XPS: DSD: Collaborative Research: NeoNexus: The Next-generation Information Processing System across Digital and Neuromorphic Computing Domains
XPS:DSD:协作研究:NeoNexus:跨数字和神经形态计算领域的下一代信息处理系统
基本信息
- 批准号:1744077
- 负责人:
- 金额:$ 18.9万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2017
- 资助国家:美国
- 起止时间:2017-05-01 至 2018-08-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
The explosion of "big data" applications imposes severe challenges of data processing speed and scalability on traditional computer systems. The performance of traditional Von Neumann machines is greatly hindered by the increasing performance gap between CPU and memory, motivating the active research on new or alternative computing architectures. By imitating brain's naturally massive parallel architecture with closely coupled memory and computing as well as the unique analog domain operations, neuromorphic computing systems are anticipated to deliver superior speed for applications in image recognition and natural language understanding.The objective of this research is to establish the fundamental framework and design methodology for NeoNexus -- the next-generation information processing system inspired by human neocortex. It integrates neuromorphic computing accelerators with conventional computing resources by leveraging large scale inference-based data processing and computing acceleration technique atop memristor crossbar arrays. The computation and data exchange will be carefully coordinated and supported by the innovative interconnect architecture, i.e., a hierarchical network-on-chip (NoC). The software-hardware co-design platform will be developed to address the various design challenges. The project will help computer architecture and high-performance computing communities to overcome the ever-increasing technical challenges of traditional architectures and accelerate the fusion between conventional computing technology and cognitive computing model. It will also promote the applications of artificial intelligence technology advances in modern computer architectures and motivate the inventions at both software and hardware levels. Undergraduate and graduate students involved in this research will be trained for the next-generation semiconductor industry workforce.
“大数据”应用的爆炸式增长对传统计算机系统的数据处理速度和可扩展性提出了严峻的挑战。传统的冯诺依曼机的性能受到CPU和存储器之间性能差距的极大阻碍,激发了对新的或替代的计算架构的积极研究。通过模仿大脑的自然大规模并行架构,紧密耦合的存储器和计算以及独特的模拟域操作,神经形态计算系统有望为图像识别和自然语言理解等应用提供上级速度。本研究的目的是建立NeoNexus的基本框架和设计方法。新一代信息处理系统的灵感来自于人类大脑皮层。它通过在忆阻器交叉阵列上利用基于大规模推理的数据处理和计算加速技术,将神经形态计算加速器与传统计算资源集成在一起。计算和数据交换将得到创新的互连架构的精心协调和支持,即,分层片上网络(NoC)。将开发软硬件协同设计平台,以应对各种设计挑战。该项目将帮助计算机体系结构和高性能计算社区克服传统体系结构日益增长的技术挑战,加速传统计算技术与认知计算模型之间的融合。它还将促进人工智能技术在现代计算机体系结构中的应用,并推动软件和硬件层面的发明。参与这项研究的本科生和研究生将接受下一代半导体行业劳动力的培训。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Hai Li其他文献
Operation Mode of Integrated Energy System with Liquid Air Energy Storage
液态空气储能综合能源系统运行模式
- DOI:
- 发表时间:
2022 - 期刊:
- 影响因子:0
- 作者:
Ning Bai;Yixue Liu;Xiaoxia Jiang;S. Cui;Hai Li;Qing He - 通讯作者:
Qing He
Shortcut-to-adiabaticity quantum tripartite Otto cycle
绝热性量子三方奥托循环的捷径
- DOI:
10.1088/1361-6455/ac3c93 - 发表时间:
2021-11 - 期刊:
- 影响因子:0
- 作者:
Lunan Li;Hai Li;Wenli Yu;Yaming Hao;Lei Li;Jian Zou - 通讯作者:
Jian Zou
ROS-Based Control Implementation of an Soft Gripper with Force Feedback
基于 ROS 的力反馈软夹具控制实现
- DOI:
10.1007/978-3-030-89095-7_51 - 发表时间:
2021 - 期刊:
- 影响因子:0
- 作者:
Yue Qiu;Xianmin Zhang;Hai Li;Rixin Wang - 通讯作者:
Rixin Wang
Preparation and Characterization of GLUT1-mediated Novel Brain Targeting Magnetic Nanoparticles
GLUT1介导的新型脑靶向磁性纳米颗粒的制备和表征
- DOI:
10.2174/1570180815666180322113934 - 发表时间:
2018-10 - 期刊:
- 影响因子:1
- 作者:
Zhang Li;Zhao Yi;Yue Qiming;Fu Qiuyi;Hai Li;Guo Li;Wang Qiantao;Wu Yong - 通讯作者:
Wu Yong
Automatic three-dimensional imaging for blastomere identification in early-stage embryos based on brightfield microscopy
基于明场显微镜的早期胚胎卵裂球自动三维成像识别
- DOI:
10.1016/j.optlaseng.2020.106093 - 发表时间:
2020-07 - 期刊:
- 影响因子:4.6
- 作者:
Sheng Yao;James K. Mills;Ihab Abu Ajamieh;Hai Li;Xianmin Zhang - 通讯作者:
Xianmin Zhang
Hai Li的其他文献
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{{ truncateString('Hai Li', 18)}}的其他基金
Conference: NSF Workshop on Hardware-Software Co-design for Neuro-Symbolic Computation
会议:NSF 神经符号计算软硬件协同设计研讨会
- 批准号:
2338640 - 财政年份:2023
- 资助金额:
$ 18.9万 - 项目类别:
Standard Grant
CCF Core: Small: Hardware/Software Co-Design for Sustainability at the Edge
CCF 核心:小型:硬件/软件协同设计,实现边缘的可持续性
- 批准号:
2233808 - 财政年份:2022
- 资助金额:
$ 18.9万 - 项目类别:
Standard Grant
Collaborative Research: CNS Core: Medium: Exploiting Synergies Between Machine-Learning Algorithms and Hardware Heterogeneity for High-Performance and Reliable Manycore Computing
合作研究:CNS Core:Medium:利用机器学习算法和硬件异构性之间的协同作用实现高性能和可靠的众核计算
- 批准号:
1955196 - 财政年份:2020
- 资助金额:
$ 18.9万 - 项目类别:
Continuing Grant
NSF Convergence Accelerator Track D: A Trusted Integrative Model and Data Sharing Platform for Accelerating AI-Driven Health Innovation
NSF 融合加速器轨道 D:加速人工智能驱动的健康创新的可信集成模型和数据共享平台
- 批准号:
2040588 - 财政年份:2020
- 资助金额:
$ 18.9万 - 项目类别:
Standard Grant
FET: Small: RESONANCE: Accelerating Speech/Language Processing through Collective Training using Commodity ReRAM Chips
FET:小型:共振:使用商用 ReRAM 芯片通过集体训练加速语音/语言处理
- 批准号:
1910299 - 财政年份:2019
- 资助金额:
$ 18.9万 - 项目类别:
Standard Grant
SHF: Small: Cross-Platform Solutions for Pruning and Accelerating Neural Network Models
SHF:小型:用于修剪和加速神经网络模型的跨平台解决方案
- 批准号:
1744082 - 财政年份:2017
- 资助金额:
$ 18.9万 - 项目类别:
Standard Grant
CSR: Small: Collaborative Research: GAMBIT: Efficient Graph Processing on a Memristor-based Embedded Computing Platform
CSR:小型:协作研究:GAMBIT:基于忆阻器的嵌入式计算平台上的高效图形处理
- 批准号:
1717885 - 财政年份:2017
- 资助金额:
$ 18.9万 - 项目类别:
Standard Grant
SHF: Small: Cross-Platform Solutions for Pruning and Accelerating Neural Network Models
SHF:小型:用于修剪和加速神经网络模型的跨平台解决方案
- 批准号:
1615475 - 财政年份:2016
- 资助金额:
$ 18.9万 - 项目类别:
Standard Grant
XPS: DSD: Collaborative Research: NeoNexus: The Next-generation Information Processing System across Digital and Neuromorphic Computing Domains
XPS:DSD:协作研究:NeoNexus:跨数字和神经形态计算领域的下一代信息处理系统
- 批准号:
1337198 - 财政年份:2013
- 资助金额:
$ 18.9万 - 项目类别:
Standard Grant
Collaborative Research: SMURFS: Statistical Modeling, SimUlation and Robust Design Techniques For MemriStors
合作研究:SMURFS:忆存的统计建模、模拟和鲁棒设计技术
- 批准号:
1311747 - 财政年份:2013
- 资助金额:
$ 18.9万 - 项目类别:
Standard Grant
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