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.
@article{arxiv.1804.06926,
title = {A Comparative Study on Exact Triangle Counting Algorithms on the GPU},
author = {Leyuan Wang and Yangzihao Wang and Carl Yang and John D. Owens},
journal= {arXiv preprint arXiv:1804.06926},
year = {2018}
}