CULZSS-Bit:一种gpgpu上无损数据压缩的位矢量算法

Adnan Ozsoy
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引用次数: 8

摘要

本文提出了一种改进gpgpu上基于字典的无损数据压缩算法。该算法采用逐位计算,并利用位并行性作为算法的核心部分,即最长的前缀匹配计算。使用位并行,也被称为位矢量方法,是一种全新的数据压缩方法,在混合CPU-GPU环境中具有良好的性能。新的压缩算法在gpu上的实现与之前的尝试相比,提高了压缩过程的性能。此外,位向量方法为改进提供了新的机会,并增加了流行的异构环境的适用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
CULZSS-Bit: A Bit-Vector Algorithm for Lossless Data Compression on GPGPUs
In this paper, we describe an algorithm to improve dictionary based lossless data compression on GPGPUs. The presented algorithm uses bit-wise computations and leverages bit parallelism for the core part of the algorithm which is the longest prefix match calculations. Using bit parallelism, also known as bit-vector approach, is a fundamentally new approach for data compression and promising in performance for hybrid CPU-GPU environments.The implementation of the new compression algorithm on GPUs improves the performance of the compression process compared to the previous attempts. Moreover, the bit-vector approach opens new opportunities for improvement and increases the applicability of popular heterogeneous environments.
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