基于opencl的低功耗遥感应用并行编程案例研究

2015 12th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE) Pub Date : 2015-12-17 DOI:10.1109/ICEEE.2015.7357959

A. C. Angulo, R. Carrasco-Alvarez, Jaime Ortegón-Aguilar, J. V. Castillo, O. Marrufo, A. Atoche

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引用次数: 1

摘要

随着高性能嵌入式计算(HPEC)系统的出现，许多数字处理算法现在都是由专用的大规模并行处理器实现的。本文采用基于opencl的并行编程实现了一种低功耗ARM/GPU协同设计架构，以实现复杂的重构信号处理操作。这些操作使用GPU和ARM处理器上的数据并行功能加速，在硬件/软件协同设计方案中通过OpenCL API调用。实验结果表明，与传统的并行嵌入式版本相比，该框架具有较高的计算性能和有效性。

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A case study of OpenCL-based parallel programming for low-power remote sensing applications

With the advent of high-performance embedded computing (HPEC) systems, many digital processing algorithms are now implemented by special-purpose massively parallel processors. In this paper, a low-power ARM/GPU co-design architecture is addressed using OpenCL-based parallel programming for implementing complex reconstructive signal processing operations. Such operations are accelerated using data-parallel functions on the GPU and ARM processor, in a HW/SW co-design scheme via OpenCL API calls. Experimental results shows the achieved computational performance and the effectiveness of the OpenCL standard comparing the framework against traditional parallel embedded versions.

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2015 12th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE)

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