Cognitive computing programming paradigm: A Corelet Language for composing networks of neurosynaptic cores

A. Amir, Pallab Datta, W. Risk, A. Cassidy, J. Kusnitz, Steven K. Esser, Alexander Andreopoulos, T. Wong, M. Flickner, Rodrigo Alvarez-Icaza, E. McQuinn, Ben Shaw, Norm Pass, D. Modha
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引用次数: 162

Abstract

Marching along the DARPA SyNAPSE roadmap, IBM unveils a trilogy of innovations towards the TrueNorth cognitive computing system inspired by the brain's function and efficiency. The sequential programming paradigm of the von Neumann architecture is wholly unsuited for TrueNorth. Therefore, as our main contribution, we develop a new programming paradigm that permits construction of complex cognitive algorithms and applications while being efficient for TrueNorth and effective for programmer productivity. The programming paradigm consists of (a) an abstraction for a TrueNorth program, named Corelet, for representing a network of neurosynaptic cores that encapsulates all details except external inputs and outputs; (b) an object-oriented Corelet Language for creating, composing, and decomposing corelets; (c) a Corelet Library that acts as an ever-growing repository of reusable corelets from which programmers compose new corelets; and (d) an end-to-end Corelet Laboratory that is a programming environment which integrates with the TrueNorth architectural simulator, Compass, to support all aspects of the programming cycle from design, through development, debugging, and up to deployment. The new paradigm seamlessly scales from a handful of synapses and neurons to networks of neurosynaptic cores of progressively increasing size and complexity. The utility of the new programming paradigm is underscored by the fact that we have designed and implemented more than 100 algorithms as corelets for TrueNorth in a very short time span.
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认知计算程序设计范例:一种构成神经突触核心网络的核心语言
在DARPA SyNAPSE路线图的指引下,IBM公布了TrueNorth认知计算系统的创新三部曲,其灵感来自于大脑的功能和效率。冯·诺伊曼架构的顺序编程范式完全不适合TrueNorth。因此,作为我们的主要贡献,我们开发了一种新的编程范式,允许构建复杂的认知算法和应用程序,同时对TrueNorth有效,对程序员的生产力有效。编程范例包括(a)一个名为Corelet的TrueNorth程序的抽象,用于表示一个神经突触核心网络,该网络封装了除外部输入和输出外的所有细节;(b)面向对象的Corelet语言,用于创建、组合和分解Corelet;(c)一个Corelet库,作为一个不断增长的可重用Corelet库,程序员可以从中组成新的Corelet;(d)端到端内核实验室,这是一个与TrueNorth架构模拟器Compass集成的编程环境,以支持从设计、开发、调试到部署的编程周期的各个方面。这个新范式无缝地从少数突触和神经元扩展到逐渐增加大小和复杂性的神经突触核心网络。我们已经在很短的时间内为TrueNorth设计并实现了100多个算法,这一事实强调了新编程范式的实用性。
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