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
基本信息
- 批准号:2233808
- 负责人:
- 金额:$ 60万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2022
- 资助国家:美国
- 起止时间:2022-11-01 至 2025-10-31
- 项目状态:未结题
- 来源:
- 关键词:
项目摘要
Due to the wide proliferation of cloud and now edge servers, the development of sustainable acceleration methods for edge and cloud computing and artificial intelligence (AI) acceleration is beneficial to society broadly and the computer science community, in particular. Reducing carbon and methane emissions is important to reaching environmental goals for reducing warming for which targets of 2030 and 2050 have been set. This project tackles the broader implications of the growing popularity of edge and cloud computing for executing AI to establish a sustainable computing system design methodology beyond pure energy efficiency. Unlike solely energy-efficient designs that focus on reducing power consumption and carbon emissions as a by-product, this project will build a hardware/software co-design framework to generate the optimal hardware and algorithm designs that meet specific constraints of functionality, performance, sustainability, and other system requirements. The framework will guide future sustainable hardware design. Towards this goal, the proposed framework engages holistic co-design efforts across four levels - modeling, algorithm, scheduling, and hardware.By introducing new synergies between computing paradigms and emerging AI applications, the outcomes of this research will benefit the entire AI industry, from hardware development to algorithm design and the applications for the end-users. The proposed co-design framework will be the first research in the community to build holistically sustainable AI systems which are recently recognized as emerging in importance. The success of this project will pave the road for future sustainable computing system design. The educational efforts aim at cultivating students' interests in the study of sustainable computing, contemporary computer architecture, and artificial intelligence. The existing curricula of computer organization, algorithms, and computing systems will be enhanced by the interdisciplinary research topics on sustainable computing, edge computing, and machine learning, as well as the hands-on experiences in building the simulation prototypes. Special attention will be given to recruiting underrepresented groups and enriching studentsí study experiences through new education forums.This project is funded by funds allocated to Design for Sustainable Computing (NSF 22-060)This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
由于云和边缘服务器的广泛普及,边缘和云计算以及人工智能(AI)加速的可持续加速方法的开发对社会广泛有益,特别是计算机科学界。减少碳和甲烷排放对于实现减少变暖的环境目标至关重要,这些目标已设定为2030年和2050年。该项目解决了边缘和云计算日益普及的广泛影响,以执行AI,建立超越纯粹能源效率的可持续计算系统设计方法。与专注于减少功耗和副产品碳排放的纯粹节能设计不同,该项目将构建硬件/软件协同设计框架,以生成满足功能、性能、可持续性和其他系统要求的特定约束的最佳硬件和算法设计。该框架将指导未来的可持续硬件设计。为了实现这一目标,该框架在建模、算法、调度和硬件四个层面上进行了全面的协同设计,通过引入计算范式和新兴人工智能应用之间的新协同效应,这项研究的成果将有利于整个人工智能行业,从硬件开发到算法设计和最终用户的应用。拟议的共同设计框架将是社区中第一个建立整体可持续人工智能系统的研究,这些系统最近被认为是重要的。该项目的成功将为未来的可持续计算系统设计铺平道路。教育工作旨在培养学生对可持续计算,当代计算机体系结构和人工智能的研究兴趣。计算机组织,算法和计算系统的现有课程将通过可持续计算,边缘计算和机器学习的跨学科研究主题以及构建模拟原型的实践经验来增强。该项目由可持续计算设计(NSF 22-060)基金资助。该奖项反映了NSF的法定使命,通过使用基金会的智力价值和更广泛的影响审查标准进行评估,被认为值得支持。
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:
$ 60万 - 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:
$ 60万 - 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:
$ 60万 - 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:
$ 60万 - 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:
$ 60万 - 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:
$ 60万 - 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:
1744077 - 财政年份:2017
- 资助金额:
$ 60万 - 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:
$ 60万 - 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:
$ 60万 - 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:
$ 60万 - 项目类别:
Standard Grant
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