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GraphBLAS information


GraphBLAS Specification
The logo of the GraphBLAS API
StatusReleased
First published29 May 2017 (2017-05-29)
Latest version2.1.0
22 December 2023 (2023-12-22)
DomainGraph algorithms
LicenseCreative Commons Attribution (CC BY) 4.0
Websitegraphblas.org

GraphBLAS (/ˈɡræfˌblɑːz/ ) is an API specification that defines standard building blocks for graph algorithms in the language of linear algebra.[1][2] GraphBLAS is built upon the notion that a sparse matrix can be used to represent graphs as either an adjacency matrix or an incidence matrix. The GraphBLAS specification describes how graph operations (e.g. traversing and transforming graphs) can be efficiently implemented via linear algebraic methods (e.g. matrix multiplication) over different semirings.[3]

The development of GraphBLAS and its various implementations is an ongoing community effort, including representatives from industry, academia, and government research labs.[4][5]

  1. ^ "GraphBLAS". graphblas.org. Retrieved 2021-12-04.
  2. ^ "GraphBLAS: A Programming Specification for Graph Analysis". www.sei.cmu.edu. Retrieved 2019-11-08.
  3. ^ Pereira, Juliana. "High-Performance Graph Algorithms Using Linear Algebra". Central European University, Department of Network and Data Science. Retrieved 13 February 2020.
  4. ^ "People of ACM - Tim Davis". acm.org. Association for Computing Machinery. Retrieved 8 November 2019.
  5. ^ Mattson, Tim; Gabb, Henry. "Graph Analytics: A Foundational Building Block for the Data Analytics World". Tech.Decoded. Intel. Retrieved 14 February 2020.

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