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The computational infrastructure of analogic CNN computing. I. The CNN-UM chip prototyping system

机译:模拟CNN计算的计算基础结构。 I. CNN-UM芯片原型系统

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A new computational paradigm is emerging for spatio-temporal problems: analogic cellular neuralonlinear network (CNN) array-computing. It has all the software and hardware ingredients of the stored programmable computer (highlevel language, compiler, operating system, assembly and machine code, analogic central processing unit (CPU), analog and digital memory, peripherals, etc.). The elementary instructions and programming techniques, however, are drastically different from any other computers. These elementary instructions represent complex spatio-temporal nonlinear dynamic phenomena, including all the standard and exotic properties of simple image processing operators, as well as waves, patterns, and evolving systems. Meanwhile, a computational infrastructure has also emerged interfacing this revolutionary computing technology to digital systems as well as enabling the development of high-level software. The main goal was to provide easy-to-use tools and hardware interfacing elements and putting most of the sophistication in the chips and chip sets.
机译:针对时空问题的一种新的计算范式正在出现:类比细胞神经网络/非线性网络(CNN)阵列计算。它具有存储的可编程计算机的所有软件和硬件组件(高级语言,编译器,操作系统,汇编和机器代码,模拟中央处理器(CPU),模拟和数字存储器,外围设备等)。但是,基本指令和编程技术与任何其他计算机都大不相同。这些基本指令表示复杂的时空非​​线性动力学现象,包括简单图像处理算子的所有标准特性和奇异特性,以及波动,图案和演化系统。同时,一种计算基础设施也应运而生,将这种革命性的计算技术与数字系统连接起来,并可以开发高级软件。其主要目的是提供易于使用的工具和硬件接口元件,并将大多数复杂性放入芯片和芯片组中。

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