在高性能计算集群上将 GROMACS 分子动力学代码扩展至 65k CPU 内核

IF 3.4 3区 化学 Q2 CHEMISTRY, MULTIDISCIPLINARY
Carsten Kutzner, Vedran Miletić, Karen Palacio Rodríguez, Markus Rampp, Gerhard Hummer, Bert L. de Groot, Helmut Grubmüller
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Scaling of the GROMACS Molecular Dynamics Code to 65k CPU Cores on an HPC Cluster

Scaling of the GROMACS Molecular Dynamics Code to 65k CPU Cores on an HPC Cluster

We benchmarked the performance of the GROMACS 2024 molecular dynamics (MD) code on a modern high-performance computing (HPC) cluster with AMD CPUs on up to 65,536 CPU cores. We used five different MD systems, ranging in size from about 82,000 to 204 million atoms, and evaluated their performance using two different Message Passing Interface (MPI) libraries, Intel-MPI and Open-MPI. The largest system showed near-perfect strong scaling up to 512 nodes or 65,536 cores, maintaining a parallel efficiency above 0.9 even at the highest level of parallelization. Energy efficiency for a given number of nodes was generally equal to or slightly better than parallel efficiency. We achieved peak performances of 687 ns/d for the 82k atom system, 116 ns/d for the 53M atom system, and about 35 ns/d for the largest 204M atom system. These results demonstrate that highly optimized software running on a state-of-the-art HPC cluster provides sufficient computing power to simulate biomolecular systems at the mesoscale of viruses and organelles, and potentially small cells in the near future.

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来源期刊
CiteScore
6.60
自引率
3.30%
发文量
247
审稿时长
1.7 months
期刊介绍: This distinguished journal publishes articles concerned with all aspects of computational chemistry: analytical, biological, inorganic, organic, physical, and materials. The Journal of Computational Chemistry presents original research, contemporary developments in theory and methodology, and state-of-the-art applications. Computational areas that are featured in the journal include ab initio and semiempirical quantum mechanics, density functional theory, molecular mechanics, molecular dynamics, statistical mechanics, cheminformatics, biomolecular structure prediction, molecular design, and bioinformatics.
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