PaSTRI: Error-Bounded Lossy Compression for Two-Electron Integrals in Quantum Chemistry


Computation of two-electron repulsion integrals is the critical and the most time-consuming step in a typical parallel quantum chemistry simulation. Such calculations have massive computing and storage requirements, which scale as 𝒪(N4) with the size of a chemical system. Compressing the integral's data and storing it on disk can avoid costly recalculation, significantly speeding the overall quantum chemistry calculations; but it requires a fast compression algorithm. To this end, we developed PaSTRI (Pattern Scaling for Two-electron Repulsion Integrals) and implemented the algorithm in the data compression package SZ. PaSTRI leverages the latent pattern features in the integral dataset and optimizes the calculation of the appropriate number of bits required for the storage of the integral. We have evaluated PaSTRI using integral datasets generated by the quantum chemistry program GAMESS. The results show an excellent 16.8 compression ratio with low overhead, while maintaining 10-10 absolute precision based on user's requirement.

Meeting Name

2018 IEEE International Conference on Cluster Computing, ICCC (2018: Sep. 10-13, Belfast, UK)


Computer Science


This research was supported by the Exascale Computing Project (ECP), Project Number: 17-SC-20-SC. This research is also supported by the National Science Foundation under Grant No. 1619253.

Keywords and Phrases

ERI; Lossy Compression; Quantum Chemistry; Two-Electron Repulsion Integral

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Document Type

Article - Conference proceedings

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© 2018 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

Publication Date

29 Oct 2018