• DocumentCode
    2487524
  • Title

    RDMS: A hardware task scheduling algorithm for Reconfigurable Computing

  • Author

    Huang, Miaoqing ; Simmler, Harald ; Serres, Olivier ; El-Ghazawi, Tarek

  • Author_Institution
    Dept. of Electr. & Comput. Eng., George Washington Univ., Washington, DC, USA
  • fYear
    2009
  • fDate
    23-29 May 2009
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    Reconfigurable computers (RC) can provide significant performance improvement for domain applications. However, wide acceptance of today´s RCs among domain scientist is hindered by the complexity of design tools and the required hardware design experience. Recent developments in HW/SW co-design methodologies for these systems provide the ease of use, but they are not comparable in performance to manual co-design. This paper aims at improving the overall performance of hardware tasks assigned to FPGA devices by minimizing both the communication overhead and configuration overhead, which are introduced by using FPGA devices. The proposed reduced data movement scheduling (RDMS) algorithm takes data dependency among tasks, hardware task resource utilization, and inter-task communication into account during the scheduling process and adopts a dynamic programming approach to reduce the communication between muP and FPGA co-processor and the number of FPGA configurations to a minimum. Compared to two other approaches that consider data dependency and hardware resource utilization only, RDMS algorithm can reduce inter-configuration communication time by 11% and 44% respectively based on simulation using randomly generated data flow graphs. The implementation of RDMS on a real-life application, N-body simulation, verifies the efficiency of RDMS algorithm against other approaches.
  • Keywords
    coprocessors; data flow graphs; dynamic programming; field programmable gate arrays; processor scheduling; reconfigurable architectures; resource allocation; FPGA coprocessor; FPGA device; N-body simulation; RDMS algorithm; communication overhead; configuration overhead; data dependency; data flow graph; dynamic programming; hardware task resource utilization; hardware task scheduling; intertask communication; reconfigurable computing; reduced data movement scheduling; Application software; Computational modeling; Coprocessors; Dynamic scheduling; Field programmable gate arrays; Hardware; High performance computing; Partitioning algorithms; Resource management; Scheduling algorithm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Parallel & Distributed Processing, 2009. IPDPS 2009. IEEE International Symposium on
  • Conference_Location
    Rome
  • ISSN
    1530-2075
  • Print_ISBN
    978-1-4244-3751-1
  • Electronic_ISBN
    1530-2075
  • Type

    conf

  • DOI
    10.1109/IPDPS.2009.5161223
  • Filename
    5161223