期刊
SCIENTIFIC PROGRAMMING
卷 20, 期 2, 页码 129-150出版社
HINDAWI LTD
DOI: 10.1155/2012/713587
关键词
Partitioning; load balancing; matrix ordering; fill-reducing ordering; graph coloring; parallel computing; combinatorial scientific computing
资金
- US Department of Energy SciDAC [DE-FC02-06ER2775]
- NSF [CNS-0643969, OCI-0904809, OCI-0904802]
- Office of Advanced Cyberinfrastructure (OAC)
- Direct For Computer & Info Scie & Enginr [0904809] Funding Source: National Science Foundation
Partitioning and load balancing are important problems in scientific computing that can be modeled as combinatorial problems using graphs or hypergraphs. The Zoltan toolkit was developed primarily for partitioning and load balancing to support dynamic parallel applications, but has expanded to support other problems in combinatorial scientific computing, including matrix ordering and graph coloring. Zoltan is based on abstract user interfaces and uses callback functions. To simplify the use and integration of Zoltan with other matrix-based frameworks, such as the ones in Trilinos, we developed Isorropia as a Trilinos package, which supports most of Zoltan's features via a matrix-based interface. In addition to providing an easy-to-use matrix-based interface to Zoltan, Isorropia also serves as a platform for additional matrix algorithms. In this paper, we give an overview of the Zoltan and Isorropia toolkits, their design, capabilities and use. We also show how Zoltan and Isorropia enable large-scale, parallel scientific simulations, and describe current and future development in the next-generation package Zoltan2.
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