Toward the Minimal Floating Operation Count Cholesky Decomposition of Electron Repulsion Integrals
Author(s) -
Tianyuan Zhang,
Xiaolin Liu,
Edward F. Valeev,
Xiaosong Li
Publication year - 2021
Publication title -
the journal of physical chemistry a
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.756
H-Index - 235
eISSN - 1520-5215
pISSN - 1089-5639
DOI - 10.1021/acs.jpca.1c02317
Subject(s) - cholesky decomposition , benchmark (surveying) , computer science , minimum degree algorithm , parallel computing , speedup , algorithm , computational science , mathematical optimization , mathematics , incomplete cholesky factorization , physics , eigenvalues and eigenvectors , geodesy , quantum mechanics , geography
As quantum chemistry calculations deal with molecular systems of increasing size, the memory requirement to store electron-repulsion integrals (ERIs) greatly outpaces the physical memory available in computing hardware. The Cholesky decomposition of ERIs provides a convenient yet accurate technique to reduce the storage requirement of integrals. Recent developments of a two-step algorithm have drastically reduced the memory operation (MOP) count, leaving the floating operation (FLOP) count as the last frontier of cost reduction in the Cholesky ERI algorithm. In this report, we introduce a dynamic integral tracking, reusing, and compression/elimination protocol embedded in the two-step Cholesky ERI method. Benchmark studies suggest that this technique becomes particularly advantageous when the basis set consists of many computationally expensive high-angular-momentum basis functions. With this dynamic-ERI improvement, the Cholesky ERI approach proves to be a highly efficient algorithm with minimal FLOP and MOP count.
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