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Split and shift methodology on cellular processor arrays: area saving versus time penalty

机译:蜂窝处理器阵列上的拆分和移位方法:面积节省与时间损失

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This paper addresses the so-called split and shift methodology. This methodology deals with the implementation of kernels of sizes that go above the physically implemented resources (local connections and weighting circuits) on synchronous cellular processor arrays (CPA), including the realization of large neighborhood operations and/or the reduction of the available hardware in order to drop the area consumption. Two main goals are pursued in the development of the methodology, namely: (1) minimum penalty at processing time and (2) absolutely no penalty at functional level. The paper presents different techniques and guidelines for the methodology application and introduces a Figure of Merit to evaluate them by relating area gains with time penalty. This, along with a kernel shape analysis, led us to propose more adequate configurations of weighting circuits and to justify the classical choice of North-East-West-South connectivity. To validate the methodology, we realize several estimates over actual physical implementations, and we propose the realization over CPAs of the spin filters, scale invariant feature transform and speeded-up robust features algorithms. A more in-depth trade-off analysis is realized over the implementation of the pixel level snakes algorithm.
机译:本文讨论了所谓的拆分和转移方法。该方法论处理的大小超过同步蜂窝处理器阵列(CPA)上物理实现的资源(本地连接和加权电路)的内核的实现,包括实现大型邻域操作和/或减少可用硬件的数量。为了减少面积消耗。在该方法的开发中追求两个主要目标,即:(1)处理时的最小损失;(2)在功能级别上绝对没有损失。本文介绍了用于方法学的不同技术和指南,并介绍了一项功绩指标,以通过将面积增益与时间损失相关联来进行评估。这与内核形状分析一起,使我们提出了更合适的加权电路配置,并证明了东北-西-南连通性的经典选择。为了验证该方法,我们对实际的物理实现进行了一些估计,并提出了自旋滤波器,尺度不变特征变换和加速鲁棒特征算法在CPA上的实现。在像素级蛇形算法的实现上实现了更深入的权衡分析。

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