Analysis of GPU-based convolution for acoustic wave propagation modeling with finite differences: Fortran to CUDA-C step-by-step
The University of Texas at Austin
The University of Texas at Austin, 2014
@phdthesis{sadahiro2014analysis,
title={Analysis of GPU-based convolution for acoustic wave propagation modeling with finite differences: Fortran to CUDA-C step-by-step},
author={Sadahiro, Makoto},
year={2014}
}
By projecting observed microseismic data backward in time to when fracturing occurred, it is possible to locate the fracture events in space, assuming a correct velocity model. In order to achieve this task in near real-time, a robust computational system to handle backward propagation, or Reverse Time Migration (RTM), is required. We can then test many different velocity models for each run of the RTM. We investigate the use of a Graphics Processing Unit (GPU) based system using Compute Unified Device Architecture for C (CUDA-C) as the programming language. Our preliminary results show a large improvement in run-time over conventional programming methods based on conventional Central Processing Unit (CPU) computing with Fortran. Considerable room for improvement still remains.
September 13, 2014 by hgpu
