Performance optimization on low-cost cellular array processors

A. Broggi
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引用次数: 11

Abstract

A massively parallel architecture is composed of a high number of processing elements (PE), but seldom a 1:1 mapping between the PEs and the data set can be achieved. To overcome this problem, a processor virtualization mechanism is needed. This work provides a theoretical study on performance optimization in the specific virtualization process used when a small amount of memory is associated to each PE. Moreover, this paper presents an algorithm for performance optimization and for the determination of the maximum processing speed on low-cost cellular array processors implementing the above mentioned visualization mechanism. These considerations are then used to improve the execution of morphological image processing tasks on the first hardware prototype of the special-purpose cellular array processor PAPRICA.<>
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低成本蜂窝阵列处理器的性能优化
大规模并行架构由大量处理元素(PE)组成,但PE和数据集之间很少能实现1:1的映射。为了克服这个问题,需要一个处理器虚拟化机制。这项工作提供了一个关于特定虚拟化进程的性能优化的理论研究,当少量内存与每个PE相关联时。此外,本文还提出了一种在低成本蜂窝阵列处理器上实现上述可视化机制的性能优化和最大处理速度确定算法。然后将这些考虑因素用于改进专用细胞阵列处理器PAPRICA. b>的第一个硬件原型上形态学图像处理任务的执行
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