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Parallel multilevel k-way partitioning scheme for irregular graphs

机译:不规则图的并行多级k路分配方案

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In this paper we present a parallel formulation of a multilevel k-way graph partitioning algorithm. The multilevel k-way partitioning algorithm reduces the size of the graph by collapsing vertices and edges (coarsening phase), finds a k-way partition of the smaller graph, and then it constructs a k-way partition for the original graph by projecting and refining the partition to successively finer graphs (uncoarsening phase). A key innovative feature of our parallel formulation is that it utilizes graph coloring to effectively parallelize both the coarsenin and the refinement during the uncoarsening phase. Our algorithm is able to achieve a high degree of concurrency, while maintaining the high quality partitions produced by the serial algorithm. We test our scheme on a large number of graphs from finite element methods, and transportation domains. Our parallel formulation on Cray T3D, produces high quality 128-way partitions on 128 processors in a little over two seconds, for graphs with a million vertices. Thus our parallel algorithm makes it possible to perform dynamic graph partition in adaptive computations without compromising quality.

机译:

在本文中,我们提出了多级k-way图划分算法的并行表述。多级k-way分割算法通过折叠顶点和边缘(粗化阶段)来减小图的大小,找到较小图的k-way分区,然后通过投影和构造原始图的k-way分区。将分区细化为依次更精细的图(不粗化阶段)。我们的平行配方的一个关键创新特征是,它利用图形着色在不粗化阶段有效地并行化了粗蛋白和细化。我们的算法能够实现高度的并发性,同时保持串行算法产生的高质量分区。我们在来自有限元方法和运输领域的大量图形上测试了我们的方案。我们在Cray T3D上的并行表示法在两秒钟多一点的时间内就可以在128个处理器上生成高质量的128路分区,以生成具有一百万个顶点的图形。因此,我们的并行算法使在自适应计算中执行动态图分区成为可能,而不会影响质量。

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