优化了OpenCL-GPU和OpenCL-CPU上的快速Walsh-Hadamard变换

Pedro M. M. Pereira, Patrício Domingues, Nuno M. M. Rodrigues, S. Faria, G. Falcão
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引用次数: 2

摘要

Walsh-Hadamard变换在许多图像和视频编码算法中起着重要的作用。一方面,它在这些算法中的大量使用使其加速成为一项挑战,以加快算法的执行速度。另一方面,可用的快速实现在不同平台上效率不高。在这项工作中,提出了一种基于OpenCL标准的CPU和GPU平台的并行实现WHT。OpenCL在代码级别实现了可移植性,但是当相同的代码用于cpu和gpu时,其性能会受到影响。为了达到最佳性能,我们提出了两个WHT版本:面向gpu的OpenCL-GPU和面向cpu的OpenCL-CPU。总的来说,在GPU上执行的OpenCL-GPU比在多核CPU上执行的OpenCL-CPU运行得快,速度从120.87到1016.35不等。然而,当在多核CPU机器上运行时,OpenCL- gpu的性能会大幅下降,因为它利用了OpenCL对SIMD指令的支持,因此OpenCL-CPU的性能更高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimized fast Walsh-Hadamard transform on OpenCL-GPU and OpenCL-CPU
The Walsh-Hadamard transform plays a major role in many image and video coding algorithms. In one hand, its intensive use in these algorithms makes its acceleration a challenge, in order to speed-up the algorithm execution. On the other hand, the available fast implementations are not efficient across different platforms. In this work, a parallel-based implementation of the WHT is proposed for CPU and GPU platforms using the OpenCL standard. OpenCL achieves portability at code level, but its performance suffers when the same code is used for CPUs and GPUs. To achieve top performance, we propose two WHT versions: OpenCL-GPU for GPUs and OpenCL-CPU for CPUs. Broadly, OpenCL-GPU executed on a GPU runs faster than OpenCL-CPU executed on a multicore CPU, with speedups that range from 120.87 to 1016.35. However, OpenCL-GPU performance drops substantially when ran on a multicore CPU machine, where OpenCL-CPU achieves higher performance, as it exploits the OpenCL support for SIMD instructions.
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