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Multi-GPU Graph Analytics
[article]
2017
arXiv
pre-print
We present a single-node, multi-GPU programmable graph processing library that allows programmers to easily extend single-GPU graph algorithms to achieve scalable performance on large graphs with billions of edges. Directly using the single-GPU implementations, our design only requires programmers to specify a few algorithm-dependent concerns, hiding most multi-GPU related implementation details. We analyze the theoretical and practical limits to scalability in the context of varying graph
arXiv:1504.04804v4
fatcat:o2g3vpa6andmnfh33uwu4t3nle