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Optimal implementations of the approximate string matching and the approximate discrete signal matching on the memory machine models

机译:内存机器模型上近似字符串匹配和近似离散信号匹配的最佳实现

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The discrete memory machine (DMM) and the unified memory machine (UMM) are theoretical parallel computing models that capture the essence of the shared memory access and the global memory access of graphics processing units. The approximate string matching (ASM) for two strings X and Y is a task to find a substring of Y most similar to X. The main contribution of this paper is to show efficient implementations of ASM on the memory machine models. Our best implementation for strings X and Y with length m and n(m ≤ n), respectively, runs in 0((mn/w) + ml) time units using n threads both on the DMM and on the UMM with width w and latency l. We also show that any implementation of the ASM on the DMM and the UMM needs O((mn/w) + ml) time units. Thus, our implementations for the DMM and the UMM are optimal. Finally, we show that the approximate discrete signal matching of two signals can be computed in the same time complexity.
机译:离散存储机(DMM)和统一存储机(UMM)是理论并行计算模型,它们捕获图形处理单元的共享内存访问和全局内存访问的本质。两个字符串X和Y的近似字符串匹配(ASM)是查找与X最相似的Y子字符串的任务。本文的主要贡献是,展示了ASM在内存机器模型上的有效实现。对于长度分别为m和n(m≤n)的字符串X和Y,我们的最佳实现分别在DMM和UMM上使用n个线程以0((mn / w)+ ml)时间单位在宽度为w和潜伏期我们还表明,在DMM和UMM上对ASM的任何实现都需要O((mn / w)+ ml)时间单位。因此,我们对DMM和UMM的实现是最佳的。最后,我们表明可以在相同的时间复杂度下计算两个信号的近似离散信号匹配。

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