An Efficient RI-MP2 Algorithm for Distributed Many-GPU Architectures.


Journal

Journal of chemical theory and computation
ISSN: 1549-9626
Titre abrégé: J Chem Theory Comput
Pays: United States
ID NLM: 101232704

Informations de publication

Date de publication:
18 Oct 2024
Historique:
medline: 18 10 2024
pubmed: 18 10 2024
entrez: 18 10 2024
Statut: aheadofprint

Résumé

Second-order Møller-Plesset perturbation theory (MP2) using the Resolution of the Identity approximation (RI-MP2) is a widely used method for computing molecular energies beyond the Hartree-Fock mean-field approximation. However, its high computational cost and lack of efficient algorithms for modern supercomputing architectures limit its applicability to large molecules. In this paper, we present the first distributed-memory many-GPU RI-MP2 algorithm explicitly designed to utilize hundreds of GPU accelerators for every step of the computation. Our novel algorithm achieves near-peak performance on GPU-based supercomputers through the development of a distributed memory algorithm for forming RI-MP2 intermediate tensors with zero internode communication, except for a single

Identifiants

pubmed: 39422609
doi: 10.1021/acs.jctc.4c00814
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Auteurs

Calum Snowdon (C)

School of Computing, Australian National University, Canberra 2600, Australia.

Giuseppe M J Barca (GMJ)

School of Computing and Information Systems, University of Melbourne, Melbourne 3010, Australia.

Classifications MeSH