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

• 批准号: 2217070
• 负责人: Ada Gavrilovska
• 金额: $ 122.5万
• 依托单位: Georgia Tech Research Corporation
• 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
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2217070&HistoricalAwards=false
• 关键词: Collaborative; Research; PPoSS; LARGE; Scalable

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

Tri-State Circuits - A Circuit Model that Captures RAM

• DOI: 10.1007/978-3-031-38551-3_5
• 发表时间: 2023
• 作者: David Heath;V. Kolesnikov;R. Ostrovsky

Fast ORAM with Server-Aided Preprocessing and Pragmatic Privacy-Efficiency Trade-Off

具有服务器辅助预处理和务实的隐私效率权衡的快速 ORAM

• 发表时间: 2023
• 期刊: and Machine Learning CSCML 2023
• 作者: Vladimir Kolesnikov, Stanislav Peceny

FleXR: A System Enabling Flexibly Distributed Extended Reality

• DOI: 10.1145/3587819.3590966
• 发表时间: 2023-06
• 期刊: Proceedings of the 14th Conference on ACM Multimedia Systems
• 作者: Jin Heo;Ketan Bhardwaj;Ada Gavrilovska

FLiCR: A Fast and Lightweight LiDAR Point Cloud Compression Based on Lossy RI

• DOI: 10.1109/sec54971.2022.00012
• 发表时间: 2022-12
• 期刊: 2022 IEEE/ACM 7th Symposium on Edge Computing (SEC)
• 作者: Jin Heo;Christopher Phillips;Ada Gavrilovska

Batchman and Robin: Batched and Non-batched Branching for Interactive ZK

• DOI: 10.1145/3576915.3623169
• 发表时间: 2023-11
• 期刊: Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security
• 作者: Yibin Yang;David Heath;Carmit Hazay;V. Kolesnikov;Muthuramakrishnan Venkitasubramaniam