Document Type

Article

Publication Date

2024

DOI

10.1002/cpe.8244

Publication Title

Concurrency and Computation: Practice and Experience

Volume

36

Issue

23

Pages

E8244

Abstract

Computational chemistry is at the forefront of solving urgent societal problems, such as polymer upcycling and carbon capture. The complexity of modeling these processes at appropriate length and time scales is mainly manifested in the number and types of chemical species involved in the reactions and may require models of several thousand atoms and large basis sets to accurately capture the chemical complexity and heterogeneity in the physical and chemical processes. The quantum chemistry package General Atomic and Molecular Electronic Structure System (GAMESS) has a wide array of methods that can efficiently and accurately treat complex chemical systems. In this work, we have used the GAMESS Effective Fragment Molecule Orbital (EFMO) method for electronic structure calculation of a challenging mesoporous silica nanoparticle (MSN) model surrounded by about 4700 water molecules to investigate the strong scaling and GPU offloading on hybrid CPU-GPU nodes. Experiments were performed on the Perlmutter platform at the National Energy Research Scientific Computing Center. Good strong scaling and load balancing have been observed on up to 88 hybrid nodes for different settings of the execution parameters for the calculation considered here. When GPUs are oversubscribed by offloading work from multiple CPU processes, using the NVIDIA multi-process service (MPS) has consistently reduced time to solution and energy consumed. Additionally, for some configuration parameter settings, oversubscription with MPS improved performance by up to 5.8% over the case without oversubscription.

Rights

© 2024 The Authors.

This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0), which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

Data Availability

Article states: "The data that support the findings of this study are available from the corresponding author upon reasonable request."

Original Publication Citation

Sosonkina, M., Mateescu, G., Xu, P., Sattasathuchana, T., Pham, B., Gordon, M. S., & Leang, S. S. (2024). Runtime performance of a GAMESS quantum chemistry application offloaded to GPUs. Concurrency and Computation: Practice and Experience, 36(23), Article E8244. https://doi.org/10.1002/cpe.8244

ORCID

0009-0005-0223-397X (Sosonkina)

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