Implementation and Performance of a GPU-Based Monte-Carlo Framework for Determining Design Ice Load

Abstract

Modern Graphics Processing Units (GPUs) with massive number of threads and many-core architecture support both graphics and general purpose computing. NVIDIA's compute unified device architecture (CUDA) takes advantage of parallel computing and utilizes the tremendous power of GPUs. The present study demonstrates a high performance computing (HPC) framework for a Monte-Carlo simulation to determine design sea ice loads which is implemented in both GPU and CPU. Results show a speedup of up to 130 times for the 4 Tesla K80 GPUs over an optimized CPU OpenMP implementation and speedup of up to 8 times for the 4 Tesla K80 over a single Tesla K80 GPU implementation. The elapsed time of the different implementations has been reduced from about 2.5 hours to 0.7 seconds.