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arXiv · 2212.08200

Essentials of Parallel Graph Analytics

Muhammad Osama·Serban D. Porumbescu·John D. Owens
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Abstract

We identify the graph data structure, frontiers, operators, an iterative loop structure, and convergence conditions as essential components of graph analytics systems based on the native-graph approach. Using these essential components, we propose an abstraction that captures all the significant programming models within graph analytics, such as bulk-synchronous, asynchronous, shared-memory, message-passing, and push vs. pull traversals. Finally, we demonstrate the power of our abstraction with an elegant modern C++ implementation of single-source shortest path and its required components.

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Muhammad Osama, Serban D. Porumbescu, John D. Owens. 2022-12-15. Essentials of Parallel Graph Analytics. https://doi.org/10.1109/ipdpsw55747.2022.00061

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