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spammpack, Version 2013-06-18

RESOURCE

Publicly Accessible Repository
https://github.com/FreeON/spammpack
https://doi.org/10.11578/dc.20171025.1446

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Abstract

This library is an implementation of the Sparse Approximate Matrix Multiplication (SpAMM) algorithm introduced. It provides a matrix data type, and an approximate matrix product, which exhibits linear scaling computational complexity for matrices with decay. The product error and the performance of the multiply can be tuned by choosing an appropriate tolerance. The library can be compiled for serial execution or parallel execution on shared memory systems with an OpenMP capable compiler
Release Date:
2014-01-17
Project Type:
Open Source, Publicly Available Repository
Software Type:
Scientific
Licenses:
BSD 3-clause "New" or "Revised" License
Sponsoring Org.:
Code ID:
2573
Site Accession Number:
5091
Research Org.:
Los Alamos National Laboratory
Country of Origin:
United States

RESOURCE

Publicly Accessible Repository
https://github.com/FreeON/spammpack
https://doi.org/10.11578/dc.20171025.1446

SAVE / SHARE



LANL Badge

Citation Formats

spammpack, Version 2013-06-18. Computer Software. https://github.com/FreeON/spammpack. USDOE. 17 Jan. 2014. Web. doi:10.11578/dc.20171025.1446.
(2014, January 17). spammpack, Version 2013-06-18. [Computer software]. https://github.com/FreeON/spammpack. https://doi.org/10.11578/dc.20171025.1446.
"spammpack, Version 2013-06-18." Computer software. January 17, 2014. https://github.com/FreeON/spammpack. https://doi.org/10.11578/dc.20171025.1446.
@misc{ doecode_2573,
title = {spammpack, Version 2013-06-18},
author = ,
abstractNote = {This library is an implementation of the Sparse Approximate Matrix Multiplication (SpAMM) algorithm introduced. It provides a matrix data type, and an approximate matrix product, which exhibits linear scaling computational complexity for matrices with decay. The product error and the performance of the multiply can be tuned by choosing an appropriate tolerance. The library can be compiled for serial execution or parallel execution on shared memory systems with an OpenMP capable compiler},
doi = {10.11578/dc.20171025.1446},
url = {https://doi.org/10.11578/dc.20171025.1446},
howpublished = {[Computer Software] \url{https://doi.org/10.11578/dc.20171025.1446}},
year = {2014},
month = {jan}
}