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

Ali Murat Gok, Sheng Di, Yuri Alexeev, Dingwen Tao, Vladimir Mironov, Xin Liang, Franck Cappello

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

23 Scopus citations


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(N-4) 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.

Original languageEnglish
Title of host publicationProceedings - 2018 IEEE International Conference on Cluster Computing, CLUSTER 2018
Number of pages11
ISBN (Electronic)9781538683194
StatePublished - Oct 29 2018
Event2018 IEEE International Conference on Cluster Computing, CLUSTER 2018 - Belfast, United Kingdom
Duration: Sep 10 2018Sep 13 2018

Publication series

NameProceedings - IEEE International Conference on Cluster Computing, ICCC
ISSN (Print)1552-5244


Conference2018 IEEE International Conference on Cluster Computing, CLUSTER 2018
Country/TerritoryUnited Kingdom

Bibliographical note

Funding Information:
ACKNOWLEDGMENTS This research was supported by the Exascale Computing Project (ECP), Project Number: 17-SC-20-SC, a collaborative effort of two DOE organizations – the Office of Science and the National Nuclear Security Administration, responsible for the planning and preparation of a capable exascale ecosystem, including software, applications, hardware, advanced system engineering and early testbed platforms, to support the nation’s exascale computing imperative. This research used resources of the Argonne Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC02-06CH11357.This research is also supported by the National Science Foundation under Grant No. 1619253. APPENDIX

Publisher Copyright:
© 2018 IEEE.


  • ERI
  • Lossy compression
  • Quantum chemistry
  • Two-electron repulsion integral

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Signal Processing


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