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CC* Regional Computing: CENVAL-ARC: Central Valley Accessible Research and Computational Hub

CC* Regional Computing: CENVAL-ARC: Central Valley Accessible Research and Computational Hub
CC* 区域计算:CENVAL-ARC:中央谷无障碍研究和计算中心
批准号:
2346744
负责人:
Sarvani Chadalapaka
金额:
$100.0万
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
项目状态:
未结题
起止时间:
2024-06-01 至 2026-05-31

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中文摘要
翻译
中央谷高级研究计算(CENVAL-ARC)计划旨在解决加州历史上服务不足的中央谷地区的计算资源需求,为西班牙裔服务中央谷机构内的广泛学生和研究人员提供研究和教育机会。 该项目由位于默塞德的加州大学(UCM)牵头,并与加州州立大学(CSU)-- CSU萨克拉门托、CSU Stanislaus和CSU Fresno合作。CENVAL-ARC的硬件设置包括图形处理单元(GPU)节点和中央处理单元(CPU)节点,每个节点都具有不同的处理器和内存规格配置。硬件无缝集成到UCM现有的Pinnacles高性能计算(HPC)集群中。该集群还具有高效的快速擦除和大数据存储功能,增强了科学驱动程序的数据存储和可访问性。CENVAL-ARC利用以太网和Omnipath网络,由XDMoD等开源工具支持,实现高效的集群管理和数据传输。它与科学DMZ的连接增强了与外部机构的数据交换,促进了合作研究。CENVAL-ARC的计算资源在RedHat Linux上运行,并带有Slurm调度器,可满足不同的研究任务。标准CPU节点和大内存CPU节点支持复杂系统建模和数值优化等活动,而GPU对于执行双精度浮点计算和管理人工智能和机器学习(AI/ML)工作负载不可或缺。CENVAL-ARC在推动整个中央谷的研究方面发挥着变革性作用。该项目支持每年举行的研究研讨会,这些研讨会吸引了数十名区域参与者,并增强了各个科学领域研究人员的能力。该奖项符合美国国家科学基金会(National Science Foundation)的愿景,即通过网络基础设施促进科学转型,促进转化研究和发现。该奖项反映了NSF的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
The Central Valley Advanced Research Computing (CENVAL-ARC) initiative aims to address the computational resource needs in the historically underserved Central Valley region of California, enhancing research and educational opportunities for a broad spectrum of students and researchers within Hispanic-Serving Central Valley institutions. The project is led by the University of California, Merced (UCM), in collaboration with California State Universities (CSUs) - CSU Sacramento, CSU Stanislaus, and CSU Fresno.CENVAL-ARC's hardware setup comprises Graphical Processing Unit (GPU) nodes and Central Processing Unit (CPU) nodes, each with distinct configurations of processor and memory specifications. The hardware seamlessly integrates into UCM's existing Pinnacles High Performance Computing (HPC) cluster. The cluster also features efficient fast scratch and large data storage, enhancing data storage and accessibility for science drivers. CENVAL-ARC utilizes Ethernet and Omnipath networks, supported by open-source tools like XDMoD, for efficient cluster management and data transfers. Its connection to a Science DMZ enhances data exchange with external institutions, fostering collaborative research. Running on RedHat Linux with the Slurm scheduler, CENVAL-ARC's computational resources accommodate diverse research tasks. Standard CPU nodes and large-memory CPU nodes support activities such as intricate systems modeling and numerical optimization, while GPUs are indispensable for executing double-precision floating-point calculations and managing Artificial Intelligence and Machine Learning (AI/ML) workloads.CENVAL-ARC plays a transformative role in advancing research throughout the Central Valley. The project supports yearly research symposia that engage dozens of regional participants and empower researchers across various scientific domains. This initiative aligns with the National Science Foundation's vision for catalyzing scientific transformation through cyberinfrastructure, fostering translational research and discovery.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.
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