"LAGraph: Linear Algebra, Network Analysis Libraries, and the Study of " by Gabor Szarnyas, David A. Bader et al.
 

LAGraph: Linear Algebra, Network Analysis Libraries, and the Study of Graph Algorithms

Document Type

Conference Proceeding

Publication Date

6-1-2021

Abstract

Graph algorithms can be expressed in terms of linear algebra. GraphBLAS is a library of low-level building blocks for such algorithms that targets algorithm developers. LAGraph builds on top of the GraphBLAS to target users of graph algorithms with high-level algorithms common in network analysis. In this paper, we describe the first release of the LAGraph library, the design decisions behind the library, and performance using the GAP benchmark suite. LAGraph, however, is much more than a library. It is also a project to document and analyze the full range of algorithms enabled by the GraphBLAS. To that end, we have developed a compact and intuitive notation for describing these algorithms. In this paper, we present that notation with examples from the GAP benchmark suite.

Identifier

85114442304 (Scopus)

ISBN

[9781665435772]

Publication Title

2021 IEEE International Parallel and Distributed Processing Symposium Workshops Ipdpsw 2021 in Conjunction with IEEE IPDPS 2021

External Full Text Location

https://doi.org/10.1109/IPDPSW52791.2021.00046

First Page

243

Last Page

252

Grant

DM21-0298

Fund Ref

International Business Machines Corporation

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