Performance analysis of dynamic load balancing algorithms with variable number of processors |
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| Affiliation: | 1. Department of Electrical and Computer Engineering, University of Texas at Austin, Austin, TX 78712-1085, USA;2. ICES, University of Texas at Austin, Austin, Texas, USA;1. University of the Basque Country UPV/EHU, Donostia-San Sebastián, Spain;2. Institut Universitaire de France & IRISA, University of Rennes 1, France;1. Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China;2. Laboratory for Regional Oceanography and Numerical Modeling, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266237, China;3. Ministry of Education Key Laboratory for Earth System modeling, Department of Earth System Science, Tsinghua University, Beijing 100084, China;4. National Supercomputing Center in Wuxi, Wuxi 214072, China;5. First Institute of Oceanography, State Oceanic Administration, Qingdao 266061, China;6. Joint Center for Global Change Studies, Beijing 100875, China;1. School of Information Technologies, The University of Sydney, Australia;2. Department of Electrical and Computer Engineering, Colorado State University, United States;3. School of Computer Science, RMIT University, Australia |
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| Abstract: | In modern parallel adaptive mesh computations the problem size varies during simulation. In this study we investigate the comparative behavior of four load balancing algorithms when the number of processors is dynamically changed during the lifetime of a multistage parallel computation. The focus is on communication and data movement overheads, total parallel runtime and total resource consumption. We demonstrate the main ideas for the case of six adaptive mesh refinement (AMR) applications with different kinds of growth patterns. The results presented are for a 32 processor Intel cluster connected by Ethernet. |
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