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Quantum Chemistry in Dataflow: Density-Fitting MP2

Cooper, B; Girdlestone, S; Burovskiy, P; Gaydadjiev, G; Averbukh, V; Knowles, PJ; Luo, W; (2017) Quantum Chemistry in Dataflow: Density-Fitting MP2. Journal of Chemical Theory and Computation , 13 (11) pp. 5265-5272. 10.1021/acs.jctc.7b00649. Green open access

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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.

Type: Article
Title: Quantum Chemistry in Dataflow: Density-Fitting MP2
Open access status: An open access version is available from UCL Discovery
DOI: 10.1021/acs.jctc.7b00649
Publisher version: http://doi.org/10.1021/acs.jctc.7b00649
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Physics and Astronomy
URI: https://discovery-pp.ucl.ac.uk/id/eprint/10052635
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