Equipment: MRI Track-I: Acquisition of CyBR: Cyber Infrastructure for Big Data Research Critical for Alaska

设备： MRI Track-I：收购 CyBR：对阿拉斯加至关重要的大数据研究网络基础设施

• 批准号: 2320196
• 负责人: Arghya Das
• 金额: $ 91.04万
• 依托单位: University of Alaska Fairbanks Campus
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-15 至 2025-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2320196&HistoricalAwards=false
• 关键词: Equipment; MRI; Track; Acquisition; CyBR

This project funds the procurement of modern Graphics Processing Unit (GPU) based compute nodes and sufficient high-performance storage at University of Alaska Fairbanks (UAF) that will support a new range of data and compute-intensive applications to allow new science and engineering discoveries. This system, a Cyberinfrastructure for Big data Research (CyBR), will enable artificial intelligence, machine learning, deep learning, image analysis, statistical modeling, and large-scale simulations at UAF. The instrument will be a catalyst for increasing high priority, data-driven research in multiple science and engineering disciplines critical to Alaska, its climate and its natural resources. These include Alaska’s distinctive flora and fauna and its sociocultural and economic mobility. At least 20 different research projects will benefit from the instrumentation. Research areas include Arctic marine biology and implications for Indigenous communities, Alaska coastal modeling, boreal wildfire management, Alaska earthquake detection, Alaska mining safety, wildlife and ecology, Arctic Ocean modeling and space science. NSF Alaska EPSCoR recognizes many of these as high-priority research areas. Other research areas include, glaciology, volcanology, water treatment, critical mineral extraction and discovery of low carbon construction material in Alaska. All of these will potentially support new funding opportunities. This project will also create training opportunities for first-generation college students, female students, and those from marginalized communities, including Alaska Native communities. CyBR will aid in diversifying the data analysis and computationally intensive workforce, which is invaluable not only in Alaska but also in the nation where data analysis jobs are expanding at an unprecedented rate.The Cyberinfrastructure for Big data Research high-performance computing instrument will consist of 10 compute nodes, each with AMD CPUs, NVIDIA GPUs, at least 256GB RAM, and NVMe SSDs. This hardware will be accompanied by a large Lustre storage array to accommodate big data and an HDR Infiniband switch for high-speed, low-latency data transfer between nodes and the storage so that computational performance is not bottlenecked by network bandwidth. The research team will collaborate with the UAF Geophysical Institute’s Research Computing Systems group to purchase, install and maintain the instrument. It will be located in the Butrovich Data Center, where it will be connected to UAF’s existing Chinook HPC cluster. Integrating the new CyBR instrument with the existing HPC cluster will reduce the time to make this new instrument available to researchers, reduce the infrastructure needed to operate it and reduce the management overhead to maintain it.This project is jointly funded by the Major Research Instrumentation (MRI) program, the Established Program to Stimulate Competitive Research (EPSCoR), the Information Technology Research (ITR) program, and the Office of Advanced Cyberinfrastructure (OAC).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.

该项目资助在阿拉斯加大学费尔班克斯分校 (UAF) 采购基于现代图形处理单元 (GPU) 的计算节点和足够的高性能存储，这将支持一系列新的数据和计算密集型应用程序，以实现新的科学和工程发现该系统是大数据研究网络基础设施 (CyBR)，将在 UAF 中实现人工智能、机器学习、深度学习、图像分析、统计建模和大规模模拟。该仪器将成为提高高优先级、对阿拉斯加及其气候和自然资源至关重要的多个科学和工程学科的数据驱动研究，其中包括阿拉斯加独特的动植物群及其社会文化和经济流动性。北极海洋生物学及其对土著社区的影响、阿拉斯加沿海建模、北方野火管理、阿拉斯加地震探测、阿拉斯加采矿安全、野生动物和生态、北冰洋建模和空间科学将其中许多视为高度优先的研究。其他研究领域包括冰川学、火山学、水处理、关键矿物开采和阿拉斯加低碳建筑材料的发现，所有这些都可能为第一代大学生创造培训机会。 、女学生和来自边缘化社区（包括阿拉斯加原住民社区）的人将有助于实现数据分析和计算密集型劳动力的多样化，这不仅在阿拉斯加而且在数据分析工作以前所未有的速度增长的国家都非常宝贵。 .大数据研究的网络基础设施高性能计算设备将由 10 个计算节点组成，每个节点均配备 AMD CPU、NVIDIA GPU、至少 256GB RAM 和 NVMe SSD。该硬件将配备一个大型 Lustre 存储阵列，用于容纳大数据和一个 HDR Infiniband 交换机。节点和存储之间的高速、低延迟数据传输，使计算性能不会受到网络带宽的瓶颈。研究团队将与 UAF 地球物理研究所的研究计算系统合作。该仪器将位于 Butrovich 数据中心，并连接到 UAF 现有的 Chinook HPC 集群，将新的 CyBR 仪器与现有的 HPC 集群集成将减少制造该新仪器的时间。为研究人员提供可用的仪器，减少操作所需的基础设施并减少维护管理费用。该项目由主要研究仪器（MRI）计划、刺激竞争性研究既定计划（EPSCoR）、该奖项反映了 NSF 的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。