Quantum Chemistry in Dataflow
Density-Fitting MP2
Bridgette Cooper (Imperial College London)
Stephen Girdlestone (Maxeler Technologies)
Pavel Burovskiy (Maxeler Technologies)
Georgi Gaydadjiev (Maxeler Technologies)
Vitali Averbukh (Imperial College London)
Peter J. Knowles (Cardiff University)
Wayne Luk (Imperial College London)
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Abstract
We demonstrate the use of dataflow technology in the computation of the correlation energy in molecules at the Møller-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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