DocumentCode :
596548
Title :
Performance analysis of the graph-partitioning algorithms used in OpenFOAM
Author :
Miao Wang ; Yuhua Tang ; Xiaowei Guo ; Xiaoguang Ren
Author_Institution :
State Key Lab. of High Performance Comput., Nat. Univ. of Defence Technol., Changsha, China
fYear :
2012
fDate :
18-20 Oct. 2012
Firstpage :
99
Lastpage :
104
Abstract :
OpenFOAM is a widely used opensource CFD application. Based on mesh partitioned, applications can run in parallel to achieve better performance in OpenFOAM. When mesh generated from the liquid field is large, performance of partitioning algorithms will heavily affect the execution efficiency of the whole application. In this paper, we investigate the four partitioning algorithms implemented in OpenFOAM-Simple, Hierarchical, Scotch and Metis and analyze their performance. Performance evaluation includes partitioning time, communication overhead, quality of load balancing and application´s parallel execution time based on the experiment of LinearPTT with 34,800,000 cells on Tianhe-1A. The results show that Scotch spends the most time on partitioning and Metis´ partitioning time remains steady when the number of processors increases. Both Scotch and Metis introduce less communication overhead than Simple and Hierarchical. Scotch does better in balancing the cells among processors than Metis. When scales of meshes and numbers of processors increase, only Scotch and Metis are practicable with acceptable performance. But their partitioning efficiency still needs a betterment.
Keywords :
C++ language; computational fluid dynamics; graph theory; mesh generation; public domain software; software performance evaluation; LinearPTT; Metis algorithm; OpenFOAM; Scotch algorithm; application parallel execution time; communication overhead; execution efficiency; graph-partitioning algorithms; hierarchical algorithm; load balancing quality; mesh generation; opensource CFD application; partitioning time; performance analysis; performance evaluation; simple algorithm; Algorithm design and analysis; Classification algorithms; Computational fluid dynamics; Computational modeling; Load management; Partitioning algorithms; Program processors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Computational Intelligence (ICACI), 2012 IEEE Fifth International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4673-1743-6
Type :
conf
DOI :
10.1109/ICACI.2012.6463129
Filename :
6463129
Link To Document :
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