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Parallel algorithms for Burrows-Wheeler compression and decompression

机译:Burrows-Wheeler压缩和解压缩的并行算法

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摘要

We present work-optimal PRAM algorithms for Burrows-Wheeler compression and decompression of strings over a constant alphabet. For a string of length n, the depth of the compression algorithm is O(log~2n), and the depth of the corresponding decompression algorithm is O(logn). These appear to be the first polylogarithmic-time work-optimal parallel algorithms for any standard lossless compression scheme. The algorithms for the individual stages of compression and decompression may also be of independent interest: (1) a novel O(log n)-time, O(n)-work PRAM algorithm for Huffman decoding; (2) original insights into the stages of the BW compression and decompression problems, bringing out parallelism that was not readily apparent, allowing them to be mapped to elementary parallel routines that have O(log n)-time, O(n)-work solutions, such as: (i) prefix-sums problems with an appropriately-defined associative binary operator for several stages, and (ii) list ranking for the final stage of decompression. Follow-up empirical work suggests potential for considerable practical speedups on a PRAM-driven many-core architecture, against a backdrop of negative contemporary results on common commercial platforms.
机译:我们提出用于Burrows-Wheeler压缩和解压缩恒定字母字符串的最优工作PRAM算法。对于长度为n的字符串,压缩算法的深度为O(log〜2n),相应的解压缩算法的深度为O(logn)。对于任何标准无损压缩方案,这些似乎是第一个对数时间工作最优并行算法。用于压缩和解压缩的各个阶段的算法也可能具有独立的意义:(1)一种用于霍夫曼解码的新颖的O(log n)时间,O(n)工作PRAM算法; (2)对BW压缩和解压缩问题各阶段的独到见解,带来了尚不明显的并行性,允许将它们映射到具有O(log n)-时间,O(n)-功的基本并行例程解决方案,例如:(i)在几个阶段使用适当定义的关联二进制运算符对问题求和,以及(ii)减压的最后阶段列出排名。后续的经验工作表明,在常见的商用平台上,当代的负面结果背景下,在PRAM驱动的多核架构上,可能有相当大的实际提速。

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