Large scale plane wave pseudopotential density functional theory calculations on GPU clusters
SC（2011）
摘要
In this work, we present our implementation of the density functional theory (DFT) plane wave pseudopotential (PWP) calculations on GPU clusters. This GPU version is developed based on a CPU DFT-PWP code: PEtot, which can calculate up to a thousand atoms on thousands of processors. Our test indicates that the GPU version can have a ~10 times speed-up over the CPU version. A detail analysis of the speed-up and the scaling on the number of CPU/GPU computing units (up to 256) are presented. The success of our speed-up relies on the adoption a hybrid reciprocal-space and band-index parallelization scheme. As far as we know, this is the first GPU DFT-PWP code scalable to large number of CPU/GPU computing units. We also outlined the future work, and what is needed to further increase the computational speed by another factor of 10.
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关键词
pseudopotential methods,gpu computing unit,large scale plane wave pseudopotential density functional theory calculation,chemistry computing,gpu,large scale plane wave,density functional theory,gpu version,petot,hybrid reciprocal-space parallelization,electronic structure,graphics processing units,gpu dft-pwp code scalable,first-principles,gpu cluster,large number,cpu dft-pwp code,multiprocessing systems,pseudopotential density functional theory,band-index parallelization scheme,gpu clusters,cpu computing units,future work,cpu version,gpu computing units,times speed-up,band-index parallelization,plane wave pseudopotential,vectors,first principles,indexation,indexes,mathematical model,plane waves,wave functions,density function theory,first principle
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