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Title: Graphs, matrices, and the GraphBLAS: Seven good reasons

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 ( 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.
 [1] ;  [2] ;  [3] ;  [4] ;  [5] ;  [6]
  1. Massachusetts Inst. of Technology., Cambridge, MA (United States)
  2. Georgia Inst. of Technology, Atlanta, GA (United States)
  3. Lawrence Berkeley National Lab., CA (United States)
  4. Univ. of California, Santa Barbara, CA (United States)
  5. Intel Corporation, Portland, OR (United States)
  6. Karlsruhe Inst. of Technology, Karlsruhe (Germany)
Publication Date:
OSTI Identifier:
Grant/Contract Number:
Accepted Manuscript
Journal Name:
Procedia Computer Science
Additional Journal Information:
Journal Volume: 51; Journal Issue: C; Journal ID: ISSN 1877-0509
Research Org:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Sponsoring Org:
USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21); NSF
Country of Publication:
United States
97 MATHEMATICS AND COMPUTING graphs; algorithms; matrices; linear algebra; software standards