Research Infrastructure: CC* Data Storage: Broadening UMBCs Data Storage footprint to Advance Scientific Research and Discovery

研究基础设施：CC* 数据存储：扩大 UMBC 数据存储足迹以推进科学研究和发现

• 批准号: 2346667
• 负责人: Damian Doyle
• 金额: $ 49.81万
• 依托单位: University of Maryland Baltimore County
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-04-01 至 2026-03-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2346667&HistoricalAwards=false
• 关键词: Research; Infrastructure; CC; Data; Storage

The Retriever Research Storage System R-RSTOR enables UMBC researchers and collaborators to address important research in atmospheric science, analyze polar ice caps, and develop AI models for human and robotic interactions. The system supports increased collaborations with the University of Maryland Center for Environmental Science (UMCES) on research into the ecology of the Chesapeake Bay and its watershed, as well as broader community access through the Open Science Data Federation. Utilizing the open-source Ceph file system that provides a flexible, high-performance, cost-effective, and scalable file architecture that will allow us to greatly expand allocations for all faculty conducting research.This system integrates with UMBC's existing High-Performance Computing Facility and Science DMZ to streamline interdisciplinary and inter-institutional collaborations. R-RSTOR is designed to utilize low latency non-volatile memory express (NVME) components and large-scale multi-petabyte solid state disc to reduce complexities and costs associated with data manipulation and transfer, which shortens the time to research. The Ceph file system allows researchers the ability to handle file, block, and object-based file structures within a single system. Through the additional gateways running on the system, researchers can utilize application programming interfaces (APIs) for enhanced data mobility between on-premises and cloud environments, accommodating evolving computational requirements as more workloads shift to a hybrid cloud model.This award by the Office of Advanced Cyberinfrastructure is also supported by National Discovery Cloud for Climate (NDC-C) resources.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.

Retriever 研究存储系统 R-RSTOR 使 UMBC 研究人员和合作者能够开展大气科学领域的重要研究、分析极地冰盖以及开发用于人类和机器人交互的 AI 模型。 该系统支持与马里兰大学环境科学中心 (UMCES) 就切萨皮克湾及其流域的生态研究加强合作，并通过开放科学数据联盟支持更广泛的社区访问。利用开源 Ceph 文件系统，该系统提供灵活、高性能、经济有效且可扩展的文件架构，使我们能够极大地扩展所有进行研究的教师的分配。该系统与 UMBC 现有的高性能计算设施集成Science DMZ 旨在简化跨学科和机构间的合作。 R-RSTOR 旨在利用低延迟非易失性快速存储器 (NVME) 组件和大规模 PB 级固态磁盘来降低与数据操作和传输相关的复杂性和成本，从而缩短研究时间。 Ceph 文件系统使研究人员能够在单个系统中处理文件、块和基于对象的文件结构。通过系统上运行的附加网关，研究人员可以利用应用程序编程接口 (API) 来增强本地和云环境之间的数据移动性，从而适应随着更多工作负载转向混合云模型而不断变化的计算需求。先进的网络基础设施还得到国家气候发现云 (NDC-C) 资源的支持。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。