Heterogeneous Platform to Accelerate Compute Intensive Applications
Santhosh Kumar Rethinagiri, Oscar Palomar, Javier Moreno, Osman Ünsal, Adrián Cristal · 2015
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.