Graphs, matrices, and the GraphBLAS: Seven good reasons
Abstract
The analysis of graphs has become increasingly important to a wide range of applications. Graph analysis presents a number of unique challenges in the areas of (1) software complexity, (2) data complexity, (3) security, (4) mathematical complexity, (5) theoretical analysis, (6) serial performance, and (7) parallel performance. Implementing graph algorithms using matrixbased approaches provides a number of promising solutions to these challenges. The GraphBLAS standard (istcbigdata.org/GraphBlas) is being developed to bring the potential of matrix based graph algorithms to the broadest possible audience. The GraphBLAS mathematically defines a core set of matrixbased graph operations that can be used to implement a wide class of graph algorithms in a wide range of programming environments. This paper provides an introduction to the GraphBLAS and describes how the GraphBLAS can be used to address many of the challenges associated with analysis of graphs.
 Authors:
 Massachusetts Inst. of Technology., Cambridge, MA (United States)
 Georgia Inst. of Technology, Atlanta, GA (United States)
 Lawrence Berkeley National Lab., CA (United States)
 Univ. of California, Santa Barbara, CA (United States)
 Intel Corporation, Portland, OR (United States)
 Karlsruhe Inst. of Technology, Karlsruhe (Germany)
 Publication Date:
 Research Org.:
 Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
 Sponsoring Org.:
 USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC21); National Science Foundation (NSF)
 OSTI Identifier:
 1208646
 Grant/Contract Number:
 AC0205CH11231
 Resource Type:
 Journal Article: Accepted Manuscript
 Journal Name:
 Procedia Computer Science
 Additional Journal Information:
 Journal Volume: 51; Journal Issue: C; Journal ID: ISSN 18770509
 Publisher:
 Elsevier
 Country of Publication:
 United States
 Language:
 English
 Subject:
 97 MATHEMATICS AND COMPUTING; graphs; algorithms; matrices; linear algebra; software standards
Citation Formats
Kepner, Jeremy, Bader, David, Buluç, Aydın, Gilbert, John, Mattson, Timothy, and Meyerhenke, Henning. Graphs, matrices, and the GraphBLAS: Seven good reasons. United States: N. p., 2015.
Web. doi:10.1016/j.procs.2015.05.353.
Kepner, Jeremy, Bader, David, Buluç, Aydın, Gilbert, John, Mattson, Timothy, & Meyerhenke, Henning. Graphs, matrices, and the GraphBLAS: Seven good reasons. United States. doi:10.1016/j.procs.2015.05.353.
Kepner, Jeremy, Bader, David, Buluç, Aydın, Gilbert, John, Mattson, Timothy, and Meyerhenke, Henning. 2015.
"Graphs, matrices, and the GraphBLAS: Seven good reasons". United States.
doi:10.1016/j.procs.2015.05.353. https://www.osti.gov/servlets/purl/1208646.
@article{osti_1208646,
title = {Graphs, matrices, and the GraphBLAS: Seven good reasons},
author = {Kepner, Jeremy and Bader, David and Buluç, Aydın and Gilbert, John and Mattson, Timothy and Meyerhenke, Henning},
abstractNote = {The analysis of graphs has become increasingly important to a wide range of applications. Graph analysis presents a number of unique challenges in the areas of (1) software complexity, (2) data complexity, (3) security, (4) mathematical complexity, (5) theoretical analysis, (6) serial performance, and (7) parallel performance. Implementing graph algorithms using matrixbased approaches provides a number of promising solutions to these challenges. The GraphBLAS standard (istcbigdata.org/GraphBlas) is being developed to bring the potential of matrix based graph algorithms to the broadest possible audience. The GraphBLAS mathematically defines a core set of matrixbased graph operations that can be used to implement a wide class of graph algorithms in a wide range of programming environments. This paper provides an introduction to the GraphBLAS and describes how the GraphBLAS can be used to address many of the challenges associated with analysis of graphs.},
doi = {10.1016/j.procs.2015.05.353},
journal = {Procedia Computer Science},
number = C,
volume = 51,
place = {United States},
year = 2015,
month = 1
}
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