Collaborative Research: PPoSS: LARGE: Scalable Specialization in Distributed Edge-Cloud Systems – The Extended Reality Case

协作研究:PPoSS:大型:分布式边缘云系统的可扩展专业化 — 扩展现实案例

基本信息

  • 批准号:
    2217144
  • 负责人:
  • 金额:
    $ 374.04万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Continuing Grant
  • 财政年份:
    2022
  • 资助国家:
    美国
  • 起止时间:
    2022-10-01 至 2027-09-30
  • 项目状态:
    未结题

项目摘要

This project will develop design methodologies for a scalable, domain-specific, heterogeneous, distributed edge/cloud system with stringent constraints on latency, energy, thermal power, computational requirements, and size. The work will use a distributed multiparty augmented / virtual / mixed reality (collectively, extended reality or XR) experience as a target parallel and distributed application with challenging quality-of-experience goals, scalability requirements, design constraints, and diverse and fast-evolving algorithmic components. There are orders-of-magnitude gaps between desirable design goals and today's state-of-the-art, making this a long-lived multidisciplinary research challenge. The project brings together work in Computer Architecture, Programming Languages and Compilers, Systems, Security and Privacy, and Accuracy and Correctness. It will result in innovations that cut across the system stack to improve quality-of-experience scalability with the number of users and devices and device resources, XR device performance scalability with hardware parallelism, and design methodologies scalability with system complexity. The project will disseminate its research results through considerable open-source software artifacts, building on the team’s previously released ILLIXR system (the first open-source end-to-end single-device XR system), in addition to publications in top venues and talks in academic and industry venues. High-performance, energy-efficient distributed applications such as multiparty XR (and numerous others) have the potential for transformative impact on a vast number of societal activities such as medicine, education, entertainment, manufacturing, science, and more. The team will work in close collaboration with industry partners for direct technology-transfer avenues. The PIs will continue their past record of strong involvement of undergraduates, women, and minorities in research; leadership in establishing the CARES movement; and other efforts to broaden participation in computing.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.
该项目将为一个可扩展的、特定于领域的、异构的、分布式边缘/云系统开发设计方法,该系统对延迟、能源、热功率、计算要求和大小有严格的限制。这项工作将使用分布式多方增强/虚拟/混合现实(统称为延展实境或XR)体验作为目标并行和分布式应用程序,具有挑战性的体验质量目标,可扩展性要求,设计约束以及多样化和快速发展的算法组件。理想的设计目标和当今最先进的技术之间存在着数量级的差距,这使得这成为一个长期存在的多学科研究挑战。该项目汇集了计算机体系结构,编程语言和编译器,系统,安全和隐私以及准确性和正确性方面的工作。它将带来跨系统堆栈的创新,以提高用户和设备以及设备资源数量的体验质量可扩展性,XR设备性能可扩展性与硬件并行性,以及设计方法可扩展性与系统复杂性。该项目将通过大量的开源软件产品传播其研究成果,建立在该团队之前发布的ILLIXR系统(第一个开源端到端单设备XR系统)的基础上,此外还将在顶级场所发表论文,并在学术和行业场所进行讲座。 高性能、高能效的分布式应用程序,如多方XR(以及许多其他应用程序),有可能对医疗、教育、娱乐、制造、科学等大量社会活动产生变革性影响。该团队将与行业合作伙伴密切合作,寻求直接的技术转让途径。PI将继续保持其过去的记录,即大学生、妇女和少数民族积极参与研究;在建立CARES运动中发挥领导作用;以及其他扩大参与计算的努力。该奖项反映了NSF的法定使命,并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(3)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Incremental Verification of Neural Networks
  • DOI:
    10.1145/3591299
  • 发表时间:
    2023-04
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Shubham Ugare;Debangshu Banerjee;Sasa Misailovic;Gagandeep Singh
  • 通讯作者:
    Shubham Ugare;Debangshu Banerjee;Sasa Misailovic;Gagandeep Singh
Power, Performance, and Image Quality Tradeoffs in Foveated Rendering
  • DOI:
    10.1109/vr55154.2023.00036
  • 发表时间:
    2023-03
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Rahul Singh;Muhammad Huzaifa;Jeffrey Liu;Anjul Patney;Hashim Sharif;Yifan Zhao;S. Adve
  • 通讯作者:
    Rahul Singh;Muhammad Huzaifa;Jeffrey Liu;Anjul Patney;Hashim Sharif;Yifan Zhao;S. Adve
A PPROX C ALIPER : A P ROGRAMMABLE F RAMEWORK FOR A PPLICATION - AWARE N EURAL N ETWORK O PTIMIZATION
  • DOI:
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Yifan Zhao;Hashim Sharif;Peter Pao-Huang;Vatsin Ninad Shah;A. N. Sivakumar;M. V. Gasparino;Abdulrahman Mahmoud;Nathan Zhao;S. Adve;Girish V. Chowdhary;Sasa Misailovic;Vikram S. Adve
  • 通讯作者:
    Yifan Zhao;Hashim Sharif;Peter Pao-Huang;Vatsin Ninad Shah;A. N. Sivakumar;M. V. Gasparino;Abdulrahman Mahmoud;Nathan Zhao;S. Adve;Girish V. Chowdhary;Sasa Misailovic;Vikram S. Adve
{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

Sarita Adve其他文献

Under-canopy dataset for advancing simultaneous localization and mapping in agricultural robotics
用于推进农业机器人同步定位和绘图的树冠下数据集
  • DOI:
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    0
  • 作者:
    José Cuarán;Andres Eduardo Baquero Velasquez;Mateus Valverde Gasparino;N. Uppalapati;A. N. Sivakumar;Justin Wasserman;Muhammad Huzaifa;Sarita Adve;Girish Chowdhary
  • 通讯作者:
    Girish Chowdhary
FastFlip: Compositional Error Injection Analysis
FastFlip:组合错误注入分析
  • DOI:
    10.48550/arxiv.2403.13989
  • 发表时间:
    2024
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Keyur Joshi;Rahul Singh;Tommaso Bassetto;Sarita Adve;Darko Marinov;Sasa Misailovic
  • 通讯作者:
    Sasa Misailovic

Sarita Adve的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('Sarita Adve', 18)}}的其他基金

CCRI: New: An Open End-to-End Extended Reality System Infrastructure: Enabling Domain-Specific Edge Systems Research
CCRI:新:开放的端到端扩展现实系统基础设施:支持特定领域的边缘系统研究
  • 批准号:
    2120464
  • 财政年份:
    2021
  • 资助金额:
    $ 374.04万
  • 项目类别:
    Standard Grant
SHF: Medium: Software Engineering for Hardware Errors
SHF:中:针对硬件错误的软件工程
  • 批准号:
    1956374
  • 财政年份:
    2020
  • 资助金额:
    $ 374.04万
  • 项目类别:
    Continuing Grant
SHF: Small: Hardware-Software Co-Designed Coherence: A Complete Coherence Solution for Performance-, Energy-, and Complexity-Efficiency
SHF:小型:硬件-软件协同设计的一致性:针对性能、能源和复杂性效率的完整一致性解决方案
  • 批准号:
    1619245
  • 财政年份:
    2016
  • 资助金额:
    $ 374.04万
  • 项目类别:
    Standard Grant
SHF: Small: Software-Driven Hardware Resiliency
SHF:小型:软件驱动的硬件弹性
  • 批准号:
    1320941
  • 财政年份:
    2013
  • 资助金额:
    $ 374.04万
  • 项目类别:
    Standard Grant
SHF: Small: DeNovo: Rethinking Hardware for Disciplined Parallelism
SHF:小型:DeNovo:重新思考硬件以实现严格的并行性
  • 批准号:
    1018796
  • 财政年份:
    2010
  • 资助金额:
    $ 374.04万
  • 项目类别:
    Continuing Grant
CPA-CSA-T: Low Cost and Comprehensive Hardware Reliability
CPA-CSA-T:低成本和全面的硬件可靠性
  • 批准号:
    0811693
  • 财政年份:
    2008
  • 资助金额:
    $ 374.04万
  • 项目类别:
    Standard Grant
Lifetime Reliability Aware Microprocessors
终生可靠性感知微处理器
  • 批准号:
    0541383
  • 财政年份:
    2006
  • 资助金额:
    $ 374.04万
  • 项目类别:
    Standard Grant
ITR: Collaborative Hardware-Software Adaptation for Multimedia Applications
ITR:多媒体应用的软硬件协同适配
  • 批准号:
    0205638
  • 财政年份:
    2002
  • 资助金额:
    $ 374.04万
  • 项目类别:
    Continuing Grant
Using Simultaneous Multithreaded Processors for Soft Real-Time Applications
使用同步多线程处理器进行软实时应用
  • 批准号:
    0209198
  • 财政年份:
    2002
  • 资助金额:
    $ 374.04万
  • 项目类别:
    Continuing Grant
CISE Research Resources: Programming Environments and Applications for Clusters and Grids
CISE 研究资源:集群和网格的编程环境和应用程序
  • 批准号:
    0224453
  • 财政年份:
    2002
  • 资助金额:
    $ 374.04万
  • 项目类别:
    Standard Grant

相似国自然基金

Research on Quantum Field Theory without a Lagrangian Description
  • 批准号:
    24ZR1403900
  • 批准年份:
    2024
  • 资助金额:
    0.0 万元
  • 项目类别:
    省市级项目
Cell Research
  • 批准号:
    31224802
  • 批准年份:
    2012
  • 资助金额:
    24.0 万元
  • 项目类别:
    专项基金项目
Cell Research
  • 批准号:
    31024804
  • 批准年份:
    2010
  • 资助金额:
    24.0 万元
  • 项目类别:
    专项基金项目
Cell Research (细胞研究)
  • 批准号:
    30824808
  • 批准年份:
    2008
  • 资助金额:
    24.0 万元
  • 项目类别:
    专项基金项目
Research on the Rapid Growth Mechanism of KDP Crystal
  • 批准号:
    10774081
  • 批准年份:
    2007
  • 资助金额:
    45.0 万元
  • 项目类别:
    面上项目

相似海外基金

Collaborative Research: PPoSS: Large: A Full-stack Approach to Declarative Analytics at Scale
协作研究:PPoSS:大型:大规模声明性分析的全栈方法
  • 批准号:
    2316161
  • 财政年份:
    2023
  • 资助金额:
    $ 374.04万
  • 项目类别:
    Continuing Grant
Collaborative Research: PPoSS: LARGE: Research into the Use and iNtegration of Data Movement Accelerators (RUN-DMX)
协作研究:PPoSS:大型:数据移动加速器 (RUN-DMX) 的使用和集成研究
  • 批准号:
    2316176
  • 财政年份:
    2023
  • 资助金额:
    $ 374.04万
  • 项目类别:
    Continuing Grant
Collaborative Research: PPoSS: Large: A Full-stack Approach to Declarative Analytics at Scale
协作研究:PPoSS:大型:大规模声明性分析的全栈方法
  • 批准号:
    2316158
  • 财政年份:
    2023
  • 资助金额:
    $ 374.04万
  • 项目类别:
    Continuing Grant
Collaborative Research: PPoSS: LARGE: Cross-layer Coordination and Optimization for Scalable and Sparse Tensor Networks (CROSS)
合作研究:PPoSS:LARGE:可扩展和稀疏张量网络的跨层协调和优化(CROSS)
  • 批准号:
    2316201
  • 财政年份:
    2023
  • 资助金额:
    $ 374.04万
  • 项目类别:
    Standard Grant
Collaborative Research: PPoSS: LARGE: Cross-layer Coordination and Optimization for Scalable and Sparse Tensor Networks (CROSS)
合作研究:PPoSS:LARGE:可扩展和稀疏张量网络的跨层协调和优化(CROSS)
  • 批准号:
    2316203
  • 财政年份:
    2023
  • 资助金额:
    $ 374.04万
  • 项目类别:
    Continuing Grant
Collaborative Research: PPoSS: LARGE: Research into the Use and iNtegration of Data Movement Accelerators (RUN-DMX)
协作研究:PPoSS:大型:数据移动加速器 (RUN-DMX) 的使用和集成研究
  • 批准号:
    2316177
  • 财政年份:
    2023
  • 资助金额:
    $ 374.04万
  • 项目类别:
    Continuing Grant
Collaborative Research: PPoSS: LARGE: Cross-layer Coordination and Optimization for Scalable and Sparse Tensor Networks (CROSS)
合作研究:PPoSS:LARGE:可扩展和稀疏张量网络的跨层协调和优化(CROSS)
  • 批准号:
    2316202
  • 财政年份:
    2023
  • 资助金额:
    $ 374.04万
  • 项目类别:
    Standard Grant
Collaborative Research: PPoSS: LARGE: General-Purpose Scalable Technologies for Fundamental Graph Problems
合作研究:PPoSS:大型:解决基本图问题的通用可扩展技术
  • 批准号:
    2316235
  • 财政年份:
    2023
  • 资助金额:
    $ 374.04万
  • 项目类别:
    Continuing Grant
Collaborative Research: PPoSS: LARGE: Principles and Infrastructure of Extreme Scale Edge Learning for Computational Screening and Surveillance for Health Care
合作研究:PPoSS:大型:用于医疗保健计算筛查和监视的超大规模边缘学习的原理和基础设施
  • 批准号:
    2406572
  • 财政年份:
    2023
  • 资助金额:
    $ 374.04万
  • 项目类别:
    Continuing Grant
Collaborative Research: PPoSS: Large: A Full-stack Approach to Declarative Analytics at Scale
协作研究:PPoSS:大型:大规模声明性分析的全栈方法
  • 批准号:
    2316159
  • 财政年份:
    2023
  • 资助金额:
    $ 374.04万
  • 项目类别:
    Continuing Grant
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了