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
基本信息
- 批准号:2320196
- 负责人:
- 金额:$ 91.04万
- 依托单位:
- 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:
- 关键词:
项目摘要
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.
该项目为阿拉斯加大学费尔班克斯分校(UAF)采购基于现代图形处理器(GPU)的计算节点和充足的高性能存储提供资金,这些存储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(CyBR)的网络基础设施,将在UAF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。该仪器将成为在对阿拉斯加、其气候和自然资源至关重要的多个科学和工程学科中增加高度优先的、数据驱动的研究的催化剂。这些包括阿拉斯加独特的动植物及其社会文化和经济流动性。至少有20个不同的研究项目将从该仪器中受益。研究领域包括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、北部野火管理、阿拉斯加地震探测、阿拉斯加采矿安全、野生动物和生态学、北冰洋建模和空间科学。NSF阿拉斯加EPSCoR承认其中许多是高度优先的研究领域。其他研究领域包括冰川学、火山学、水处理、关键矿物提取和阿拉斯加低碳建筑材料的发现。所有这些都可能为新的融资机会提供支持。该项目还将为第一代大学生、女大学生以及包括阿拉斯加土著社区在内的边缘化社区的学生创造培训机会。CyBR将有助于使数据分析和计算密集型劳动力多样化,这不仅在阿拉斯加是无价的,在数据分析工作正以前所未有的速度扩展的国家也是如此。大数据研究高性能计算仪器的网络基础设施将由10个计算节点组成,每个节点都配备AMD CPU、NVIDIA图形处理器、至少256 GB RAM和NVMe固态硬盘。该硬件将配备一个大型的Lustre存储阵列来容纳大数据,以及一个HDR Infiniband交换机,用于在节点和存储之间进行高速、低延迟的数据传输,从而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小组合作购买、安装和维护该仪器。它将位于Butrovich数据中心,在那里它将连接到UAF现有的Chinook HPC集群。将新的CybR仪器与现有的HPC集群集成,将减少使这一新仪器可供研究人员使用的时间,减少操作它所需的基础设施,并减少维护它的管理开销。该项目由重大研究仪器(MRI)计划、既定的激励竞争研究计划(EPSCoR)、信息技术研究(ITR)计划和高级网络基础设施办公室(OAC)联合资助。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。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
数据更新时间:{{ journalArticles.updateTime }}
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
数据更新时间:{{ journalArticles.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ monograph.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ sciAawards.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ conferencePapers.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ patent.updateTime }}
Arghya Das其他文献
Asymptotically flat vacuum solution for a rotating black hole in a modified gravity theory
修正引力理论中旋转黑洞的渐近平坦真空解
- DOI:
10.1140/epjc/s10052-022-10899-5 - 发表时间:
2022 - 期刊:
- 影响因子:0
- 作者:
Arghya Das;B. Mukhopadhyay - 通讯作者:
B. Mukhopadhyay
An advanced pore-scale model for simulating water retention characteristics in granular soils
用于模拟粒状土壤保水特性的先进孔隙尺度模型
- DOI:
10.1016/j.jhydrol.2022.128561 - 发表时间:
2022 - 期刊:
- 影响因子:6.4
- 作者:
Suaiba Mufti;Arghya Das - 通讯作者:
Arghya Das
Evaluation of a simple method for testing aztreonam and ceftazidime-avibactam synergy in New Delhi metallo-beta-lactamase producing Enterobacterales
评估新德里产金属-β-内酰胺酶肠杆菌中氨曲南和头孢他啶-阿维巴坦协同作用的简单方法
- DOI:
- 发表时间:
2024 - 期刊:
- 影响因子:3.7
- 作者:
Salman Khan;Arghya Das;Deepali Vashisth;Anwita Mishra;A. Vidyarthi;Raghav Gupta;N. Begam;Babita Kataria;Sushma Bhatnagar - 通讯作者:
Sushma Bhatnagar
Mucormycosis and black fungus: Breaking the myth.
毛霉菌病和黑木耳:打破神话。
- DOI:
- 发表时间:
2021 - 期刊:
- 影响因子:4.9
- 作者:
A. Vidyarthi;Arghya Das;R. Chaudhry - 通讯作者:
R. Chaudhry
Transport and fluctuations in mass aggregation processes: Mobility-driven clustering.
质量聚合过程中的传输和波动:移动驱动的聚类。
- DOI:
- 发表时间:
2020 - 期刊:
- 影响因子:2.4
- 作者:
Subhadip Chakraborti;Tanmoy Chakraborty;Arghya Das;Rahul Dandekar;P. Pradhan - 通讯作者:
P. Pradhan
Arghya Das的其他文献
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
{{ truncateString('Arghya Das', 18)}}的其他基金
RII Track-4: NSF: Extracting Pan Genomic Information from Metagenomic Data: Distributed Algorithms and Scalable Software
RII Track-4:NSF:从宏基因组数据中提取泛基因组信息:分布式算法和可扩展软件
- 批准号:
2327456 - 财政年份:2024
- 资助金额:
$ 91.04万 - 项目类别:
Standard Grant
相似国自然基金
肝硬化患者4D Flow MRI血流动力学与肝脂肪和铁代谢的交互机制研究
- 批准号:
- 批准年份:2025
- 资助金额:0.0 万元
- 项目类别:省市级项目
基于生物学引导MRI-Transformer模型评估三阴性乳腺癌抗PD-1/PD-L1免疫治疗反应的研究
- 批准号:QN25H180017
- 批准年份:2025
- 资助金额:0.0 万元
- 项目类别:省市级项目
基于MRI深度学习Grad-CAM技术的临床显著性前列腺癌预测模型研究
- 批准号:
- 批准年份:2025
- 资助金额:0.0 万元
- 项目类别:省市级项目
基于MRI时空异质性的影像组学联合临床文本数据挖掘预测乳腺癌HER2表达状态的研究
- 批准号:
- 批准年份:2025
- 资助金额:0.0 万元
- 项目类别:省市级项目
核酸适体偶联的靶向对比剂用于早期膀胱癌的MRI成像诊断
- 批准号:
- 批准年份:2025
- 资助金额:0.0 万元
- 项目类别:省市级项目
MRI深度组学联合液体活检技术构建乳腺癌新辅助化疗后pCR状态精准量化预测体系
- 批准号:MS25H180029
- 批准年份:2025
- 资助金额:0.0 万元
- 项目类别:省市级项目
基于MRI影像组学特征的子宫内膜癌分子分型术前预测模型构建
- 批准号:2025JJ80869
- 批准年份:2025
- 资助金额:0.0 万元
- 项目类别:省市级项目
αvβ3整合素靶向有机探针用于NIR-II FL/MRI双模态成像引导的三阴性乳腺癌光热治疗研究
- 批准号:2025JJ81013
- 批准年份:2025
- 资助金额:0.0 万元
- 项目类别:省市级项目
γ-谷氨酰转肽酶响应的近红外(NIR)余辉/MRI探针用于肝癌的诊疗一体化
- 批准号:2025JJ81188
- 批准年份:2025
- 资助金额:0.0 万元
- 项目类别:省市级项目
基于时间依赖扩散MRI成像评估三阴性乳腺癌肿瘤免疫微环境特征及新辅助化学免疫治疗疗效的研究
- 批准号:2025JJ70285
- 批准年份:2025
- 资助金额:0.0 万元
- 项目类别:省市级项目
相似海外基金
Equipment: MRI: Track 2 Acquisition of a Novel Performance-Driven 3D Imaging System for Extremely Noisy Objects (NPIX)
设备: MRI:第 2 道采购新型性能驱动的 3D 成像系统,用于极噪物体 (NPIX)
- 批准号:
2319708 - 财政年份:2023
- 资助金额:
$ 91.04万 - 项目类别:
Continuing Grant
Equipment: MRI Track 1: Acquisition of Flow Cytometer
设备:MRI 轨道 1:流式细胞仪的购置
- 批准号:
2320130 - 财政年份:2023
- 资助金额:
$ 91.04万 - 项目类别:
Standard Grant
Equipment: MRI: Track 2 Acquisition of a Hydraulic and Sediment Recirculation Flume to Advance Fundamental Research in Urban Stormwater and Fluvial Processes
设备: MRI:轨道 2 获取水力和沉积物再循环水槽,以推进城市雨水和河流过程的基础研究
- 批准号:
2320356 - 财政年份:2023
- 资助金额:
$ 91.04万 - 项目类别:
Standard Grant
Collaborative Research: Equipment: MRI Consortium: Track 2 Development of a Next Generation Fast Neutron Detector
合作研究:设备:MRI 联盟:下一代快中子探测器的 Track 2 开发
- 批准号:
2320407 - 财政年份:2023
- 资助金额:
$ 91.04万 - 项目类别:
Standard Grant
Collaborative Research: Equipment: MRI Consortium: Track 2 Development of a Next Generation Fast Neutron Detector
合作研究:设备:MRI 联盟:下一代快中子探测器的 Track 2 开发
- 批准号:
2320405 - 财政年份:2023
- 资助金额:
$ 91.04万 - 项目类别:
Standard Grant
Equipment: MRI: Track 1: Acquisition of a Zeiss 560 VP FE-SEM for chemical and surface characterization and training.
设备:MRI:轨道 1:购买 Zeiss 560 VP FE-SEM,用于化学和表面表征和培训。
- 批准号:
2320480 - 财政年份:2023
- 资助金额:
$ 91.04万 - 项目类别:
Standard Grant
MRI: Track 3 Acquisition of Helium Recovery Equipment at West Virginia University
MRI:第 3 轨道采购西弗吉尼亚大学氦回收设备
- 批准号:
2320495 - 财政年份:2023
- 资助金额:
$ 91.04万 - 项目类别:
Standard Grant
Equipment: MRI: Track 1 Acquisition of a Digital Real-Time Simulator to Enhance Research and Student Research Training in Next-Generation Engineering and Computer Science
设备: MRI:轨道 1 采购数字实时模拟器,以加强下一代工程和计算机科学的研究和学生研究培训
- 批准号:
2320619 - 财政年份:2023
- 资助金额:
$ 91.04万 - 项目类别:
Standard Grant
Equipment: MRI: Track #1 Acquisition of a Differential Scanning Calorimeter to Support Modern Materials Research and Teaching at Western Washington University
设备: MRI:轨道
- 批准号:
2320809 - 财政年份:2023
- 资助金额:
$ 91.04万 - 项目类别:
Standard Grant
Equipment: MRI: Track 2 Acquisition of a HPC Cluster for Fostering Interdisciplinary Collaboration on AI-driven and Data-intensive Research and Education in West Tennessee
设备: MRI:第二轨道收购 HPC 集群,以促进田纳西州西部人工智能驱动和数据密集型研究和教育的跨学科合作
- 批准号:
2318210 - 财政年份:2023
- 资助金额:
$ 91.04万 - 项目类别:
Standard Grant