文章基本信息

标题：Better Process Mapping and Sparse Quadratic Assignment
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作者：Christian Schulz ; Jesper Larsson Tr{\"a}ff
期刊名称：LIPIcs : Leibniz International Proceedings in Informatics
电子版ISSN：1868-8969
出版年度：2017
卷号：75
页码：4:1-4:15
DOI：10.4230/LIPIcs.SEA.2017.4
出版社：Schloss Dagstuhl -- Leibniz-Zentrum fuer Informatik
摘要：Communication and topology aware process mapping is a powerful approach to reduce communication time in parallel applications with known communication patterns on large, distributed memory systems. We address the problem as a quadratic assignment problem (QAP), and present algorithms to construct initial mappings of processes to processors as well as fast local search algorithms to further improve the mappings. By exploiting assumptions that typically hold for applications and modern supercomputer systems such as sparse communication patterns and hierarchically organized communication systems, we arrive at significantly more powerful algorithms for these special QAPs. Our multilevel construction algorithms employ recently developed, perfectly balanced graph partitioning techniques and excessively exploit the given communication system hierarchy. We present improvements to a local search algorithm of Brandfass et al. (2013), and decrease the running time by reducing the time needed to perform swaps in the assignment as well as by carefully constraining local search neighborhoods. Experiments indicate that our algorithms not only dramatically speed up local search, but due to the multilevel approach also find much better solutions in practice.
关键词：rank reordering; graph algorithms; process mapping; graph partitioning