Parallel and Distributed Processing Symposium, International (2001)
San Francisco, California, USA
Apr. 23, 2001 to Apr. 27, 2001
Graph partitioning is an important tool for dividing work amongst processors of a parallel machine, but it is unsuitable for some important applications. Specifically, graph partitioning requires the work per processor to be a simple sum of vertex weights. For many applications, this assumption is not true - the work (or memory) is a complex function of the partition. In this paper we describe a general framework for addressing such partitioning problems and investigate its utility on two applications -partitioning so that overlapped subdomains are balanced and partitioning to minimize the sum of computation plus communication time.
A. Pinar and B. Hendrickson, "Partitioning for Complex Objectives," Parallel and Distributed Processing Symposium, International(IPDPS), San Francisco, California, USA, 2001, pp. 30121.