We design, implement, and evaluate a GPU-based maximum cardinality matching algorithm on bipartite graphs. Such matchings on bipartite graphs have a variety of applications in computer science, scientific computing, bioinformatics, and other areas. To the best of our knowledge, ours is the first study which focuses on maximum cardinality matchings and provides a GPU implementation. We compare the resulting algorithms with serial and multicore implementations from the literature on a large set of real-life matrices where in majority of the cases our GPU-accelerated algorithm is demonstrated to be faster than both the sequential and multicore implementations.
matchmaker2 extends matchmaker with the additional GPU implementations.
Supplementary materials can be found