Skip to Main content Skip to Navigation
Conference papers

GPU accelerated maximum cardinality matching algorithms for bipartite graphs

Abstract : We design, implement, and evaluate GPU-based algorithms for the maximum cardinality matching problem in bipartite graphs. Such algorithms 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 the GPU implementation of the maximum cardinality matching algorithms. We compare the proposed algorithms with serial and multicore implementations from the literature on a large set of real-life problems where in majority of the cases one of our GPU-accelerated algorithms is demonstrated to be faster than both the sequential and multicore implementations.
Complete list of metadata

Cited literature [18 references]  Display  Hide  Download
Contributor : Equipe Roma Connect in order to contact the contributor
Submitted on : Thursday, January 2, 2014 - 7:46:51 PM
Last modification on : Friday, September 30, 2022 - 4:12:06 AM
Long-term archiving on: : Saturday, April 8, 2017 - 10:35:51 AM


Files produced by the author(s)




Mehmet Deveci, Kamer Kaya, Bora Uçar, Umit V. Catalyurek. GPU accelerated maximum cardinality matching algorithms for bipartite graphs. Euro-Par 2013, Aug 2013, Aachen, Germany. pp.850-861, ⟨10.1007/978-3-642-40047-6_84⟩. ⟨hal-00923449⟩



Record views


Files downloads