首页|Research on General-Purpose Brain-Inspired Computing Systems

Research on General-Purpose Brain-Inspired Computing Systems

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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 tech-nology.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 architec-tures.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-archi-tecture 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.

brain-inspired computingneuromorphic chipcompilerspiking neural network

渠鹏、纪兴龙、陈嘉杰、庞猛、李宇晨、刘晓义、张悠慧

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Department of Computer Science and Technology,Tsinghua University,Beijing 100084,China

Department of Precision Instrument,Tsinghua University,Beijing 100084,China

国家自然科学基金国家自然科学基金国家自然科学基金国家自然科学基金青年基金Beijing National Research Center for Information Science and TechnologyTsinghua University Initiative Scientific Research ProgramSuzhou-Tsinghua Innovation Leadership Program

62250006620722666183600462202254BNR2022RC01003

2024

计算机科学技术学报(英文版)
中国计算机学会

计算机科学技术学报(英文版)

CSTPCD
影响因子:0.432
ISSN:1000-9000
年,卷(期):2024.39(1)
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