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
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