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Signal Assignment to Hierarchical Memory Organizations for Embedded Multidimensional Signal Processing Systems

机译:嵌入式多维信号处理系统的信号分配给分层存储组织

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The storage requirements of the array-dominated and loop-organized algorithmic specifications running on embedded systems can be significant. Employing a data memory space much larger than needed has negative consequences on the energy consumption, latency, and chip area. Finding an optimized storage of the usually large arrays from these algorithmic specifications is an essential task of memory allocation. This paper proposes an efficient algorithm for mapping multidimensional arrays to the data memory. Similarly to , it computes bounding windows for live elements in the index space of arrays, but this algorithm is several times faster. More important, since this algorithm works not only for entire arrays, but also parts of arrays—like, for instance, array references or, more general, sets of array elements represented by lattices , this signal-to-memory mapping technique can be also applied in hierarchical memory architectures.
机译:在嵌入式系统上运行的,以阵列为主和以循环组织的算法规范的存储要求可能很高。使用比所需大得多的数据存储空间会对能耗,延迟和芯片面积产生负面影响。从这些算法规范中找到通常大型阵列的优化存储是内存分配的一项基本任务。本文提出了一种将多维数组映射到数据存储器的有效算法。与相似,它为数组的索引空间中的活动元素计算边界窗口,但是此算法要快几倍。更重要的是,由于此算法不仅适用于整个数组,而且适用于数组的某些部分(例如,数组引用,或更一般地,由点阵表示的数组元素集),因此这种信号到内存的映射技术也可以是应用于分层内存架构。

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