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Optimization of asynchronous graph processing on GPU with hybrid coloring model

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Published:24 January 2015Publication History
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Abstract

Modern GPUs have been widely used to accelerate the graph processing for complicated computational problems regarding graph theory. Many parallel graph algorithms adopt the asynchronous computing model to accelerate the iterative convergence. Unfortunately, the consistent asynchronous computing requires locking or the atomic operations, leading to significant penalties/overheads when implemented on GPUs. To this end, coloring algorithm is adopted to separate the vertices with potential updating conflicts, guaranteeing the consistency/correctness of the parallel processing. We propose a light-weight asynchronous processing framework called Frog with a hybrid coloring model. We find that majority of vertices (about 80%) are colored with only a few colors, such that they can be read and updated in a very high degree of parallelism without violating the sequential consistency. Accordingly, our solution will separate the processing of the vertices based on the distribution of colors.

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      • Published in

        cover image ACM SIGPLAN Notices
        ACM SIGPLAN Notices  Volume 50, Issue 8
        PPoPP '15
        August 2015
        290 pages
        ISSN:0362-1340
        EISSN:1558-1160
        DOI:10.1145/2858788
        • Editor:
        • Andy Gill
        Issue’s Table of Contents
        • cover image ACM Conferences
          PPoPP 2015: Proceedings of the 20th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming
          January 2015
          290 pages
          ISBN:9781450332057
          DOI:10.1145/2688500

        Copyright © 2015 Owner/Author

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        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 24 January 2015

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