Journal
ADVANCES IN METEOROLOGY
Volume 2016, Issue -, Pages -Publisher
HINDAWI LTD
DOI: 10.1155/2016/8483728
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Funding
- IWHR Scientific Research Projects of Outstanding Young Scientists Research and Application on the Fast Global Optimization Method for the Xinanjiang Model Parameters Based on the High Performance Heterogeneous Computing [KY1605, JZ0145B052016]
- Specific Research of China Institute of Water Resources and Hydropower Research [Fangji 1240]
- Controlling and Flood Prevention Aided Software Development for Poyang Lake Area of Jiangxi Province [0628-136006104242, JZ0205A432013, SLXMB200902]
- NNSF of China, Numerical Simulation Technology of Flash Flood Based on Godunov Scheme and Its Mechanism Study by Experiment [51509263]
- NNSF of China, Study on the Integrated Assessment Model for Risk and Benefit of Dynamic Control of Reservoir Water Level in Flood Season [51509268]
- NNSF of China, Estimation of Regional Evapotranspiration Using Remotely Sensed Data Based on the Theoretical VFC/LST Trapezoid Space [41501415]
- NVIDIA Corporation
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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.
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