The IBM Neural Computer (INC) is a highly flexible, re-configurable parallel processing system that is intended as a research and development platform for emerging machine intelligence algorithms and computational neuroscience. It consists of hundreds of programmable nodes, primarily based on Xilinx's Field Programmable Gate Array (FPGA) technology. The nodes are interconnected in a scalable 3d mesh topology. We overview INC, emphasizing unique features such as flexibility and scalability both in the types of computations performed and in the available modes of communication, enabling new machine intelligence approaches and learning strategies not well suited to the matrix manipulation/SIMD libraries that GPUs are optimized for. This paper describes the architecture of the machine and applications are to be described in detail elsewhere.

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IBM 神经计算机架构概述

IBM 神经计算机 (INC) 是一种高度灵活、可重新配置的并行处理系统，旨在作为新兴机器智能算法和计算神经科学的研发平台。它由数百个可编程节点组成，主要基于赛灵思的现场可编程门阵列 (FPGA) 技术。节点以可扩展的 3d 网格拓扑互连。我们概述了 INC，强调在执行的计算类型和可用通信模式方面的独特功能，例如灵活性和可扩展性，启用新的机器智能方法和学习策略，这些方法和学习策略不太适合 GPU 优化的矩阵操作/SIMD 库. 本文描述了机器的架构，应用程序将在别处详细描述。