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- W1983582642 abstract "Simple algorithms for the execution of a Breadth First Search on large graphs lead, running on clusters of GPUs, to a situation of load unbalance among threads and un-coalesced memory accesses, resulting in pretty low performances. To obtain a significant improvement on a single GPU and to scale by using multiple GPUs, we resort to a suitable combination of operations to rearrange data before processing them. We propose a novel technique for mapping threads to data that achieves a perfect load balance by leveraging prefix-sum and binary search operations. To reduce the communication overhead, we perform a pruning operation on the set of edges that needs to be exchanged at each BFS level. The result is an algorithm that exploits at its best the parallelism available on a single GPU and minimizes communication among GPUs. We show that a cluster of GPUs can efficiently perform a distributed BFS on graphs with billions of nodes." @default.
- W1983582642 created "2016-06-24" @default.
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- W1983582642 date "2013-09-01" @default.
- W1983582642 modified "2023-10-18" @default.
- W1983582642 title "Efficient breadth first search on multi-GPU systems" @default.
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- W1983582642 doi "https://doi.org/10.1016/j.jpdc.2013.05.007" @default.
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