Nuclear Fusion Simulation Code Optimization on GPU Clusters

Abstract

GT5D is a nuclear fusion simulation program which aims to analyze the turbulence phenomena in tokamak plasma. In this research, we optimize it for GPU clusters with multiple GPUs on a node. Based on the profile result of GT5D on a CPU node, we decide to offload the whole of the time development part of the program to GPUs except MPI communication. We achieved 3.37 times faster performance in maximum in function level evaluation, and 2.03 times faster performance in total than the case of CPU-only execution, both in the measurement on high density GPU cluster HA-PACS where each computation node consists of four NVIDIA M2090 GPUs and two Intel Xeon E5-2670 (Sandy Bridge) to provide 16 cores in total. These performance improvements on single GPU corresponds to four CPU cores, not compared with a single CPU core. It includes 53% performance gain with overlapping the communication between MPI processes with GPU calculation.