GO:大型不规则图的out - core Partitioning

Gurneet Kaur, Rajesh K. Gupta
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引用次数: 2

摘要

单pc、基于磁盘的大型不规则图形处理最近得到了广泛的普及。基于磁盘的系统的核心是静态图分区,必须在处理开始之前创建它。通过一次处理一个分区,在一台机器上处理不适合内存的图。然而,最复杂的分区器所使用的多层图分区算法不能在同一台机器上运行,因为它们的内存需求远远超过图的大小。流行的内存高效的Mt-Metis图分区器需要4.8到13.8倍的内存才能将整个图保存在内存中。为了克服这个问题,我们提出了GO out- core图分区器,它可以在单个机器上成功地对大型图进行分区。GO只在整个输入图上执行两次传递:创建平衡分区的分区创建传递和减少切边的分区细化传递。两者都通过基于磁盘的处理以内存受限的方式传递函数。GO成功地对Mt-Metis耗尽内存的大型图进行分区。对于可以通过Mt-Metis在单个机器上成功分区的图,GO产生平衡的8路分区,在可比运行时使用1.9到8.3倍的内存,减少了11.8到76.2倍的切边。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
GO: Out-Of-Core Partitioning of Large Irregular Graphs
Single-PC, disk-based processing of large irregular graphs has recently gained much popularity. At the core of a disk-based system is a static graph partitioning that must be created before the processing starts. By handling one partition at a time, graphs that do not fit in memory are processed on a single machine. However, the multilevel graph partitioning algorithms used by the most sophisticated partitioners cannot be run on the same machine as their memory requirements far exceed the size of the graph. The popular memory efficient Mt-Metis graph partitioner requires 4.8× to 13.8× the memory needed to hold the entire graph in memory. To overcome this problem, we present the GO out-of-core graph partitioner that can successfully partition large graphs on a single machine. GO performs just two passes over the entire input graph, partition creation pass that creates balanced partitions and partition refinement pass that reduces edgecuts. Both passes function in a memory constrained manner via disk-based processing. GO successfully partitions large graphs for which Mt-Metis runs out of memory. For graphs that can be successfully partitioned by Mt-Metis on a single machine, GO produces balanced 8-way partitions with 11.8× to 76.2× fewer edgecuts using 1.9× to 8.3× less memory in comparable runtime.
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