Parallel processing architectures for rank order and stack filters
Parallel processing architectures for rank order and stack filters
复制标题
排序和堆栈过滤器的并行处理架构
DOI：
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发表时间：
1993
期刊：
影响因子：
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通讯作者：
K. Parhi
中科院分区：
文献类型：
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作者：
L. Lucke;K. Parhi
为了在等级顺序和堆栈滤波器架构中实现额外的加速，需要使用并行处理技术，例如流水线和块处理。流水线很好地理解，但很少有块架构已开发的秩顺序和堆栈过滤。当体系结构达到底层技术造成的吞吐量限制时，块处理是必不可少的。平凡块结构重复单输入、单输出结构以生成多输入、多输出结构，并且可以实现等于块大小（或多个输出的数量）的加速比。与线性滤波器不同，秩序和堆栈滤波器输出是使用比较计算的。可以在块结构内共享这些比较。作者介绍了一种系统的方法，适用于块处理的秩顺序和堆栈过滤器。该方法利用块结构内的共享比较来生成具有共享子结构的块滤波器，其复杂度降低。此外，块处理对于低功耗设计的生成是重要的。简单的块结构产生低功耗设计，达到一定的限制。作者演示了如何使用共享子结构的块结构来生成具有任意低功耗的设计。<<ETX>>
To achieve additional speedup in rank order and stack filter architectures requires the use of parallel processing techniques such as pipelining and block processing. Pipelining is well understood but few block architectures have been developed for rank order and stack filtering. Block processing is essential when the architecture reaches the throughput limits caused by the underlying technology. A trivial block structure repeats a single input, single output structure to generate a multiple input, multiple output structure and can achieve speedups equal to the block size (or the number of multiple outputs). Unlike linear filters, the rank order and stack filter outputs are calculated using comparisons. It is possible to share these comparisons within the block structure. The authors introduce a systematic method for applying block processing to the rank order and stack filters. This method takes advantage of shared comparisons within the block structure to generate a block filter with shared substructures whose complexity is reduced. Furthermore, block processing is important for the generation of low power designs. Trivial block structures generate low power designs up to a certain limit. The authors demonstrate how block structures with shared substructures are used to generate designs with arbitrarily low power.<<ETX>>