论文标题
IBM神经计算机架构的概述
Overview of the IBM Neural Computer Architecture
论文作者
论文摘要
IBM神经计算机（INC）是一种高度灵活的，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Xilinx的现场可编程门阵列（FPGA）技术。节点在可扩展的3D网格拓扑中互连。我们概述了Inc，强调了独特的功能，例如在执行的计算类型和可用通信模式中的灵活性和可伸缩性，从而实现了新的机器智能方法和学习策略，并且不太适合矩阵操作/simd库，该库已优化了GPU。本文描述了机器的体系结构，应用程序将在其他地方进行详细描述。
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.
