Accelerating the SCE-UA Global Optimization Method Based on Multi-Core CPU and Many-Core GPU
The famous global optimization SCE-UA method, which has been widely used in the field of environmental model parameter calibration, is an effective and robust method. However, the SCE-UA method has a high computational load which prohibits the application of SCE-UA to high dimensional and complex pr...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2016-01-01
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| Series: | Advances in Meteorology |
| Online Access: | http://dx.doi.org/10.1155/2016/8483728 |
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| author | Guangyuan Kan Ke Liang Jiren Li Liuqian Ding Xiaoyan He Youbing Hu Mark Amo-Boateng |
| author_facet | Guangyuan Kan Ke Liang Jiren Li Liuqian Ding Xiaoyan He Youbing Hu Mark Amo-Boateng |
| author_sort | Guangyuan Kan |
| collection | DOAJ |
| description | The famous global optimization SCE-UA method, which has been widely used in the field of environmental model parameter calibration, is an effective and robust method. However, the SCE-UA method has a high computational load which prohibits the application of SCE-UA to high dimensional and complex problems. In recent years, the hardware of computer, such as multi-core CPUs and many-core GPUs, improves significantly. These much more powerful new hardware and their software ecosystems provide an opportunity to accelerate the SCE-UA method. In this paper, we proposed two parallel SCE-UA methods and implemented them on Intel multi-core CPU and NVIDIA many-core GPU by OpenMP and CUDA Fortran, respectively. The Griewank benchmark function was adopted in this paper to test and compare the performances of the serial and parallel SCE-UA methods. According to the results of the comparison, some useful advises were given to direct how to properly use the parallel SCE-UA methods. |
| format | Article |
| id | doaj-art-862f0e9db56546a8b085fc7cdc98f615 |
| institution | OA Journals |
| issn | 1687-9309 1687-9317 |
| language | English |
| publishDate | 2016-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Meteorology |
| spelling | doaj-art-862f0e9db56546a8b085fc7cdc98f6152025-08-20T02:08:47ZengWileyAdvances in Meteorology1687-93091687-93172016-01-01201610.1155/2016/84837288483728Accelerating the SCE-UA Global Optimization Method Based on Multi-Core CPU and Many-Core GPUGuangyuan Kan0Ke Liang1Jiren Li2Liuqian Ding3Xiaoyan He4Youbing Hu5Mark Amo-Boateng6State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, Research Center on Flood & Drought Disaster Reduction of the Ministry of Water Resources, China Institute of Water Resources and Hydropower Research, Beijing 100038, ChinaCollege of Hydrology and Water Resources, Hohai University, Nanjing 210098, ChinaState Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, Research Center on Flood & Drought Disaster Reduction of the Ministry of Water Resources, China Institute of Water Resources and Hydropower Research, Beijing 100038, ChinaState Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, Research Center on Flood & Drought Disaster Reduction of the Ministry of Water Resources, China Institute of Water Resources and Hydropower Research, Beijing 100038, ChinaState Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, Research Center on Flood & Drought Disaster Reduction of the Ministry of Water Resources, China Institute of Water Resources and Hydropower Research, Beijing 100038, ChinaHydrologic Bureau (Information Center) of the Huaihe River Commission, Bengbu 233001, ChinaCollege of Hydrology and Water Resources, Hohai University, Nanjing 210098, ChinaThe famous global optimization SCE-UA method, which has been widely used in the field of environmental model parameter calibration, is an effective and robust method. However, the SCE-UA method has a high computational load which prohibits the application of SCE-UA to high dimensional and complex problems. In recent years, the hardware of computer, such as multi-core CPUs and many-core GPUs, improves significantly. These much more powerful new hardware and their software ecosystems provide an opportunity to accelerate the SCE-UA method. In this paper, we proposed two parallel SCE-UA methods and implemented them on Intel multi-core CPU and NVIDIA many-core GPU by OpenMP and CUDA Fortran, respectively. The Griewank benchmark function was adopted in this paper to test and compare the performances of the serial and parallel SCE-UA methods. According to the results of the comparison, some useful advises were given to direct how to properly use the parallel SCE-UA methods.http://dx.doi.org/10.1155/2016/8483728 |
| spellingShingle | Guangyuan Kan Ke Liang Jiren Li Liuqian Ding Xiaoyan He Youbing Hu Mark Amo-Boateng Accelerating the SCE-UA Global Optimization Method Based on Multi-Core CPU and Many-Core GPU Advances in Meteorology |
| title | Accelerating the SCE-UA Global Optimization Method Based on Multi-Core CPU and Many-Core GPU |
| title_full | Accelerating the SCE-UA Global Optimization Method Based on Multi-Core CPU and Many-Core GPU |
| title_fullStr | Accelerating the SCE-UA Global Optimization Method Based on Multi-Core CPU and Many-Core GPU |
| title_full_unstemmed | Accelerating the SCE-UA Global Optimization Method Based on Multi-Core CPU and Many-Core GPU |
| title_short | Accelerating the SCE-UA Global Optimization Method Based on Multi-Core CPU and Many-Core GPU |
| title_sort | accelerating the sce ua global optimization method based on multi core cpu and many core gpu |
| url | http://dx.doi.org/10.1155/2016/8483728 |
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