CC* NPEO: Toward the National Research Platform

CC* NPEO：迈向国家研究平台

• 批准号: 1826967
• 负责人: Larry Smarr
• 金额: $ 250万
• 依托单位: University of California-San Diego
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-10-01 至 2023-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1826967&HistoricalAwards=false
• 关键词: CC; NPEO; Toward; National; Research

Academic researchers need a simple data sharing architecture with end-to-end 10-to-100Gbps performance to enable virtual co-location of large amounts of data with computing. End-to-end is a difficult problem to solve in general because the networks between ends (campuses, data repositories, etc.) typically traverse multiple network management domains: campus, regional, and national. No one organization owns the responsibility for providing scientists with high-bandwidth disk-to-disk performance. Toward the National Research Platform (TNRP), addresses issues critical to scaling end-to-end data sharing. TNRP will instrument a large federation of heterogeneous "national-regional-state" networks (NRSNs) to greatly improve end-to-end network performance across the nation. The goal of improving end-to-end network performance across the nation requires active participation of these distributed intermediate-level entities to reach out to their campuses. They are trusted conveners of their member institutions, contributing effectively to the "people networking" that is as necessary to the development of a full National Research Platform as is the stability, deployment, and performance of technology. TNRP's collaborating NRSNs structure leads to engagement of a large set of science applications, identified by the participating NRSNs and the Open Science Grid. TNRP is highly instrumented to directly measure performance. Visualizations of disk-to-disk performance with passive and active network monitoring show intra- and inter-NSRN end-to-end performance. Internet2, critical for interconnecting regional networks, will provide an instrumented dedicated virtual network instance for the interconnection of TNRP's NRSNs. Cybersecurity is a continuing concern; evaluations of advanced containerized orchestration, hardware crypto engines, and novel IPv6 strategies are part of the TNRP plan.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.

学术研究人员需要一个具有端到端 10 至 100Gbps 性能的简单数据共享架构，以实现大量数据与计算的虚拟共置。一般来说，端到端是一个很难解决的问题，因为两端（校园、数据存储库等）之间的网络通常会穿越多个网络管理域：校园、区域和国家。 没有任何组织有责任为科学家提供高带宽磁盘到磁盘性能。迈向国家研究平台（TNRP），解决扩展端到端数据共享的关键问题。 TNRP 将建立一个由异构“国家-地区-国家”网络 (NRSN) 组成的大型联盟，以极大地提高全国范围内的端到端网络性能。提高全国端到端网络性能的目标需要这些分布式中级实体的积极参与，以覆盖其校园。他们是其成员机构值得信赖的召集人，为“人员网络”做出了有效贡献，这对于发展完整的国家研究平台以及技术的稳定性、部署和性能都是必要的。 TNRP 的合作 NRSN 结构导致大量科学应用程序的参与，这些应用程序由参与的 NRSN 和开放科学网格确定。 TNRP 高度仪器化，可以直接衡量绩效。通过被动和主动网络监控实现磁盘到磁盘性能的可视化，显示 NSRN 内和 NSRN 间的端到端性能。 Internet2 对于互连区域网络至关重要，它将为 TNRP 的 NRSN 互连提供一个仪表化的专用虚拟网络实例。网络安全是一个持续关注的问题；对先进容器化编排、硬件加密引擎和新颖的 IPv6 策略的评估是 TNRP 计划的一部分。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力优点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

Characterizing network paths in and out of the clouds

表征云中和云外的网络路径

• DOI: 10.1051/epjconf/202024507059
• 发表时间: 2020
• 期刊: EPJ Web of Conferences
• 作者: Sfiligoi, Igor;Graham, John;Wuerthwein, Frank
• 通讯作者: Wuerthwein, Frank

NASCENT2: Generic Near-Storage Sort Accelerator for Data Analytics on SmartSSD

NSCENT2：用于 SmartSSD 上数据分析的通用近存储排序加速器

• DOI: 10.1145/3472769
• 发表时间: 2022
• 期刊: ACM Transactions on Reconfigurable Technology and Systems
• 影响因子: 2.3
• 作者: Salamat, Sahand;Zhang, Hui;Ki, Yang Seok;Rosing, Tajana
• 通讯作者: Rosing, Tajana

GenieHD: Efficient DNA Pattern Matching Accelerator Using Hyperdimensional Computing

• DOI: 10.23919/date48585.2020.9116397
• 发表时间: 2020-01-01
• 期刊: PROCEEDINGS OF THE 2020 DESIGN, AUTOMATION & TEST IN EUROPE CONFERENCE & EXHIBITION (DATE 2020)
• 作者: Kim, Yeseong;Imani, Mohsen;Rosing, Tajana
• 通讯作者: Rosing, Tajana

Depthwise Convolution Is All You Need for Learning Multiple Visual Domains

• DOI: 10.1609/aaai.v33i01.33018368
• 发表时间: 2019-01-01
• 期刊: arXiv
• 作者: Guo, Y.;Li, Y.;Rosing, T.
• 通讯作者: Rosing, T.

Revisiting HyperDimensional Learning for FPGA and Low-Power Architectures

• DOI: 10.1109/hpca51647.2021.00028
• 发表时间: 2021-01-01
• 期刊: 2021 27TH IEEE INTERNATIONAL SYMPOSIUM ON HIGH-PERFORMANCE COMPUTER ARCHITECTURE (HPCA 2021)
• 作者: Imani, Mohsen;Zou, Zhuowen;Rosing, Tajana
• 通讯作者: Rosing, Tajana