• DocumentCode
    624350
  • Title

    A practical measure of FPGA floating point acceleration for High Performance Computing

  • Author

    Cappello, John D. ; Strenski, Dave

  • Author_Institution
    Optimal Design, Inc., Sewell, NJ, USA
  • fYear
    2013
  • fDate
    5-7 June 2013
  • Firstpage
    160
  • Lastpage
    167
  • Abstract
    A key enabler for Field Programmable Gate Arrays (FPGAs) in High Performance Computing (HPC) has been the addition of hard arithmetic cores. These “slices of DSP” dedicated to accelerated number crunching allow FPGAs to deliver more computing muscle, especially for floating point algorithms. This paper compares how an FPGA\´s performance in a practical HPC application measures up to its theoretical capacity. The implementation of a floating point matrix multiplication algorithm based on a 12x12 MAC (MultiplyAccumulate) array targeting the Xilinx Virtex 7 XT family is described. Several design techniques were used to ensure uninterrupted systolic operation of the array throughout execution, including a novel approach to handling heavily pipelined accumulators, as well as a scheme for overcoming the inherent inefficiencies of DDR3 memory. The result is a sustained "practical" performance range of 144-180 GFLOPS, compared to the target device\´s "theoretical" range of 257-290 GFLOPS.
  • Keywords
    field programmable gate arrays; floating point arithmetic; logic design; FPGA floating point acceleration; GFLOPS; HPC; MAC; field programmable gate array; high performance computing; matrix multiplication algorithm; multiply-accumulate array; systolic operation; Adders; Algorithm design and analysis; Arrays; Clocks; Field programmable gate arrays; Parallel processing; DSP48; FPGA; GFLOPS; Virtex-7; Xilinx; floating point arithmetic; hardware acceleration; heavily-pipelined accumulators; high performance computing; matrix multiplication; multiply-accumulate; systolic array;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Application-Specific Systems, Architectures and Processors (ASAP), 2013 IEEE 24th International Conference on
  • Conference_Location
    Washington, DC
  • ISSN
    2160-0511
  • Print_ISBN
    978-1-4799-0494-5
  • Type

    conf

  • DOI
    10.1109/ASAP.2013.6567570
  • Filename
    6567570