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.
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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.ucl.ac.uk/id/eprint/10052635 |
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