With endless amounts of data and very limited bandwidth, fast data compression is one solution for the growing datasharing problem. Compression helps lower transfer times and save memory, but if the compression takes too long, this no longer seems viable. Multi-core processors enable parallel data compression; however, parallelizing the algorithms is anything but straightforward since compression is inherently serial. This paper explores techniques to parallelize three compression schemes: Huffman coding, LZSS, and MP3 coding

翻译：随着数据量无限增长而带宽极其有限，快速数据压缩成为解决日益严峻的数据共享问题的一种方案。压缩有助于降低传输时间并节省内存，但如果压缩过程耗时过长，这一方案便不再可行。多核处理器支持并行数据压缩；然而，压缩本质上具有串行性，因此算法的并行化绝非易事。本文探讨了三种压缩方案的并行化技术：霍夫曼编码、LZSS编码和MP3编码。