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Faster Self-Consistent Field (SCF) Calculations on GPU Clusters

Giuseppe M. J. Barca, Melisa Alkan, Jorge L. Galvez-Vallejo, David Poole, Alistair P. Rendell, Mark S. Gordon

2021Journal of Chemical Theory and Computation62 citationsDOIOpen Access PDF

Abstract

A novel implementation of the self-consistent field (SCF) procedure specifically designed for high-performance execution on multiple graphics processing units (GPUs) is presented. The algorithm offloads to GPUs the three major computational stages of the SCF, namely, the calculation of one-electron integrals, the calculation and digestion of electron repulsion integrals, and the diagonalization of the Fock matrix, including SCF acceleration via DIIS. Performance results for a variety of test molecules and basis sets show remarkable speedups with respect to the state-of-the-art parallel GAMESS CPU code and relative to other widely used GPU codes for both single and multi-GPU execution. The new code outperforms all existing multi-GPU implementations when using eight V100 GPUs, with speedups relative to Terachem ranging from 1.2× to 3.3× and speedups of up to 28× over QUICK on one GPU and 15× using eight GPUs. Strong scaling calculations show nearly ideal scalability up to 8 GPUs while retaining high parallel efficiency for up to 18 GPUs.

Topics & Concepts

Computer scienceParallel computingCUDAComputational scienceGraphicsScalabilityCode (set theory)Field (mathematics)GPU clusterGraphics processing unitSupercomputerGeneral-purpose computing on graphics processing unitsComputer graphics (images)Set (abstract data type)Programming languageMathematicsDatabasePure mathematicsParallel Computing and Optimization TechniquesAdvanced NMR Techniques and ApplicationsAdvanced Data Storage Technologies
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