Performance Analysis of CP2K Code for Ab Initio Molecular Dynamics on CPUs and GPUs

被引：8

作者：

Yokelson, Dewi ^{[1
]}

Tkachenko, Nikolay, V ^{[2
]}

Robey, Robert ^{[3
]}

Li, Ying Wai ^{[1
]}

Dub, Pavel A. ^{[2
]}

机构：

[1] Los Alamos Natl Lab, Appl Comp Sci Div CCS 7, Los Alamos, NM 87545 USA

[2] Los Alamos Natl Lab, Chem Div C IIAC, Los Alamos, NM 87545 USA

[3] Los Alamos Natl Lab, Computat Phys Div XCP 2, Los Alamos, NM 87545 USA

来源：

JOURNAL OF CHEMICAL INFORMATION AND MODELING | 2022年 / 62卷 / 10期

关键词：

EXCHANGE; ACCURATE;

D O I：

10.1021/acs.jcim.1c01538

中图分类号：

R914 [药物化学];

学科分类号：

100701 ;

摘要：

Using a realistic molecular catalyst system, we conduct scaling studies of ab initio molecular dynamics simulations using the popular CP2K code on both Intel Xeon CPU and NVIDIA V100 GPU architectures. Additional performance improvements were gained by finding more optimal process placement and affinity settings. Statistical methods were employed to understand performance changes in spite of the variability in runtime for each molecular dynamics timestep. Ideal conditions for CPU runs were found when running at least four MPI ranks per node, bound evenly across each socket. This study also showed that fully utilizing processing cores, with one OpenMP thread per core, performed better than when reserving cores for the system. The CPU-only simulations scaled at 70% or more of the ideal scaling up to 10 compute nodes, after which the returns began to diminish more quickly. Simulations on a single 40-core node with two NVIDIA V100 GPUs for acceleration achieved over 3.7x speedup compared to the fastest single 36-core node CPU-only version. These same GPU runs showed a 13% speedup over the fastest time achieved across five CPU-only nodes.

引用

页码：2378 / 2386

页数：9

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