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High Performance Exact Triangle Counting on GPUs
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DOI：10.1109/TPDS.2017.2735405.png)
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Abstract
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This paper presents a GPU implementation of the graph triangle counting operation based on the set intersection algorithm. The algorithmis implemented in four kernels optimized for different types of graphs in a code delivering performance higher than the current state-of-the-art and without preprocessing the input graph. At runtime, a lightweight heuristic is used to select the kernel to run based on the specific graph taken as input. In contrast to previous works, the presented approach takes advantage of a set intersection operation implemented via bitmaps. Moreover, the simplicity of the approach allows the code to have limited size and engineering complexity.
Keywords:
Triangle counting
graph processing
GPU computing
parallel computing
big data
CUDA
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