Maximal clique enumeration with data-parallel primitives
- Univ. of Oregon, Eugene, OR (United States)
- Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
The enumeration of all maximal cliques in an undirected graph is a fundamental problem arising in several research areas. We consider maximal clique enumeration on shared-memory, multi-core architectures and introduce an approach consisting entirely of data-parallel operations, in an effort to achieve efficient and portable performance across different architectures. We study the performance of the algorithm via experiments varying over benchmark graphs and architectures. Overall, we observe that our algorithm achieves up to a 33-time speedup and 9-time speedup over state-of-the-art distributed and serial algorithms, respectively, for graphs with higher ratios of maximal cliques to total cliques. Further, we attain additional speedups on a GPU architecture, demonstrating the portable performance of our data-parallel design.
- Research Organization:
- Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)
- DOE Contract Number:
- AC02-05CH11231
- OSTI ID:
- 1440003
- Resource Relation:
- Conference: 7th IEEE Symposium on Large Data Analysis and Visualization (LDAV), Phoenix, AZ (United States), 2 Oct 2017
- Country of Publication:
- United States
- Language:
- English
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