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Title: Pole EXpansion and Selected Inversion (PEXSI)

Abstract

The Pole EXpansion and Selected Inversion method (PEXSI) is a fast method for evaluating certain selected elements of a matrix function. PEXSI is highly scalable on distributed memory parallel machines. For sparse matrices, the PEXSI method can be more efficient than the widely used diagonalization method for evaluating matrix functions, especially when a relatively large number of eigenpairs are needed to be computed in the diagonalization methond

Publication Date:
Research Org.:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDepartment of Energy
Contributing Org.:
Lin Lin, Mathias Jacquelin, Chao Yang
OSTI Identifier:
1231762
Report Number(s):
PEXSI; 003003MLTPL00
2014-072
DOE Contract Number:  
AC02-05CH11231
Resource Type:
Software
Software Revision:
00
Software Package Number:
003003
Software Package Contents:
Software package available from Lawrence Berkeley National Laboratory at the following URL: http://pexsi.github.io/pexsi/
Software CPU:
MLTPL
Open Source:
No
Source Code Available:
Yes
Related Software:
SuperLU_DIST, ParMETIS/PT-SCOTCH
Country of Publication:
United States

Citation Formats

. Pole EXpansion and Selected Inversion (PEXSI). Computer software. Vers. 00. USDepartment of Energy. 1 Mar. 2014. Web.
. (2014, March 1). Pole EXpansion and Selected Inversion (PEXSI) (Version 00) [Computer software].
. Pole EXpansion and Selected Inversion (PEXSI). Computer software. Version 00. March 1, 2014.
@misc{osti_1231762,
title = {Pole EXpansion and Selected Inversion (PEXSI), Version 00},
author = {},
abstractNote = {The Pole EXpansion and Selected Inversion method (PEXSI) is a fast method for evaluating certain selected elements of a matrix function. PEXSI is highly scalable on distributed memory parallel machines. For sparse matrices, the PEXSI method can be more efficient than the widely used diagonalization method for evaluating matrix functions, especially when a relatively large number of eigenpairs are needed to be computed in the diagonalization methond},
doi = {},
url = {https://www.osti.gov/biblio/1231762}, year = {Sat Mar 01 00:00:00 EST 2014},
month = {Sat Mar 01 00:00:00 EST 2014},
note =
}

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