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New systolic array processor architecture for simultaneous discrete convolution of an image plane with multiple filter coefficient sets

机译:新的脉动阵列处理器架构,用于具有多个滤波器系数集的图像平面的同时离散卷积

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摘要

A new high-performance scalable systolic array processor architecture module for implementation of the two-dimensional discrete convolution algorithm on an (ixj) pixel input image plane (IP) using an (nxn) filter coefficient (FC) plane is first presented. The module generates one convoluted output image (OI) plane pixel per system clock cycle for an (n x n) FC plane using a level of r hardware resources. Second, the architecture is extended in a modular scalable manner to allow simultaneous convolution of a single IP, with k different (nxn) FC planes, such that k convoluted OI plane pixels are generated each system clock cycle, utilizing less than (k~*r) hardware resources. The new convolution architecture may be implemented to an ASIC or programmable logic device (PLD) platform. Results of synthesizing and implementing the proposed architecture are shown, illustrating the scalability of the new convolution architecture relative to k. Results from postimplementa-tion virtual hardware prototype simulation testing and from testing a PLD-based experimental hardware prototype are shown that validate correct functional and performance operation of the new convolution architecture module.
机译:首先介绍了一种新的高性能可伸缩脉动阵列处理器架构模块,该模块可使用(nxn)滤波系数(FC)平面在(ixj)像素输入图像平面(IP)上实施二维离散卷积算法。该模块使用r级硬件资源在一个(n x n)FC平面的每个系统时钟周期生成一个卷积的输出图像(OI)平面像素。其次,以模块化可扩展方式扩展该体系结构,以允许单个IP与k个不同的(nxn)FC平面同时卷积,从而在每个系统时钟周期生成k个卷积的OI平面像素,而使用的卷积小于(k〜* r)硬件资源。新的卷积体系结构可以实现到ASIC或可编程逻辑设备(PLD)平台。显示了综合和实施所提出的体系结构的结果,说明了新卷积体系相对于k的可扩展性。实施后的虚拟硬件原型仿真测试和基于PLD的实验硬件原型的测试结果表明,该结果验证了新卷积体系结构模块的正确功能和性能操作。

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