Quantum Chemistry in Dataflow: Density-Fitting MP2.

JOURNAL OF CHEMICAL THEORY AND COMPUTATION(2017)

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摘要
We demonstrate the use of dataflow technology in the computation of the correlation energy in molecules at the Moller-Plesset perturbation theory (MP2) level. Specifically, we benchmark density fitting (DF)-MP2 for as many as 168 atoms (in valinomycin) and show that speed-ups between 3 and 3.8 times can be achieved when compared to the MOLPRO package run on a single CPU. Acceleration is achieved by offloading the matrix multiplications steps in DF-MP2 to Dataflow Engines (DFEs). We project that the acceleration factor could be as much as 24 with the next generation of DFEs.
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