II-New: Infrastructure for Energy-Aware High Performance Computing (HPC) and Data Analytics on Heterogeneous Systems

II-新：异构系统上的能源感知高性能计算 (HPC) 和数据分析基础设施

• 批准号: 1513120
• 负责人: Gagan Agrawal
• 金额: $ 89.87万
• 依托单位: Ohio State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-07-01 至 2019-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1513120&HistoricalAwards=false
• 关键词: II; New; Infrastructure; Energy; Aware

The project builds a comprehensive research infrastructure to meet the needs of a large research team at the Ohio State University allowing experimental research in a number of computer science areas including high performance computing, data analytics, storage, and virtualization. The project will lead to significant advances in many computer science areas, and its impact will be enhanced through active dissemination of software from the investigators. The project will contribute substantially to human resource development, education in computer science increasing diversity in related areas. More specifically, researchers will acquire and deploy an infrastructure that includes three types of accelerators, conventional as well as energy-efficient nodes, large main memory including Solid State Drive (SSD) on a subset of nodes, and hardware for fine-grained power measurements. The requested resources will allow experimentation with a number of popular or emerging cluster configurations that address needs of a variety of compute-intensive and/or data-intensive workloads. Such an internally hosted and reconfigurable cluster will also allow power measurements, voltage margin reduction experiments, and failure detection and recovery studies in the presence of physical failures - none of which is typically feasible at national supercomputing and cloud infrastructures. The infrastructure is motivated by the multiple paradigm shifts that high performance computing is presently undergoing. They include increasing use of accelerators or coprocessors, increased criticality of energy and resilience beyond performance, synergy with data analytic applications, and popularity of massive main memory or SSD technologies. These trends provide opportunities and challenges for a variety of scientific, medical, and enterprise applications to be explored in this project.

该项目建立了一个全面的研究基础设施，以满足俄亥俄州立大学大型研究团队的需求，允许在多个计算机科学领域进行实验研究，包括高性能计算、数据分析、存储和虚拟化。该项目将在许多计算机科学领域带来重大进展，并且通过研究人员积极传播软件，其影响力将得到增强。该项目将为人力资源开发、计算机科学教育以及增加相关领域的多样性做出重大贡献。 更具体地说，研究人员将获取并部署一个基础设施，其中包括三种类型的加速器、传统节点和节能节点、大型主存储器（包括节点子集上的固态硬盘（SSD））以及用于细粒度功率测量的硬件。所请求的资源将允许对许多流行或新兴的集群配置进行实验，以满足各种计算密集型和/或数据密集型工作负载的需求。 这种内部托管和可重新配置的集群还将允许在出现物理故障时进行功率测量、电压裕度降低实验以及故障检测和恢复研究——这些在国家超级计算和云基础设施中通常是不可行的。高性能计算目前正在经历的多重范式转变推动了基础设施的发展。其中包括加速器或协处理器的使用增加、能源和弹性重要性的提高、与数据分析应用程序的协同以及海量主内存或 SSD 技术的普及。这些趋势为本项目中探索的各种科学、医学和企业应用提供了机遇和挑战。