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Title: Performance Evaluation of NWChem Ab-Initio Molecular Dynamics (AIMD) Simulations on the Intel® Xeon Phi™ Processor

Abstract

Ab-initio Molecular Dynamics (AIMD) methods are an important class of algorithms, as they enable scientists to understand the chemistry and dynamics of molecular and condensed phase systems while retaining a first-principles-based description of their interactions. Many-core architectures such as the Intel® Xeon Phi™ processor are an interesting and promising target for these algorithms, as they can provide the computational power that is needed to solve interesting problems in chemistry. In this paper, we describe the efforts of refactoring the existing AIMD plane-wave method of NWChem from an MPI-only implementation to a scalable, hybrid code that employs MPI and OpenMP to exploit the capabilities of current and future many-core architectures. We describe the optimizations required to get close to optimal performance for the multiplication of the tall-and-skinny matrices that form the core of the computational algorithm. We present strong scaling results on the complete AIMD simulation for a test case that simulates 256 water molecules and that strong-scales well on a cluster of 1024 nodes of Intel Xeon Phi processors. We compare the performance obtained with a cluster of dual-socket Intel® Xeon® E5–2698v3 processors.

Authors:
; ; ; ;
Publication Date:
Research Org.:
Pacific Northwest National Laboratory (PNNL), Richland, WA (US), Environmental Molecular Sciences Laboratory (EMSL)
Sponsoring Org.:
USDOE
OSTI Identifier:
1411925
Report Number(s):
PNNL-SA-130899
49691; KC0302060
DOE Contract Number:
AC05-76RL01830
Resource Type:
Conference
Resource Relation:
Conference: International Conference on High Performance Computing, June 18-22, 2017, Frankfurt, Germany. Lecture Notes in Computer Science, 10524:404-418
Country of Publication:
United States
Language:
English
Subject:
Environmental Molecular Sciences Laboratory

Citation Formats

Bylaska, Eric J., Jacquelin, Mathias, De Jong, Wibe A., Hammond, Jeff R., and Klemm, Michael. Performance Evaluation of NWChem Ab-Initio Molecular Dynamics (AIMD) Simulations on the Intel® Xeon Phi™ Processor. United States: N. p., 2017. Web. doi:10.1007/978-3-319-67630-2_30.
Bylaska, Eric J., Jacquelin, Mathias, De Jong, Wibe A., Hammond, Jeff R., & Klemm, Michael. Performance Evaluation of NWChem Ab-Initio Molecular Dynamics (AIMD) Simulations on the Intel® Xeon Phi™ Processor. United States. doi:10.1007/978-3-319-67630-2_30.
Bylaska, Eric J., Jacquelin, Mathias, De Jong, Wibe A., Hammond, Jeff R., and Klemm, Michael. Fri . "Performance Evaluation of NWChem Ab-Initio Molecular Dynamics (AIMD) Simulations on the Intel® Xeon Phi™ Processor". United States. doi:10.1007/978-3-319-67630-2_30.
@article{osti_1411925,
title = {Performance Evaluation of NWChem Ab-Initio Molecular Dynamics (AIMD) Simulations on the Intel® Xeon Phi™ Processor},
author = {Bylaska, Eric J. and Jacquelin, Mathias and De Jong, Wibe A. and Hammond, Jeff R. and Klemm, Michael},
abstractNote = {Ab-initio Molecular Dynamics (AIMD) methods are an important class of algorithms, as they enable scientists to understand the chemistry and dynamics of molecular and condensed phase systems while retaining a first-principles-based description of their interactions. Many-core architectures such as the Intel® Xeon Phi™ processor are an interesting and promising target for these algorithms, as they can provide the computational power that is needed to solve interesting problems in chemistry. In this paper, we describe the efforts of refactoring the existing AIMD plane-wave method of NWChem from an MPI-only implementation to a scalable, hybrid code that employs MPI and OpenMP to exploit the capabilities of current and future many-core architectures. We describe the optimizations required to get close to optimal performance for the multiplication of the tall-and-skinny matrices that form the core of the computational algorithm. We present strong scaling results on the complete AIMD simulation for a test case that simulates 256 water molecules and that strong-scales well on a cluster of 1024 nodes of Intel Xeon Phi processors. We compare the performance obtained with a cluster of dual-socket Intel® Xeon® E5–2698v3 processors.},
doi = {10.1007/978-3-319-67630-2_30},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Fri Oct 20 00:00:00 EDT 2017},
month = {Fri Oct 20 00:00:00 EDT 2017}
}

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