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Parallel Distributed Breadth First Search on the Kepler Architecture
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DOI：10.1109/TPDS.2015.2475270.png)
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摘要
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We present the results obtained by using an evolution of our CUDA-based solution for the exploration, via a breadth first search, of large graphs. This latest version exploits at its best the features of the Kepler architecture and relies on a combination of techniques to reduce both the number of communications among the GPUs and the amount of exchanged data. The final result is a code that can visit more than 800 billion edges in a second by using a cluster equipped with 4,096 Tesla K20X GPUs.
Keyword:
Large graphs
breadth first search
parallel computing
GPU
CUDA
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