Quantum Chemistry in Dataflow

Density-Fitting MP2

Journal Article (2017)
Author(s)

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)

Affiliation
External organisation
DOI related publication
https://doi.org/10.1021/acs.jctc.7b00649
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Publication Year
2017
Language
English
Affiliation
External organisation
Issue number
11
Volume number
13
Pages (from-to)
5265-5272

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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