Accelerating seismic computations using customized number representations on FPGAs

Authors:
Haohuan Fu;William Osborne;Robert G. Clapp;Oskar Mencer;Wayne Luk
Affiliations:
Department of Computing, Imperial College London, London, UK;Department of Computing, Imperial College London, London, UK;Department of Geophysics, Stanford University, CA;Department of Computing, Imperial College London, London, UK;Department of Computing, Imperial College London, London, UK
Venue:
EURASIP Journal on Embedded Systems - FPGA supercomputing platforms, architectures, and techniques for accelerating computationally complex algorithms
Year:
2009

Citing 10
Cited 3

Elementary functions: algorithms and implementation

Elementary functions: algorithms and implementation
Heuristic datapath allocation for multiple wordlength systems

Proceedings of the conference on Design, automation and test in Europe
Logarithmic Number System and Floating-Point Arithmetics on FPGA

FPL '02 Proceedings of the Reconfigurable Computing Is Going Mainstream, 12th International Conference on Field-Programmable Logic and Applications
Accelerating Seismic Migration Using FPGA-Based Coprocessor Platform

FCCM '04 Proceedings of the 12th Annual IEEE Symposium on Field-Programmable Custom Computing Machines
Précis: A Usercentric Word-Length Optimization Tool

IEEE Design & Test
Optimizing Hardware Function Evaluation

IEEE Transactions on Computers
Synthesis of Arithmetic Circuits: FPGA, ASIC and Embedded Systems

Synthesis of Arithmetic Circuits: FPGA, ASIC and Embedded Systems
Optimizing Logarithmic Arithmetic on FPGAs

FCCM '07 Proceedings of the 15th Annual IEEE Symposium on Field-Programmable Custom Computing Machines
ASC: a stream compiler for computing with FPGAs

IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Accuracy-Guaranteed Bit-Width Optimization

IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems

Hardware/software co-design for energy-efficient seismic modeling

Proceedings of 2011 International Conference for High Performance Computing, Networking, Storage and Analysis
Revisiting finite difference and spectral migration methods on diverse parallel architectures

Computers & Geosciences
FPGA-based architecture to speed-up scientific computation in seismic applications

International Journal of High Performance Systems Architecture

Quantified Score

Hi-index	0.00

Visualization

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.