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Accelerating Actor-Based Distributed Triangle Counting

DescriptionTriangle counting is a cornerstone operation in large graph analytics. It has been a challenging problem historically, owing to the irregular and dynamic nature of the algorithm, which not only inhibits compile-time optimizations, but also requires runtime optimizations such as message aggregation and load-imbalance mitigation. Popular triangle counting algorithms are either inherently slow, fail to take advantage of available vectorization in modern processors, or involve sparse matrix operations. With its support for fine-grained asynchronous messages, the Partitioned Global Address Space (PGAS) with the Actor model has been identified to be efficient for irregular applications. However, few triangle counting implementations have been optimally implemented on top of PGAS Actor runtimes. To address the above mentioned challenges, we propose a set-intersection-based implementation of a distributed triangle counting algorithm atop the PGAS Actor runtime. Evaluation of our approach on the PACE Phoenix cluster and the Perlmutter supercomputer shows encouraging results.

Authors

Aniruddha Mysore

Georgia Institute of Technology

Kaushik Ravichandran

Georgia Institute of Technology

Youssef Elmougy

Georgia Institute of Technology

Akihiro Hayashi

Georgia Institute of Technology