@inproceedings{63fcc2a5ea8545aabe5925301b0581b4,
title = "A GraphBLAS Implementation of Triangle Centrality",
abstract = "Identifying key members in large social network graphs is an important graph analytic. Recently, a new centrality measure called triangle centrality finds members based on the triangle support of vertices in graph. In this paper, we describe our rapid implementation of triangle centrality using Graph-BLAS, an API specification for describing graph algorithms in the language of linear algebra. We use triangle centrality's algebraic algorithm and easily implement it using the SuiteSparse GraphBLAS library. A set of experiments on large, sparse graph datasets is conducted to verify the implementation.",
keywords = "Graph algorithms, High Performance Data Analytics, Sparse matrix computations",
author = "Fuhuan Li and Bader, {David A.}",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 2021 IEEE High Performance Extreme Computing Conference, HPEC 2021 ; Conference date: 20-09-2021 Through 24-09-2021",
year = "2021",
doi = "10.1109/HPEC49654.2021.9622806",
language = "English (US)",
series = "2021 IEEE High Performance Extreme Computing Conference, HPEC 2021",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2021 IEEE High Performance Extreme Computing Conference, HPEC 2021",
address = "United States",
}