MRI: Acquisition of the Kentucky Research Informatics Composable Cloud (KyRICC)

MRI：收购肯塔基州研究信息学可组合云 (KyRICC)

• 批准号: 2216140
• 负责人: Jeffery Talbert
• 金额: $ 113.66万
• 依托单位: University of Kentucky Research Foundation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-10-01 至 2023-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2216140&HistoricalAwards=false
• 关键词: MRI; Acquisition; Kentucky; Research; Informatics

Scientific discovery today is driven by computation and data-intensive research that exploits the growing amounts of available data. However, the wide variety and size of emerging datasets often make analysis challenging on current high-performance computing (HPC) infrastructures because system configurations cannot be customized to process the data efficiently. This project will acquire and deploy a dynamically composable computer infrastructure called the Kentucky Research Informatics Composable Cloud (KyRICC). This KyRICC architecture will support complex data analysis pipelines with highly heterogeneous hardware requirements not currently supported by current HPC infrastructures. As a result, this project will enable and support a wide range of new research activities. KyRICC will be used by hundreds of University of Kentucky (UK) researchers (faculty, staff, and students) and by other computational research collaborators at institutions across the region including Centre College, Morehead State University, Eastern Kentucky University, University of Louisville, Northern Kentucky University, and Kentucky State University. As a leading-edge system, KyRICC and the exciting projects it makes possible will help recruit students, including students from groups underrepresented in STEM, to computational research. The system will also enhance the research training of many undergraduates, graduate students, and postdocs in Kentucky colleges and universities.The KyRICC architecture will support complex data analysis pipelines with highly heterogeneous hardware requirements across individual data analysis steps. Specifically, KyRICC will integrate four subsystems that will enable dynamically composable cloud infrastructure: (1) A cluster of peripheral-composable compute nodes, allowing for up to 10’s of GPUs and 10’s of TB of main memory on a single node. Groups of nodes can be dynamically allocated to allow the training and inference of very large deep learning models and datasets; (2) A next-generation high-speed NVMe-based storage cluster capable of efficiently serving large volumes of data to multi-GPU nodes. Unlike traditional clustered storage systems, this composable filesystem allows the partitioning of storage on the project-level, allowing us to isolate data and better manage system performance; (3) A Peta-scale storage system provided by UK’s current research storage infrastructure, providing a total of 2.2 PB of storage; and (4) An innovative workload management system for dynamic infrastructure composition, workload profiling, model and infrastructure tuning, supporting common pipelines and machine and deep learning models through templated projects. KyRICC will be a regional computational resource and will also be made available to the broader national computational research infrastructure through the NSF-supported ACCESS projects. Areas of expected breakthroughs in KyRICC-enabled research include deep learning and computer vision; natural language processing and multimodal embedding; computational modeling and simulation with data analytics; and omics analysis and systemic integration.This project is jointly funded by the Major Research Instrumentation (MRI) program, the Established Program to Stimulate Competitive Research (EPSCoR), and the Computer & Information Science & Engineering (CISE) Directorate.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.

当今的科学发现是由计算和数据密集型研究驱动的，这些研究利用了越来越多的可用数据。然而，新兴数据集的多样性和规模往往使当前高性能计算 (HPC) 基础设施的分析面临挑战，因为系统配置无法进行调整。该项目将获取并部署一个称为肯塔基州研究信息学可组合云 (KyRICC) 的动态可组合计算机基础设施。该架构将支持具有高度异构硬件要求的复杂数据分析管道。目前由当前 HPC 基础设施支持，因此，该项目将支持和支持广泛的新研究活动，将由数百名肯塔基大学（英国）研究人员（教职员工和学生）和其他人员使用。该地区各机构的计算研究合作者包括中心学院、莫尔黑德州立大学、东肯塔基大学、路易斯维尔大学、北肯塔基大学和肯塔基州立大学。作为一个领先的系统，KyRICC 及其所实现的令人兴奋的项目将提供帮助。招收学生，包括团体学生该系统还将加强肯塔基州学院和大学的许多本科生、研究生和博士后的研究培训。KyRICC 架构将支持复杂的数据分析管道，跨各个数据分析步骤具有高度异构的硬件要求。具体来说，KyRICC 将集成四个子系统，以实现动态可组合的云基础设施：(1) 外围可组合计算节点集群，允许最多 10 个 GPU 和 10 个 GPU单个节点上 TB 的主内存可以动态分配节点组，以允许非常大的深度学习模型和数据集的训练和推理；（2）能够高效服务的下一代高速 NVMe 存储集群； (3) 提供的Peta级存储系统英国当前的研究存储基础设施，总共提供 2.2 PB 的存储空间；(4) 创新的工作负载管理系统，用于动态基础设施组成、工作负载分析、模型和基础设施调整，通过模板项目支持常见管道以及机器和深度学习模型。 KyRICC 将成为一个区域性计算资源，并将通过 NSF 支持的 ACCESS 项目提供给更广泛的国家计算研究基础设施。 KyRICC 支持的研究预计将取得突破，包括深度学习和计算机视觉；处理和多模态嵌入；数据分析的计算建模和模拟；以及组学分析和系统集成。该项目由主要研究仪器（MRI）计划、刺激竞争研究既定计划（EPSCoR）和计算机与信息科学与工程 (CISE) 理事会。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。