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A dynamic diffusion optimization method for irregular finite element graph partitioning,” The

By Don-lin Yang, Yeh-ching Chung, Chih-chang Chen and Ching-jung Liao


Abstract. To efficiently execute a finite element application program on a distributed memory multicomputer, we need to distribute nodes of a finite element graph to processors of a distributed memory multicomputer as evenly as possible and minimize the communication cost of processors. This partitioning problem is known to be NP-complete. Therefore, many heuristics have been proposed to find satisfactory sub-optimal solutions. Based on these heuristics, many graph partitioners have been developed. Among them, Jostle, Metis, and Party are considered as the best graph partitioners available up-to-date. For these three graph partitioners, in order to minimize the total cut-edges, in general, they allow 3 % to 5 % load imbalance among processors. This is a tradeoff between the communication cost and the computation cost of the partitioning problem. In this paper, we propose an optimization method, the dynamic diffusion method (DDM), to balance the 3 % to 5 % load imbalance allowed by these three graph partitioners while minimizing the total cut-edges among partitioned modules. To evaluate the proposed method, we compare the performance of the dynamic diffusion method with the directed diffusion method and the multilevel diffusion method on an IBM SP2 parallel machine. Three 2D and two 3D irregular finite element graphs are used as test samples. For each test sample, 3 % and 5 % load imbalance situations are tested. From the experimental results, we have the following conclusions. (1) Th

Year: 2013
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