Research on General-Purpose Brain-Inspired Computing Systems

IF 1.2 3区 计算机科学 Q4 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE Journal of Computer Science and Technology Pub Date : 2024-01-30 DOI:10.1007/s11390-023-4002-3
Peng Qu, Xing-Long Ji, Jia-Jie Chen, Meng Pang, Yu-Chen Li, Xiao-Yi Liu, You-Hui Zhang
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Abstract

Brain-inspired computing is a new technology that draws on the principles of brain science and is oriented to the efficient development of artificial general intelligence (AGI), and a brain-inspired computing system is a hierarchical system composed of neuromorphic chips, basic software and hardware, and algorithms/applications that embody this technology. While the system is developing rapidly, it faces various challenges and opportunities brought by interdisciplinary research, including the issue of software and hardware fragmentation. This paper analyzes the status quo of brain-inspired computing systems. Enlightened by some design principle and methodology of general-purpose computers, it is proposed to construct “general-purpose” brain-inspired computing systems. A general-purpose brain-inspired computing system refers to a brain-inspired computing hierarchy constructed based on the design philosophy of decoupling software and hardware, which can flexibly support various brain-inspired computing applications and neuromorphic chips with different architectures. Further, this paper introduces our recent work in these aspects, including the ANN (artificial neural network)/SNN (spiking neural network) development tools, the hardware agnostic compilation infrastructure, and the chip micro-architecture with high flexibility of programming and high performance; these studies show that the “general-purpose” system can remarkably improve the efficiency of application development and enhance the productivity of basic software, thereby being conductive to accelerating the advancement of various brain-inspired algorithms and applications. We believe that this is the key to the collaborative research and development, and the evolution of applications, basic software and chips in this field, and conducive to building a favorable software/hardware ecosystem of brain-inspired computing.

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通用脑启发计算系统研究
脑启发计算是一种借鉴脑科学原理、面向人工通用智能(AGI)高效发展的新技术,脑启发计算系统是由神经形态芯片、基础软硬件和体现该技术的算法/应用组成的分层系统。该系统在快速发展的同时,也面临着跨学科研究带来的各种挑战和机遇,其中就包括软硬件碎片化问题。本文分析了脑启发计算系统的现状。在通用计算机一些设计原理和方法的启发下,提出构建 "通用型 "脑启发计算系统。通用脑启发计算系统是指基于软硬件解耦设计理念构建的脑启发计算层次结构,可以灵活支持各种脑启发计算应用和不同架构的神经形态芯片。此外,本文还介绍了我们最近在这些方面的工作,包括 ANN(人工神经网络)/SNN(尖峰神经网络)开发工具、硬件无关的编译基础架构,以及具有高编程灵活性和高性能的芯片微体系结构;这些研究表明,"通用 "系统可以显著提高应用开发的效率,提高基础软件的生产力,从而有利于加速各种脑启发算法和应用的发展。我们相信,这是该领域应用、基础软件和芯片协同研发和演进的关键,有利于构建良好的脑启发计算软硬件生态系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Computer Science and Technology
Journal of Computer Science and Technology 工程技术-计算机:软件工程
CiteScore
4.00
自引率
0.00%
发文量
2255
审稿时长
9.8 months
期刊介绍: Journal of Computer Science and Technology (JCST), the first English language journal in the computer field published in China, is an international forum for scientists and engineers involved in all aspects of computer science and technology to publish high quality and refereed papers. Papers reporting original research and innovative applications from all parts of the world are welcome. Papers for publication in the journal are selected through rigorous peer review, to ensure originality, timeliness, relevance, and readability. While the journal emphasizes the publication of previously unpublished materials, selected conference papers with exceptional merit that require wider exposure are, at the discretion of the editors, also published, provided they meet the journal''s peer review standards. The journal also seeks clearly written survey and review articles from experts in the field, to promote insightful understanding of the state-of-the-art and technology trends. Topics covered by Journal of Computer Science and Technology include but are not limited to: -Computer Architecture and Systems -Artificial Intelligence and Pattern Recognition -Computer Networks and Distributed Computing -Computer Graphics and Multimedia -Software Systems -Data Management and Data Mining -Theory and Algorithms -Emerging Areas
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