Accelerating Large-Scale Simulation of Seismic Wave Propagation by Multi-GPUs and Three-Dimensional Domain Decomposition

Abstract

We adopted the GPU (graphics processing unit) to accelerate the large-scale finite-difference simulation of seismic wave propagation. We describe the main part of our implementation: the memory optimization, the three-dimensional domain decomposition, and overlapping communication and computation. With our GPU program, we achieved a very high single-precision performance of about 61 TFlops by using 1,200 GPUs and 1.5 TB of total memory, and a scalability nearly proportional to the number of GPUs on TSUBAME–2.0, the recently installed GPU supercomputer in Tokyo Institute of Technology, Japan. In a realistic application by using 400 GPUs, only a wall clock time of 2,068 s (including the times for the overhead of snapshot output) was required for a complex structure model with more than 13 billion unit cells and 20,000 time steps. We therefore conclude that GPU computing for large-scale simulation of seismic wave propagation is a promising approach.KeywordsGround MotionShared MemoryGlobal MemorySeismic Wave PropagationMemory OptimizationThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.