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

doi:10.1109/CLUSTER.2018.00013

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

Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

23 Scopus citations

Abstract

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 language	English
Title of host publication	Proceedings - 2018 IEEE International Conference on Cluster Computing, CLUSTER 2018
Pages	1-11
Number of pages	11
ISBN (Electronic)	9781538683194
DOIs	https://doi.org/10.1109/CLUSTER.2018.00013
State	Published - Oct 29 2018
Event	2018 IEEE International Conference on Cluster Computing, CLUSTER 2018 - Belfast, United Kingdom Duration: Sep 10 2018 → Sep 13 2018

Publication series

Name	Proceedings - IEEE International Conference on Cluster Computing, ICCC
Volume	2018-September
ISSN (Print)	1552-5244

Conference

Conference	2018 IEEE International Conference on Cluster Computing, CLUSTER 2018
Country/Territory	United Kingdom
City	Belfast
Period	9/10/18 → 9/13/18

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.

Keywords

ERI
Lossy compression
Quantum chemistry
Two-electron repulsion integral

ASJC Scopus subject areas

Software
Hardware and Architecture
Signal Processing

Access to Document

10.1109/CLUSTER.2018.00013

Cite this

Gok, A. M., Di, S., Alexeev, Y., Tao, D., Mironov, V., Liang, X., & Cappello, F. (2018). PaSTRI: Error-Bounded Lossy Compression for Two-Electron Integrals in Quantum Chemistry. In Proceedings - 2018 IEEE International Conference on Cluster Computing, CLUSTER 2018 (pp. 1-11). [8514854] (Proceedings - IEEE International Conference on Cluster Computing, ICCC; Vol. 2018-September). https://doi.org/10.1109/CLUSTER.2018.00013

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abstract = "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.",

keywords = "ERI, Lossy compression, Quantum chemistry, Two-electron repulsion integral",

author = "Gok, {Ali Murat} and Sheng Di and Yuri Alexeev and Dingwen Tao and Vladimir Mironov and Xin Liang and Franck Cappello",

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{\textquoteright}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: {\textcopyright} 2018 IEEE.; 2018 IEEE International Conference on Cluster Computing, CLUSTER 2018 ; Conference date: 10-09-2018 Through 13-09-2018",

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Gok, AM, Di, S, Alexeev, Y, Tao, D, Mironov, V, Liang, X & Cappello, F 2018, PaSTRI: Error-Bounded Lossy Compression for Two-Electron Integrals in Quantum Chemistry. in Proceedings - 2018 IEEE International Conference on Cluster Computing, CLUSTER 2018., 8514854, Proceedings - IEEE International Conference on Cluster Computing, ICCC, vol. 2018-September, pp. 1-11, 2018 IEEE International Conference on Cluster Computing, CLUSTER 2018, Belfast, United Kingdom, 9/10/18. https://doi.org/10.1109/CLUSTER.2018.00013

PaSTRI: Error-Bounded Lossy Compression for Two-Electron Integrals in Quantum Chemistry. / Gok, Ali Murat; Di, Sheng; Alexeev, Yuri et al.
Proceedings - 2018 IEEE International Conference on Cluster Computing, CLUSTER 2018. 2018. p. 1-11 8514854 (Proceedings - IEEE International Conference on Cluster Computing, ICCC; Vol. 2018-September).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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

Abstract

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Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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