Accelerating Seismic Computations Using Customized Number Representations on FPGAs

Abstract

The oil and gas industry has an increasingly large demand for high-performance computation over huge volume of data. Compared to common processors, field-programable gate arrays (FPGAs) can boost the computation performance with a streaming computation architecture and the support for application-specific number representation. With hardware support for reconfigurable number format and bit width, reduced precision can greatly decrease the area cost and I/O bandwidth of the design, thus multiplying the performance with concurrent processing cores on an FPGA. In this paper, we present a tool to determine the minimum number precision that still provides acceptable accuracy for seismic applications. By using the minimized number format, we implement core algorithms in seismic applications (the FK step in forward continued-based migration and 3D convolution in reverse time migration) on FPGA and show speedups ranging from 5 to 7 by including the transfer time to and from the processors. Provided sufficient bandwidth between CPU and FPGA, we show that a further increase to 48times; speedup is possible.