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hierarchical partitioning techniques for structured adaptive mesh refinement applications

JOURNAL OF SUPERCOMPUTING 2004年第3期28卷 265-278页

作者： Li, XL Parashar, M Rutgers State Univ Dept Elect & Comp Engn Piscataway NJ 08854 USA

This paper presents the design and preliminary evaluation of hierarchical partitioning and load-balancing techniques for distributed structured adaptive mesh refinement (SAMR) applications. The overall goal of these techniques is to enable the load distribution to reflect the state of the adaptive grid hierarchy and exploit it to reduce synchronization requirements, improve load-balance, and enable concurrent communications and incremental redistribution. The hierarchical partitioning algorithm (HPA) partitions the computational domain into subdomains and assigns them to hierarchical processor groups. Two variants of HPA are presented in this paper. The static hierarchical partitioning algorithm (SHPA) assigns portions of overall load to processor groups. In SHPA, the group size and the number of processors in each group is setup during initialization and remains unchanged during application execution. It is experimentally shown that SHPA reduces communication costs as compared to the Non-HPA scheme, and reduces overall application execution time by up to 59%. The adaptive hierarchical partitioning algorithm (AHPA) dynamically partitions the processor pool into hierarchical groups that match the structure of the adaptive grid hierarchy. Initial evaluations of AHPA show that it can reduce communication costs by up to 70%.

关键词： dynamic load balancing hierarchical partitioning algorithm distributed computing structured adaptive mesh refinement

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hierarchical partitioning techniques for Structured Adaptive Mesh Refinement (SAMR) applications

Hierarchical partitioning techniques for Structured Adaptive...

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31st International Conference on Parallel Processing (ICPP 2002)

作者： Li, XL Ramanathan, S Parashar, M Rutgers State Univ Appl Software Syst Lab Dept Elect & Comp Engn Piscataway NJ 08854 USA

ISBN: (纸本)0769516807

This paper presents the design and preliminary evaluation of hierarchical partitioning and load-balancing techniques for distributed Structured Adaptive Mesh Refinement (SAMR) applications. The overall goal of these techniques is to enable the load distribution to reflect the state of the adaptive grid hierarchy and exploit it to reduce synchronization requirements, improve load-balance, and enable concurrent communications and incremental redistribution. The hierarchical partitioning algorithm (HPA) partitions the computational domain into subdomains and assigns them to hierarchical processor groups. Two variants of HPA are presented in this paper. The Static hierarchical partitioning algorithm (SHPA) assigns portions of overall load to processor groups. In SHPA, the group size and the number of processors in each group is setup during initialization and remains unchanged during application execution. It is experimentally shown that SHRA reduces communication costs as compared to the Non-HPA scheme, and reduces overall application execution time by up to 41%. The Adaptive hierarchical partitioning algorithm (AHPA) dynamically partitions the processor pool into hierarchical groups that match the structure of the adaptive grid hierarchy. Initial evaluations of AHRA show that it can reduce communication costs by up to 70%.

关键词： dynamic load balancing hierarchical partitioning algorithm distributed computing structured adaptive mesh refinement

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hierarchical partitioning techniques for structured adaptive mesh refinement applications

Hierarchical partitioning techniques for structured adaptive...

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4th International Workshop on High Performance Scientific and Engineering Computing with Applications

作者： Li, XL Parashar, M Rutgers State Univ Dept Elect & Comp Engn Piscataway NJ 08854 USA

关键词： dynamic load balancing hierarchical partitioning algorithm distributed computing structured adaptive mesh refinement

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