• DocumentCode
    3269985
  • Title

    ePUMA: A novel embedded parallel DSP platform for predictable computing

  • Author

    Wang, Jian ; Sohl, Joar ; Kraigher, Olof ; Liu, Dake

  • Author_Institution
    Dept. of Electr. Eng., Linkoping Univ., Linkoping, Sweden
  • Volume
    5
  • fYear
    2010
  • fDate
    22-24 June 2010
  • Abstract
    In this paper, a novel parallel DSP platform based on master-multi-SIMD architecture is introduced. The platform is named ePUMA [1]. The essential technology is to use separated data access kernels and algorithm kernels to minimize the communication overhead of parallel processing by running the two types of kernels in parallel. ePUMA platform is optimized for predictable computing. The memory subsystem design that relies on regular and predictable memory accesses can dramatically improve the performance according to benchmarking results. As a scalable parallel platform, the chip area is estimated for different number of co-processors. The aim of ePUMA parallel platform is to achieve low power high performance embedded parallel computing with low silicon cost for communications and similar signal processing applications.
  • Keywords
    coprocessors; embedded systems; information retrieval; parallel architectures; parallel memories; communication overhead; coprocessor; data access kernel; data algorithm kernel; ePUMA; embedded parallel DSP platform; embedded parallel computing; master-multiSIMD architecture; memory subsystem design; parallel processing; predictable computing; predictable memory access; scalable parallel platform; Computer architecture; Concurrent computing; Coprocessors; Costs; Digital signal processing; Embedded computing; Kernel; Parallel processing; Signal processing algorithms; Silicon; SIMD architecture; chip multi-processor; conflict-free memory access; data permutation; multi-bank memory;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Education Technology and Computer (ICETC), 2010 2nd International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4244-6367-1
  • Type

    conf

  • DOI
    10.1109/ICETC.2010.5529952
  • Filename
    5529952