Graphs, matrices, and the GraphBLAS: Seven good reasons

Jeremy Kepner, David Bader, Aydin Buluç, John Gilbert, Timothy Mattson, Henning Meyerhenke

Research output: Contribution to journalConference articlepeer-review

27 Scopus citations

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 matrix-based 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 matrix-based 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.

Original languageEnglish (US)
Pages (from-to)2453-2462
Number of pages10
JournalProcedia Computer Science
Volume51
Issue number1
DOIs
StatePublished - 2015
Externally publishedYes
EventInternational Conference on Computational Science, ICCS 2002 - Amsterdam, Netherlands
Duration: Apr 21 2002Apr 24 2002

All Science Journal Classification (ASJC) codes

  • General Computer Science

Keywords

  • Algorithms
  • Graphs
  • Linear algebra
  • Matrices
  • Software standards

Fingerprint

Dive into the research topics of 'Graphs, matrices, and the GraphBLAS: Seven good reasons'. Together they form a unique fingerprint.

Cite this