Evaluating the Performance and Cost of Accelerating Seismic Processing with CUDA, OpenCL, OpenACC, and OpenMP

摘要

The Common Midpoint and Common Reflection Surface methods are computationally demanding seismic processing techniques for improving signal-to-noise ratios. In this paper, we discuss the performance results and the cost-benefit of accelerating these two procedures using CUDA, OpenCL, OpenACC, and OpenMP on CPUs and GPUs. We obtained results on server-class CPUs and state-of-the-art GPUs that show that, while OpenCL and CUDA present the best performance results on GPUs, OpenACC can also be an interesting choice due to its programmability. Among the tested accelerators, GPUs with the Pascal microarchitecture showed the best results for the tested seismic processing methods in terms of raw performance, energy efficiency, and performance per price.