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 = {2017},
month = {10}
}