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Finding Space-Time Stream Permutations for Minimum Memory and Latency

机译:寻找时空流排列以最小化内存和延迟

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Processing of parallel data streams requires permutation units for many algorithms where the streams are not independent. Such algorithms include transforms, multi-rate signal processing, and Viterbi decoding. The absolute order of data elements from the permutation is not important, only that data elements are located correctly for the next processing step. This paper describes a method to find permutations that require a minimum amount of memory and latency. The required permutations are generated based on the data dependencies of a computation set. Additional constraints are imposed so that the parallel streaming architecture processes the data without flow control. Results show agreement with brute force methods, which become computationally infeasible for large permutation sets.
机译:并行数据流的处理要求流不独立的许多算法的置换单元。这样的算法包括变换,多速率信号处理和维特比解码。排列中的数据元素的绝对顺序并不重要,只有为下一个处理步骤正确定位数据元素。本文介绍了一种查找需要最少内存和等待时间的排列的方法。基于计算集的数据依赖性生成所需的排列。施加了附加的约束,以便并行流体系结构可以在没有流控制的情况下处理数据。结果表明与蛮力方法一致,蛮力方法在计算上不适用于大型排列集。

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