Imaging the earth's interior
Design and exploitation of a high-performance SIMD floating-point unit for Blue Gene/L
IBM Journal of Research and Development
IBM Journal of Research and Development
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When accompanied by the appropriate algorithmic approach, seismic imaging is an application that can take advantage of massively parallel computer systems. Three-dimensional (3D) pre-stack time migration (PSTM) and pre-stack depth migration (PSDM) are key components of seismic imaging and require very large computing resources. In this paper, we show that execution of these algorithms can be dramatically accelerated by massive parallelism. Many oil exploration and service companies purchase supercomputing clusters for performing 3D PSTM and PSDM seismic imaging. The common azimuth migration (CAM) algorithm, ported to many architectures, is particularly well suited to offshore marine applications. This paper describes the porting of the CAM algorithm to the IBM Blue Gene/L™ supercomputer, which requires introducing a second level of parallelism, building a parallel 3D-FFT (fast Fourier transform) routine, optimizing a tridiagonal solver for SIMD (single-instruction, multiple-data) floating-point units, and addressing various I/O concerns. We present results obtained by using up to 16, 368 processors for actual data provided from a marine seismic acquisition. Finally, we provide recommendations for porting other pre-stack algorithms to a massively parallel environment.