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High Performance and Scalable GPU Graph Traversal

Merrill, Duane; Garland, Michael; Grimshaw, Andrew
Format
Report
Author
Merrill, Duane
Garland, Michael
Grimshaw, Andrew
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 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. Note: Abstract extracted from PDF text
Language
English
Date Received
2012-10-29
Published
University of Virginia, Department of Computer Science, 2011
Published Date
2011
Rights
All rights reserved (no additional license for public reuse)
Collection
Libra Open Repository

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