SIMD多处理器系统的并行矢量量化算法

H.J. Lee, J.C. Liu, A. Chan, C. Chui
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引用次数: 8

摘要

仅给出摘要形式,如下。本文提出了一种并行矢量量化(VQ)算法,用于单指令多数据(SIMD)多处理器上的码本穷举搜索。提出的并行VQ算法可以与并行小波变换技术相结合,实现图像的快速压缩。该算法已在MasPar并行计算机上实现,取得了良好的性能提升。我们的研究结果表明,VQ可以在商用SIMD机器上有效地并行化,以满足许多应用程序的实时性能要求。请注意,尽管MP-1机器中的处理器基于相对较旧的VLSI技术,但通过并行化计算获得的巨大加速是明显的。由于我们的算法适用于任何大小的图像,因此它可以很容易地用于更大、更快的SIMD多处理器系统,以实时处理非常大的图像。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A parallel vector quantization algorithm for SIMD multiprocessor systems
Summary form only given , as follows. This article proposes a parallel vector quantization (VQ) algorithm for an exhaustive search of codebooks on a single-instruction-multiple-data (SIMD) multiprocessor. The proposed parallel VQ algorithm can be integrated with the parallel wavelet-transform techniques for fast image compression. This algorithm has been implemented on the MasPar parallel computer to achieve favorable performance gains. Our results show that VQ can be efficiently parallelized on commercial SIMD machines to meet the real-time performance requirements of numerous applications. Note that although processors in the MP-1 machine are based on relatively old VLSI technology, the drastic speedup gained by parallelization of the computations is marked. Since our algorithm is applicable to any image size, it can be readily used on larger, faster SIMD multiprocessor systems for real-time processing of very large images.
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