Parallel Minimum Cuts in Near-linear Work and Low Depth
Parallel Minimum Cuts in Near-linear Work and Low Depth
复制标题
近线性工作和低深度的并行最小切削
DOI：
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
Lukas Gianinazzi
中科院分区：
文献类型：
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作者：
Barbara Geissmann;Lukas Gianinazzi
我们介绍了用于计算图中最小切割的第一个接近线性工作和多元素的深度算法，而以前的平行算法具有poly-logritharithmic的深度，至少需要在图形和n vertices和n vertices和n vertices和n vertices和n vertices和dymentice中。 m边缘，我们的算法计算出$ O（m。通过利用最小切割和大约跨越树的最大包装之间的连接来汇总重量，我们的算法在计算最小切割的速度上的界限上有所改善。
We present the first near-linear work and poly-logritharithmic depth algorithm for computing a minimum cut in a graph, while previous parallel algorithms with poly-logarithmic depth required at least quadratic work in the number of vertices. In a graph with n vertices and m edges, our algorithm computes the correct result with high probability in $O(m łog^4 n)$ work and $O(łog^3 n)$ depth. This result is obtained by parallelizing a data structure that aggregates weights along paths in a tree and by exploiting the connection between minimum cuts and approximate maximum packings of spanning trees. In addition, our algorithm improves upon bounds on the number of cache misses incurred to compute a minimum cut.