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 |
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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 | |
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 |
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Volume | 2018-September |
ISSN (Print) | 1552-5244 |
Conference
Conference | 2018 IEEE International Conference on Cluster Computing, CLUSTER 2018 |
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Country/Territory | United Kingdom |
City | Belfast |
Period | 9/10/18 → 9/13/18 |
Bibliographical note
Publisher Copyright:© 2018 IEEE.
Keywords
- ERI
- Lossy compression
- Quantum chemistry
- Two-electron repulsion integral
ASJC Scopus subject areas
- Software
- Hardware and Architecture
- Signal Processing