GPU-based monte-carlo simulation for a sea ice load application

High Performance Computing (HPC) has recently been considerably improved, for instance General Purpose computation on Graphics Processing Units (GPGPU) has been developed to accelerate parallel computing by using hundreds of cores simultaneously. GPU computing with Compute Unified Device Architecture (CUDA) is a new approach to solve complex problems and transform the GPU into a massively parallel processor. The present study applies this new technology to a Monte-Carlo simulation for a sea ice load application. The goal of this study is to measure the performance of the GPU and Multi-GPU against the serial Central Processing Unit (CPU), parallel CPU (OpenMP), MATLAB and MATLAB (Parallel for) implementations. Results show a speedup of up to 89,000 times, and reduction in elapsed time from about 3 hours to approximately 0.1 second.

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