以内存为中心的VDF图形转换的实际FPGA实现

Matthew Milford, J. McAllister
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引用次数: 1

摘要

在FPGA上实现图像和视频处理等内存密集型应用需要创建复杂的多级内存层次结构以实现实时性能;然而,商业高级综合工具无法自动导出这样的结构,因此无法满足这些应用对带宽和容量的要求。目前解决这个问题的方法要么只能得到单级内存结构,要么只能得到非常深的、效率极低的层次结构,这两种情况都会导致一个或多个高实现成本和低性能。本文对现有的MC-HLS合成方法进行了改进,解决了这一问题;它利用并消除了生成的层次结构的多个级别上的数据重复,从而减少了级别的数量,最终实现了更高的性能和更低的成本。当应用于基于c的运动估计,矩阵乘法和Sobel边缘检测应用的合成时,这可以减少块RAM和查找表(LUT)成本高达25%,同时提高吞吐量。
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Memory-centric VDF graph transformations for practical FPGA implementation
Realising memory intensive applications such as image and video processing on FPGA requires creation of complex, multi-level memory hierarchies to achieve real-time performance; however commerical High Level Synthesis tools are unable to automatically derive such structures and hence are unable to meet the demanding bandwidth and capacity constraints of these applications. Current approaches to solving this problem can only derive either single-level memory structures or very deep, highly inefficient hierarchies, leading in either case to one or more of high implementation cost and low performance. This paper presents an enhancement to an existing MC-HLS synthesis approach which solves this problem; it exploits and eliminates data duplication at multiple levels levels of the generated hierarchy, leading to a reduction in the number of levels and ultimately higher performance, lower cost implementations. When applied to synthesis of C-based Motion Estimation, Matrix Multiplication and Sobel Edge Detection applications, this enables reductions in Block RAM and Look Up Table (LUT) cost of up to 25%, whilst simultaneously increasing throughput.
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