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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Zhang YZhu YZhang HGao CWang YLi GXu TZhong MJiang JQian TZhang CYu J(2025)TGraph: A Tensor-centric Graph Processing FrameworkProceedings of the ACM on Management of Data10.1145/37097313:1(1-27)Online publication date: 11-Feb-2025
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Meng KGeng LLi XTao QYu WZhou J(2023)Efficient Multi-GPU Graph Processing with Remote Work Stealing2023 IEEE 39th International Conference on Data Engineering (ICDE)10.1109/ICDE55515.2023.00022(191-204)Online publication date: Apr-2023
https://doi.org/10.1109/ICDE55515.2023.00022
Wang QZhang YWang HGeng LLee RZhang XYu GMaier DPottinger RDoan ATan WAlawini ANgo H(2020)Automating Incremental and Asynchronous Evaluation for Recursive Aggregate Data ProcessingProceedings of the 2020 ACM SIGMOD International Conference on Management of Data10.1145/3318464.3389712(2439-2454)Online publication date: 11-Jun-2020
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Index Terms

Optimization of asynchronous graph processing on GPU with hybrid coloring model
1. Computing methodologies
  1. Concurrent computing methodologies
    1. Concurrent programming languages
2. Software and its engineering
  1. Software notations and tools
    1. General programming languages
      1. Language types
        Concurrent programming languages

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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

General Chair:
Albert Cohen
INRIA, France
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Program Chair:
David Grove
IBM Research, USA

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
University of Kansas, Lawrence, KS
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Meng KGeng LLi XTao QYu WZhou J(2023)Efficient Multi-GPU Graph Processing with Remote Work Stealing2023 IEEE 39th International Conference on Data Engineering (ICDE)10.1109/ICDE55515.2023.00022(191-204)Online publication date: Apr-2023
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Zhao WTan SLi P(2020)SONG: Approximate Nearest Neighbor Search on GPU2020 IEEE 36th International Conference on Data Engineering (ICDE)10.1109/ICDE48307.2020.00094(1033-1044)Online publication date: Apr-2020
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