Breaking the Million-Electron and 1 EFLOP/s Barriers: Biomolecular-Scale Ab Initio Molecular Dynamics Using MP2 Potentials

dc.contributor.authorStocks, Ryanen
dc.contributor.authorVallejo, Jorge L.Galvezen
dc.contributor.authorYu, Fiona C.Y.en
dc.contributor.authorSnowdon, Calumen
dc.contributor.authorPalethorpe, Eliseen
dc.contributor.authorKurzak, Jakuben
dc.contributor.authorBykov, Dmytroen
dc.contributor.authorBarca, Giuseppe M.J.en
dc.date.accessioned2025-05-23T02:22:50Z
dc.date.available2025-05-23T02:22:50Z
dc.date.issued2024en
dc.description.abstractThe accurate simulation of complex biochemical phenomena has historically been hampered by the computational requirements of high-fidelity molecular-modeling techniques. Quantum mechanical methods, such as ab initio wave-function (WF) theory, deliver the desired accuracy, but have impractical scaling for modeling biosystems with thousands of atoms. Combining molecular fragmentation with MP2 perturbation theory, this study presents an innovative approach that enables biomolecular-scale ab initio molecular dynamics (AIMD) simulations at WF theory level. Leveraging the resolution-of-the-identity approximation for Hartree-Fock and MP2 gradients, our approach eliminates computationally intensive four-center integrals and their gradients, while achieving near-peak performance on modern GPU architectures. The introduction of asynchronous time steps minimizes time step latency, overlapping computational phases and effectively mitigating load imbalances. Utilizing up to 9, 4 0 0 nodes of Frontier and achieving 5 9 % (1006.7 PFLOP/s) of its double-precision floating-point peak, our method enables us to break the million-electron and 1 EFLOP / s barriers for AIMD simulations with quantum accuracy.en
dc.description.sponsorshipThis research used resources from the Oak Ridge Leadership Computing Facility (Contract No. DE-AC05-00OR22725) and the National Energy Research Scientific Computing Center (NERSC, ERCAP0026496), supported by the U.S. Department of Energy. RS and EP thank the National Industry PhD program and QDX Technologies for additional support. The authors also thank Dr. Schnoover from Fluid Numerics for providing access to hardware resources.en
dc.description.statusPeer-revieweden
dc.identifier.isbn9798350352917en
dc.identifier.issn2167-4329en
dc.identifier.scopus85215008025en
dc.identifier.urihttp://www.scopus.com/inward/record.url?scp=85215008025&partnerID=8YFLogxKen
dc.identifier.urihttps://hdl.handle.net/1885/733750836
dc.language.isoenen
dc.publisherIEEE Computer Societyen
dc.relation.ispartofProceedings of SC 2024: International Conference for High Performance Computing, Networking, Storage and Analysisen
dc.relation.ispartofseries2024 International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2024en
dc.relation.ispartofseriesInternational Conference for High Performance Computing, Networking, Storage and Analysis, SCen
dc.rightsCopyright:© 2024 IEEE.en
dc.subjectAIMDen
dc.subjectexascaleen
dc.subjectGPUen
dc.subjectquantumen
dc.subjectTerms-chemistryen
dc.titleBreaking the Million-Electron and 1 EFLOP/s Barriers: Biomolecular-Scale Ab Initio Molecular Dynamics Using MP2 Potentialsen
dc.typeConference paperen
dspace.entity.typePublicationen
local.contributor.affiliationStocks, Ryan; School of Computing, ANU College of Systems and Society, The Australian National Universityen
local.contributor.affiliationVallejo, Jorge L.Galvez; School of Computing, ANU College of Systems and Society, The Australian National Universityen
local.contributor.affiliationYu, Fiona C.Y.; School of Computing, ANU College of Systems and Society, The Australian National Universityen
local.contributor.affiliationSnowdon, Calum; School of Computing, ANU College of Systems and Society, The Australian National Universityen
local.contributor.affiliationPalethorpe, Elise; School of Engineering, ANU College of Systems and Society, The Australian National Universityen
local.contributor.affiliationKurzak, Jakub; Advanced Micro Devicesen
local.contributor.affiliationBykov, Dmytro; Oak Ridge National Laboratoryen
local.contributor.affiliationBarca, Giuseppe M.J.; University of Melbourneen
local.identifier.doi10.1109/SC41406.2024.00015en
local.identifier.essn2167-4337en
local.identifier.pure13e28606-c38c-489f-ac8b-4d6bf5cb6ecfen
local.identifier.urlhttps://www.scopus.com/pages/publications/85215008025en
local.type.statusPublisheden

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