Scalable Hybrid Implementation of Graph Coloring Using MPI and OpenMP

Ahmet Erdem Sarıyüce, Erik Saule, Ümit V. Çatalyürek
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引用次数: 14

Abstract

Graph coloring algorithms are commonly used in large scientific parallel computing either for identifying parallelism or as a tool to reduce computation, such as compressing Hessian matrices. Large scientific computations are nowadays either run on commodity clusters or on large computing platforms. In both cases, the current target platform is hierarchical with distributed memory at the node level and shared memory at the processor level. In this paper, we present a novel hybrid graph coloring algorithm and discuss how to obtain the best performance on such systems from algorithmic, system and engineering perspectives.
使用MPI和OpenMP的图形着色的可伸缩混合实现
图着色算法通常用于大型科学并行计算中,用于识别并行性或作为减少计算的工具,例如压缩Hessian矩阵。如今,大型科学计算要么运行在商品集群上,要么运行在大型计算平台上。在这两种情况下,当前目标平台都是分层的,节点级是分布式内存,处理器级是共享内存。本文提出了一种新的混合图着色算法,并从算法、系统和工程的角度讨论了如何在这种系统上获得最佳性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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