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Image-processing system based on homogeneous computing and storage structures

机译:基于同类计算和存储结构的图像处理系统

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Abstract: Nowadays various architectures are suggested for highly efficient image processing, including parallel processors of SIMD type, multiprocessor systems, pipelined processors, systolic arrays and pyramid machines. However, a maximal speed of algorithm execution can be reached only by specialized processor implemented on a custom chip. So merging of the properties of a specialized processor and a possibility of reprogramming in one approach should give a satisfactory result. The paper suggests a new approach to the developing of architecture of a high-speed parallel system for low-level image processing. The homogeneous computing structure (HCS) and homogeneous storing structure (HSS) are the basic elements of this approach. The high speed of the system is provided by structural method of organization of the computing process which is based on the hardware realization of all the nodes of the information graph and their interconnections. The size of the HCS matrix allows to use for each program instruction its own group of processor elements. The program is loaded once before starting to solve the problem, and the information streams processing is carried out without intermediate results storage. The data streams applied to the information inputs of the processor elements are processed in accordance with the program, moving from one element to another in the matrix of the HCS. The examples of execution of the image filtering algorithms on the system are presented.!12
机译:摘要:如今,已提出了用于高效图像处理的各种体系结构,包括SIMD类型的并行处理器,多处理器系统,流水线处理器,脉动阵列和金字塔机器。但是,只有在定制芯片上实现的专用处理器才能达到算法执行的最大速度。因此,采用一种方法合并专用处理器的属性和重新编程的可能性应该可以得出令人满意的结果。本文提出了一种新的方法,用于开发用于低级图像处理的高速并行系统的体系结构。同类计算结构(HCS)和同类存储结构(HSS)是此方法的基本元素。计算过程的组织结构方法基于信息图所有节点及其互连的硬件实现,从而提供了系统的高速性。 HCS矩阵的大小允许为每个程序指令使用其自己的一组处理器元素。在开始解决问题之前,将程序加载一次,并且在不存储中间结果的情况下执行信息流处理。应用于处理器元素信息输入的数据流根据程序进行处理,从HCS矩阵中的一个元素移动到另一个元素。给出了在系统上执行图像过滤算法的示例。!12

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