Accelerating the SCE-UA Global Optimization Method Based on Multi-Core CPU and Many-Core GPU

Abstract EN

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.