UPC++ Programmer’s Guide, v1.0-2018.3.0", March 31, 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.

J Bachan, S Baden, D Bonachea, P Hargrove, S Hofmeyr, K Ibrahim, M Jacquelin, A Kamil, B Lelbach, B van Straalen, "UPC++ Specification v1.0, Draft 6", 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 Hargrove, Steven Hofmeyr, Khaled Ibrahim, Mathias Jacquelin, Amir Kamil, Brian van Straalen, "UPC++ and GASNet: PGAS Support for Exascale Apps and Runtimes", Poster at Exascale Computing Project (ECP) Annual Meeting 2018., February 2018,

Eugene Vecharynski

2018

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

Colin Wahl

2018

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

Bin Wang

2018

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,

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,

Teng Wang

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,

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,

Teng Wang, Suren Byna, Bin Dong, and Houjun Tang, "UniviStor: Integrated Hierarchical and Distributed Storage for HPC", IEEE Cluster 2018., September 1, 2018,

Gunther H. Weber

2018

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

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

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

GH Weber, C Ophus, L Ramakrishnan, "Automated Labeling of Electron Microscopy Images Using Deep Learning", Proc. 4th Workshop of Machine Learning in HPC Environments (MLHPC), 2018,

Samuel W. Williams

2018

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,

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,

Samuel Williams, Roofline on Manycore and Accelerated Systems, ModSim, August 2018,

Samuel Williams, Parallelism and Performance, MolSSI Summer School, August 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,

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,

Charlene Yang, Brian Friesen, Thorsten Kurth, Brandon Cook, Samuel Williams, "Toward Automated Application Profiling on Cray Systems", Cray User Group (CUG), May 2018,

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,

Samuel Williams, Introduction to the Roofline Model, ECP Annual Meeting, February 8, 2018,

Samuel Williams, Advisor Hand-On: Stencil Example, ECP Annual Meeting, February 8, 2018,

Samuel Williams, Performance Modeling and Analysis, CS267 lecture, University of California at Berkeley, January 30, 2018,

David Bruce Williams-Young

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

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

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

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

Nicholas J. Wright

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,

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,

Kesheng Wu

2018

Tal Shachaf, Alexander Sim, Kesheng Wu, Wilko Kroeger, "Detecting Anomalies in the LCLS Workflow", 3rd workshop on Open Science in Big Data (OSBD 2018), in conjunction with IEEE International Conference on Big Data (Big Data 2018), 2018, doi: 10.1109/bigdata.2018.8622334

A. Lazar, K. Wu, A. Sim, "Predicting Network Traffic Using TCP Anomalies", IEEE International Conference on Big Data (Big Data 2018), 2018, doi: 10.1109/bigdata.2018.8622522

Bin Dong, Teng Wang, Houjun Tang, Quincey Koziol, Kesheng Wu, and Suren Byna, "ARCHIE: Data Analysis Acceleration with Array Caching in Hierarchical Storage", IEEE BigData, 2018, December 10, 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,

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) in SC 2018, November 10, 2018,

S. Balasubramanian, D. Ghosal, K. N. Balasubramanian, E. Pouyoul, A. Sim, K. Wu, B. Tierney, "Auto-tuned Publisher in a Pub/Sub System: Design and Performance Evaluation", the 15th IEEE International Conference on Autonomic Computing (ICAC 2018), 2018, doi: 10.1109/icac.2018.00012

J. Wang, K. Wu, A. Sim, S. Hwangbo, "Feature Engineering and Classification Models for Partial Discharge in Power Transformers", Joint Workshop on Deep Learning for Safety-Critical in Engineering Systems (DISE1), in conjunction with ICML, AAMAS, IJCAI, and ECAI 2018, 2018,

Weijie Zhao, Florin Rusu, Bin Dong, Kesheng Wu, Anna Ho, and Peter Nugent, "Distributed Caching for Processing Raw Arrays", SSDBM, 2018,

C. Dao, X. Liu, J. Jiang, A. Sim, C. E. Tull, K. Wu, "Modeling Data Transfers: Change Point and Anomaly Detection", 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.2018.00177

R. Kettimuthu, Z. Liu, I. Foster, P. Beckman, A. Sim, K. Wu, W. Liao, Q. Kang, A. Agrawal, A. Choudhary, "Towards Autonomic Science Infrastructure: Architecture, Limitations, and Open Issues", Workshop in Autonomous Infrastructure for Science (AI-Science 2018), 2018, in conjunction with the 27th International Symposium on High-Performance Parallel and Distributed Computing (ACM HPDC 2018), 2018, doi: 10.1145/3217197.3217205

M. Yang, X. Liu, W. Kroeger, A. Sim, K. Wu, "Identifying Anomalous File Transfer Events in LCLS Workflow", Workshop in Autonomous Infrastructure for Science (AI-Science 2018), 2018, in conjunction with the 27th International Symposium on High-Performance Parallel and Distributed Computing (ACM HPDC 2018), 2018, doi: 10.1145/3217197.3217203

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,

Junmin Gu, Scott Klasky, Norbert Podhorszki, Ji Qiang, Kesheng Wu, "Querying Large Scientific Data Sets with Adaptable IO System ADIOS", Supercomputing Frontiers (Best Paper Award), Springer International Publishing, 2018, 51-69,

H. Zhan, G. Gomes, X. S. Li, K. Madduri, A. Sim, K. Wu, "Consensus Ensemble System for Traffic Flow Prediction", IEEE Transactions on Intelligent Transportation Systems, 2018, doi: 10.1109/TITS.2018.2791505

T. Kim, J. Choi, D. Lee, A. Sim, C. A. Spurlock, A. Todd, K. Wu, "Predicting Baseline for Analysis of Electricity Pricing", International Journal of Big Data Intelligence. Special issue on Data to Decision, 2018, 5:3-20, doi: 10.1504/IJBDI.2018.10008133

Kesheng Wu, Horst D Simon, "High-Performance Computational Intelligence and Forecasting Technologies", Lawrence Berkeley National Laboratory, 2018,

Kesheng Wu, Surendra Byna, Bin Dong, others, VPIC IO utilities, 2018,

Chao Yang

2018

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

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

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,

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

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

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

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

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

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

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

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

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

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,

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

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,

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,

Katherine Yelick

2018

Giulia Guidi, Marquita Ellis, Daniel Rokhsar, Katherine Yelick, Aydın Buluç, "BELLA: Berkeley Efficient Long-Read to Long-Read Aligner and Overlapper (Preprint)", Submitted, 2018, doi: https://doi.org/10.1101/464420

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,

Jinmei Zhang

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

Weiqun Zhang

2018

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

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

Wibe Albert de Jong

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

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,

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

Other

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,

Charlene Yang, Intel Advisor on Cori, ECP Annual Meeting, February 8, 2018,

C. Fremling, J. Sollerman, M. M. Kasliwal, S. R., C. Barbarino, M. Ergon, E. Karamehmetoglu, F., I. Arcavi, S. B. Cenko, K. Clubb, A. Cia, G. Duggan, A. V. Filippenko, A. Gal-Yam, M. L., A. Horesh, G. Hosseinzadeh, D. A., D. Kuesters, R. Lunnan, T. Matheson, P. E., 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

R. Lunnan, C. Fransson, P. M. Vreeswijk, S. E. Woosley, G., D. A. Perley, R. M. Quimby, L. Yan, N., B. D. Bue, S. B. Cenko, A. De Cia, D. O., C. U. Fremling, P. Gatkine, A. Gal-Yam, M. M., S. R. Kulkarni, F. J. Masci, P. E., 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

T. M. C. Abbott, F. B. Abdalla, A. Alarcon, J., S. Allam, S. Allen, A. Amara, J., J. Asorey, S. Avila, D. Bacon, E., M. Banerji, N. Banik, W. Barkhouse, M., E. Baxter, K. Bechtol, M. R. Becker, A., B. A. Benson, G. M. Bernstein, E., J. Blazek, S. L. Bridle, D. Brooks, D., E. Buckley-Geer, D. L. Burke, M. T. Busha, A., D. Capozzi, A. Carnero Rosell, M. Kind, J. Carretero, F. J. Castander, R., C. Chang, N. Chen, M. Childress, A., C. Conselice, R. Crittenden, M. Crocce, C. E., C. B. D Andrea, L. N. da Costa, R., T. M. Davis, C. Davis, J. De Vicente, D. L., J. DeRose, S. Desai, H. T. Diehl, J. P., S. Dodelson, P. Doel, A. Drlica-Wagner, T. F., A. E. Elliott, F. Elsner, J. Elvin-Poole, J., A. E. Evrard, Y. Fang, E. Fernandez, A., D. A. Finley, B. Flaugher, P. Fosalba, O., J. Frieman, J. Garc\ \ia-Bellido, M., M. Gatti, E. Gaztanaga, D. W., T. Giannantonio, M. S. S. Gill, K., D. A. Goldstein, D. Gruen, R. A., J. Gschwend, G. Gutierrez, S., W. G. Hartley, S. R. Hinton, K., B. Hoyle, D. Huterer, B. Jain, D. J., M. Jarvis, T. Jeltema, M. D. Johnson, M. W. G., T. Kacprzak, S. Kent, A. G. Kim, A., D. Kirk, N. Kokron, A. Kovacs, E., C. Krawiec, A. Kremin, K. Kuehn, S., N. Kuropatkin, F. Lacasa, O. Lahav, T. S., A. R. Liddle, C. Lidman, M. Lima, H., N. MacCrann, M. A. G. Maia, M. Makler, M., M. March, J. L. Marshall, P. Martini, R. G., P. Melchior, F. Menanteau, R., V. Miranda, D. Mudd, J. Muir, A., E. Neilsen, R. C. Nichol, B. Nord, P., R. L. C. Ogando, A. Palmese, J. Peacock, H. V., J. Peoples, W. J. Percival, D., A. A. Plazas, A. Porredon, J. Prat, A., M. M. Rau, A. Refregier, P. M. Ricker, N., R. P. Rollins, A. K. Romer, A. Roodman, R., A. J. Ross, E. Rozo, E. S. Rykoff, M., A. I. Salvador, S. Samuroff, C. S\ anchez, E., B. Santiago, V. Scarpine, R. Schindler, D., L. F. Secco, S. Serrano, I. Sevilla-Noarbe, E., R. C. Smith, M. Smith, J. Smith, M., F. Sobreira, E. Suchyta, G., D. Thomas, M. A. Troxel, D. L. Tucker, B. E., S. A. Uddin, T. N. Varga, P. Vielzeuf, V., A. K. Vivas, A. R. Walker, M. Wang, R. H., J. Weller, W. Wester, R. C. Wolf, B., F. Yuan, A. Zenteno, B. Zhang, Y., 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

C. Contreras, M. M. Phillips, C. R. Burns, A. L., B. J. Shappee, M. D. Stritzinger, C., P. J. Brown, E. Conseil, A. Klotz, P. E., D. Turpin, S. Parker, D. Rabinowitz, E. Y., N. Morrell, A. Campillay, S. Castell\ on, C., C. Gonz\ alez, K. Krisciunas, J., B. E. Tucker, E. S. Walker, E., C. Cain, M. J. Childress, G. Folatelli, W. L., M. Hamuy, P. Hoeflich, S. E. Persson, R. Scalzo, B. Schmidt, N. 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

R. M. Quimby, A. De Cia, A. Gal-Yam, G. Leloudas, R., D. A. Perley, P. M. Vreeswijk, L., J. S. Bloom, S. B. Cenko, J. Cooke, R., A. V. Filippenko, M. M. Kasliwal, I. K. W., S. R. Kulkarni, T. Matheson, P. E., Y.-C. Pan, J. M. Silverman, A. Sternberg, M. Sullivan, O. Yaron, Spectra of Hydrogen-poor Superluminous Supernovae from the Palomar Transient Factory, Astrophysical Journal, Pages: 2 2018, doi: 10.3847/1538-4357/aaac2f

M. Smith, M. Sullivan, R. C. Nichol, L. Galbany, C. B., C. Inserra, C. Lidman, A. Rest, M., A. V. Filippenko, W. Zheng, S. B. Cenko, C. R., P. J. Brown, T. M. Davis, D. A. Finley, R. J., S. Gonz\ alez-Gait\ an, C. P. Guti\ errez, R., S. Kuhlmann, J. Marriner, A. M\ oller, P. E., S. Prajs, R. Thomas, R. Wolf, A., T. M. C. Abbott, F. B. Abdalla, S., J. Annis, K. Bechtol, A. Benoit-L\ evy, E., D. Brooks, D. L. Burke, A. Carnero Rosell, M. Kind, J. Carretero, F. J. Castander, M., C. E. Cunha, L. N. da Costa, C. Davis, S., H. T. Diehl, P. Doel, T. F. Eifler, B., P. Fosalba, J. Frieman, J. Garc\ \ia-Bellido, E., D. W. Gerdes, D. A. Goldstein, D., R. A. Gruendl, J. Gschwend, G. Gutierrez, K., D. J. James, M. W. G. Johnson, K., N. Kuropatkin, T. S. Li, M. Lima, M. A. G., J. L. Marshall, P. Martini, F., C. J. Miller, R. Miquel, R. L. C. Ogando, D., A. A. Plazas, A. K. Romer, E. S. Rykoff, M., E. Sanchez, V. Scarpine, R. Schindler, M., I. Sevilla-Noarbe, R. C. Smith, M., F. Sobreira, E. Suchyta, M. E. C., 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

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,