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Title: A General Sparse Tensor Framework for Electronic Structure Theory

Linear-scaling algorithms must be developed in order to extend the domain of applicability of electronic structure theory to molecules of any desired size. But, the increasing complexity of modern linear-scaling methods makes code development and maintenance a significant challenge. A major contributor to this difficulty is the lack of robust software abstractions for handling block-sparse tensor operations. We therefore report the development of a highly efficient symbolic block-sparse tensor library in order to provide access to high-level software constructs to treat such problems. Our implementation supports arbitrary multi-dimensional sparsity in all input and output tensors. We then avoid cumbersome machine-generated code by implementing all functionality as a high-level symbolic C++ language library and demonstrate that our implementation attains very high performance for linear-scaling sparse tensor contractions.
Authors:
 [1] ;  [2] ;  [3] ; ORCiD logo [1]
  1. Univ. of California, Berkeley, CA (United States). Kenneth S. Pitzer Center for Theoretical Chemistry; Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Chemical Sciences Division
  2. Q-Chem, Inc., Pleasanton, CA (United States)
  3. Univ. of Southern California, Los Angeles, CA (United States). Dept. of Chemistry
Publication Date:
Grant/Contract Number:
AC02-05CH11231
Type:
Accepted Manuscript
Journal Name:
Journal of Chemical Theory and Computation
Additional Journal Information:
Journal Volume: 13; Journal Issue: 3; Journal ID: ISSN 1549-9618
Publisher:
American Chemical Society
Research Org:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org:
USDOE Office of Science (SC), Basic Energy Sciences (BES) (SC-22); USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21)
Country of Publication:
United States
Language:
English
Subject:
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY
OSTI Identifier:
1379778

Manzer, Samuel, Epifanovsky, Evgeny, Krylov, Anna I., and Head-Gordon, Martin. A General Sparse Tensor Framework for Electronic Structure Theory. United States: N. p., Web. doi:10.1021/acs.jctc.6b00853.
Manzer, Samuel, Epifanovsky, Evgeny, Krylov, Anna I., & Head-Gordon, Martin. A General Sparse Tensor Framework for Electronic Structure Theory. United States. doi:10.1021/acs.jctc.6b00853.
Manzer, Samuel, Epifanovsky, Evgeny, Krylov, Anna I., and Head-Gordon, Martin. 2017. "A General Sparse Tensor Framework for Electronic Structure Theory". United States. doi:10.1021/acs.jctc.6b00853. https://www.osti.gov/servlets/purl/1379778.
@article{osti_1379778,
title = {A General Sparse Tensor Framework for Electronic Structure Theory},
author = {Manzer, Samuel and Epifanovsky, Evgeny and Krylov, Anna I. and Head-Gordon, Martin},
abstractNote = {Linear-scaling algorithms must be developed in order to extend the domain of applicability of electronic structure theory to molecules of any desired size. But, the increasing complexity of modern linear-scaling methods makes code development and maintenance a significant challenge. A major contributor to this difficulty is the lack of robust software abstractions for handling block-sparse tensor operations. We therefore report the development of a highly efficient symbolic block-sparse tensor library in order to provide access to high-level software constructs to treat such problems. Our implementation supports arbitrary multi-dimensional sparsity in all input and output tensors. We then avoid cumbersome machine-generated code by implementing all functionality as a high-level symbolic C++ language library and demonstrate that our implementation attains very high performance for linear-scaling sparse tensor contractions.},
doi = {10.1021/acs.jctc.6b00853},
journal = {Journal of Chemical Theory and Computation},
number = 3,
volume = 13,
place = {United States},
year = {2017},
month = {1}
}