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Bridgette Cooper¹, Stephen Girdlestone², Pavel Burovskiy²

¹Department of Physics, Blackett Laboratory, Imperial College London , Prince Consort Road, SW7 2AZ London, United Kingdom.

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|October 12, 2017

Summary

This summary is machine-generated.

Dataflow technology accelerates molecular correlation energy calculations using density fitting Møller-Plesset perturbation theory (DF-MP2). This approach achieved 3-3.8x speed-ups, with future potential for 24x acceleration.

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Area of Science:

Computational chemistry
High-performance computing

Background:

Calculating molecular correlation energy is computationally intensive.
Møller-Plesset perturbation theory (MP2) is a standard method for this calculation.
Density fitting (DF) approximations can speed up MP2 calculations.

Purpose of the Study:

To demonstrate the application of dataflow technology for accelerating DF-MP2 calculations.
To benchmark the performance of DF-MP2 on a dataflow engine (DFE).

Main Methods:

Implementing DF-MP2 calculations on a DFE.
Offloading matrix multiplication steps to DFEs for acceleration.
Benchmarking against the MOLPRO package on a single CPU.

Main Results:

Achieved speed-ups of 3 to 3.8 times for DF-MP2 calculations on systems up to 168 atoms (valinomycin).
Demonstrated the effectiveness of DFEs in accelerating computationally demanding steps.

Conclusions:

Dataflow technology offers significant acceleration for DF-MP2 calculations.
Future DFE generations are projected to provide even greater speed-ups (up to 24x).
This approach has the potential to enable larger and more complex molecular simulations.