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.

回猎犬研究存储系统R-RSTOR使UMBC的研究人员和合作者能够解决大气科学领域的重要研究，分析极地冰盖，并为人类和机器人相互作用开发AI模型。 该系统支持与马里兰州环境科学中心（UMCE）有关Chesapeake Bay及其流域生态学的研究以及通过开放科学数据联合会的更广泛的社区访问。利用开源CEPH文件系统，该系统提供了灵活，高性能，具有成本效益和可扩展的文件架构，这将使我们能够为所有教师进行研究大大扩展分配。该系统与UMBC现有的高表现计算机和科学DMZ集成，以简化跨学科和跨学科的合作。 R-RSTOR旨在利用低潜伏期非易失性记忆快递（NVME）组件和大规模的多核固态固态光盘来降低与数据操作和传输相关的复杂性和成本，从而缩短了研究时间。 CEPH文件系统允许研究人员能够处理单个系统中的文件，块和基于对象的文件结构。 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 Cyber​​infrastructure is also supported by National Discovery Cloud for Climate (NDC-C) resources.This award reflects NSF's statutory mission and has been deemed值得通过基金会的智力优点和更广泛的影响审查标准来通过评估来支持。