CUVLE: Variable-length encoding on CUDA
CUVLE: Variable-length encoding on CUDA
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CUVLE：CUDA 上的可变长度编码
DOI：
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发表时间：
2014
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通讯作者：
Nicolás Guil Mata
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作者：
Antonio Fuentes;Juan Gómez;José María González;Nicolás Guil Mata
数据压缩是以紧凑的形式表示信息的过程，以减少存储需求，从而减少通信带宽。几十年来，它一直是正在进行的数字多媒体革命的关键技术之一。在可变长度编码（VLE）压缩方法中，最频繁出现的符号被具有较短长度的代码替换。由于它是许多压缩应用中的常见策略，因此非常需要高效的并行实现VLE。在本文中，我们提出了CUVLE，在CUDA上的VLE的GPU实现。我们的方法平均比相应的CPU串行实现和唯一已知的最先进的GPU实现分别快20倍和2倍以上。
Data compression is the process of representing information in a compact form, in order to reduce the storage requirements and, hence, communication bandwidth. It has been one of the critical enabling technologies for the ongoing digital multimedia revolution for decades. In the variable-length encoding (VLE) compression method, most frequently occurring symbols are replaced by codes with shorter lengths. As it is a common strategy in many compression applications, efficient parallel implementations of VLE are very desirable. In this paper we present CUVLE, a GPU implementation of VLE on CUDA. Our approach is on average more than 20 and 2 times faster than the corresponding CPU serial implementation and the only known state-of-the-art GPU implementation, respectively.