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引用次数: 2
摘要
介绍了一种用于图像处理的大规模并行体系结构的硅编译器设计方法。它从与GAPP NCR语言(GAL)相当的语言中的应用程序的算法描述开始,并生成一个优化电路,该电路组织为1-b处理元件的二维阵列,资源最少。通过两个算例说明了该方法的有效性。第一个是专用集成电路(ASIC),用于两种基本的数学形态学操作,膨胀和侵蚀。第二个是用于卷积的ASIC。两者都在双铝2 μ m CMOS标准电池中实现。在这两种情况下,处理器元素都是非常有效的。节省了相当大的面积。
A silicon compiler for massively parallel image processing ASICs
A silicon compiler design methodology for massively parallel architecture for image processing is introduced. It starts from an algorithmic description of the application in a language comparable to the GAPP NCR language (GAL) and generates an optimized circuit organized as a 2-D array of 1-b processing elements with minimized resources. The effectiveness of the approach is shown by two examples. The first is an ASIC (application-specific integrated circuit) for two basic mathematical morphology operations, dilation and erosion. The second is an ASIC for convolution. Both have been implemented in a double-aluminium 2- mu m CMOS standard cell. In both cases the processor element has been found to be very effective. Considerable area savings have been achieved.<>