• DocumentCode
    3181770
  • Title

    Heterogeneous Platform to Accelerate Compute Intensive Applications

  • Author

    Kumar Rethinagiri, Santhosh ; Palomar, Oscar ; Arias Moreno, Javier ; Unsal, Osman ; Cristal, Adrian

  • Author_Institution
    BSC-Microsoft Res. Center, Barcelona, Spain
  • fYear
    2015
  • fDate
    2-6 May 2015
  • Firstpage
    31
  • Lastpage
    31
  • Abstract
    Nowadays image processing applications are widely used in various industries such as traffic, safety, medical engineering, etc. In this paper, we propose a power and energy efficient heterogeneous platform to accelerate image processing applications. To achieve this efficiency, we propose a novel hybrid platform which consists of a Xilinx Zynq (ARM+FPGA) and an NVidias Jetson TK1 (ARM+GPU) coupled with PCIe card. In applications such face recognition, we optimized major tasks in detection and recognition in order to achieve a speedup of 69× when compared to sequential execution on the ARM core, 4.8× against Zynq platform (ARM+FPGA), 3.2× against NVidia platform (ARM+GPU) and 40% more energy efficient against sequential execution.
  • Keywords
    face recognition; field programmable gate arrays; graphics processing units; microcontrollers; peripheral interfaces; ARM+FPGA; ARM+GPU; NVidia platform; NVidias Jetson TK1; PCIe card; Xilinx Zynq platform; energy efficient heterogeneous platform; face recognition; image processing; power efficient heterogeneous platform; Acceleration; Face recognition; Field programmable gate arrays; Graphics processing units; Image processing; Performance evaluation; Prototypes; FPGA; GPU; Heterogeneous platform; Image processing; PCIe;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Field-Programmable Custom Computing Machines (FCCM), 2015 IEEE 23rd Annual International Symposium on
  • Conference_Location
    Vancouver, BC
  • Type

    conf

  • DOI
    10.1109/FCCM.2015.62
  • Filename
    7160032