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: $ 100万
• 依托单位: University of California - Merced
• 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: 2024-06-01 至 2026-05-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2346744&HistoricalAwards=false
• 关键词: CC; Regional; Computing; CENVAL; ARC

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.

中央山谷高级研究计算（CENVAL-ARC）倡议旨在满足历史悠久的加利福尼亚州中央山谷地区的计算资源需求，从而增强了西班牙裔服务中心谷机构中广泛的学生和研究人员的研究和教育机会。 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.硬件无缝集成到UCM现有的Pinnacles高性能计算（HPC）群集中。该集群还具有有效的快速刮擦和大型数据存储，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，并由XDMOD（例如XDMOD）的开源工具支持，以实现有效的集群管理和数据传输。它与科学DMZ的联系可以通过外部机构增强数据交换，从而促进了协作研究。 Cenval-Arc的计算资源在Redhat Linux上使用Slurm调度程序运行，可容纳多种研究任务。标准的CPU节点和大型内存CPU节点支持诸如复杂的系统建模和数值优化等活动，而GPU对于执行双精确的浮点计算以及管理人工智能和机器学习（AI/ML）的工作是必不可少的。该项目支持年度研究研讨会，这些研讨会吸引了数十名区域参与者，并赋予了各个科学领域的研究人员的能力。该倡议与国家科学基金会通过网络基础结构催化科学转型的愿景相吻合，促进转化研究和发现。该奖项反映了NSF的法定使命，并被认为是值得通过基金会的知识分子优点和更广泛影响的评估标准来通过评估来进行评估的。