A Comparative Study on Exact Triangle Counting Algorithms on the GPU

Published: 01 Jan 2016, Last Modified: 06 Nov 2024HPGP@HPDC 2016EveryoneRevisionsBibTeXCC BY-SA 4.0
Abstract: We implement exact triangle counting in graphs on the GPU using three different methodologies: subgraph matching to a triangle pattern; programmable graph analytics, with a set-intersection approach; and a matrix formulation based on sparse matrix-matrix multiplies. All three deliver best-of-class performance over CPU implementations and over comparable GPU implementations, with the graph-analytic approach achieving the best performance due to its ability to exploit efficient filtering steps to remove unnecessary work and its high-performance set-intersection core.
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