Coupling-aware graph partitioning algorithms: Preliminary study

Maria Predari, Aurélien Esnard
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引用次数: 5

Abstract

In the field of scientific computing, load balancing is a major issue that determines the performance of parallel applications. Nowadays, simulations of real-life problems are becoming more and more complex, involving numerous coupled codes, representing different models. In this context, reaching high performance can be a great challenge. In this paper, we present graph partitioning techniques, called co-partitioning, that address the problem of load balancing for two coupled codes: the key idea is to perform a “coupling-aware” partitioning, instead of partitioning these codes independently, as it is usually done. Finally, we present a preliminary experimental study which compares our methods against the usual approach.
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耦合感知图划分算法:初步研究
在科学计算领域,负载平衡是决定并行应用程序性能的主要问题。目前,对现实问题的仿真变得越来越复杂,涉及大量的耦合代码,代表不同的模型。在这种情况下,达到高性能可能是一个巨大的挑战。在本文中,我们提出了图分区技术,称为协分区,它解决了两个耦合代码的负载平衡问题:关键思想是执行“耦合感知”分区,而不是像通常那样独立地划分这些代码。最后,我们提出了一个初步的实验研究,将我们的方法与通常的方法进行了比较。
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