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8th International Symposium on Parallel Architectures,Algorithms and Networks (ISPAN'05)
An FPGA-Based Floating-Point Jacobi Iterative Solver
Las Vegas, Nevada, USA
December 07-December 09
ISBN: 0-7695-2509-1
Gerald R. Morris, University of Southern California
Viktor K. Prasanna, University of Southern California
Within the parallel computing domain, field programmable gate arrays (FPGA) are no longer restricted to their traditional role as substitutes for application-specific integrated circuits as hardware "hidden" from the end user. Several high performance computing vendors offer parallel reconfigurable computers employing user-programmable FPGAs. These exciting new architectures allow end-users to, in effect, create reconfigurable coprocessors targeting the computationally intensive parts of each problem. The increased capability of contemporary FPGAs coupled with the embarrassingly parallel nature of the Jacobi iterative method make the Jacobi method an ideal candidate for hardware acceleration. This paper introduces a parameterized design for a deeply pipelined, highly parallelized IEEE 64-bit floating-point version of the Jacobi method. A Jacobi circuit is implemented using a Xilinx Virtex-II Pro as the target FPGA device. Implementation statistics and performance estimates are presented.
Citation:
Gerald R. Morris, Viktor K. Prasanna, "An FPGA-Based Floating-Point Jacobi Iterative Solver," ispan, pp.420-427, 8th International Symposium on Parallel Architectures,Algorithms and Networks (ISPAN'05), 2005
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