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04-17-12, 03:20 PM
Abstract:

Breadth-first search (BFS) is a core primitive for graph traversal and a basis for many higher-level graph analysis algorithms. It is also representative of a class of parallel computations whose memory accesses and work distribution are both irregular and data-dependent. Recent work has demonstrated the plausibility of GPU sparse graph traversal, but has tended to focus on asymptotically inefficient algorithms that perform poorly on graphs with non-trivial diameter.

We present a BFS parallelization focused on fine-grained task management constructed from efficient prefix sum that achieves an asymptotically optimal O(|V|+|E|) work complexity. Our implementation delivers excellent performance on diverse graphs, achieving traversal rates in excess of 3.3 billion and 8.3 billion traversed edges per second using single and quad-GPU configurations, respectively. This level of performance is several times faster than state-of-the-art implementations both CPU and GPU platforms.

(Duane Merrill, Michael Garland and ¬*Andrew Grimshaw: ‚??Scalable GPU graph traversal‚??,¬*Proceedings of the 17th ACM SIGPLAN symposium on Principles and Practice of Parallel Programming (PPoPP‚??12), pp.117-128, Feburary 2012. [DOI (http://dx.doi.org/10.1145/2145816.2145832)])



More... (http://gpgpu.org/2012/04/17/scalable-gpu-graph-traversal)