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，允许在许多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。该项目将导致许多计算机科学领域的重大进展，并通过从研究人员中积极传播软件来增强其影响。该项目将为人力资源开发，计算机科学的教育做出重大贡献，从而增加了相关领域的多样性。 更具体地说，研究人员将获取和部署包括三种类型的加速器，常规和节能节点，包括固态驱动器（SSD）的大型主机（SSD）的基础架构，以及用于细粒电源测量的硬件。请求的资源将允许进行许多流行或新兴的集群配置，以解决各种计算密集型和/或数据密集型工作负载的需求。 这样的内部托管和可重构群集还将允许在存在物理失败的情况下进行功率测量，降压实验以及故障检测和恢复研究 - 在国家超级计算和云基础架构中，通常不可行。基础架构是由高性能计算目前正在进行的多个范式变化所激发的。其中包括增加加速器或协助程序的使用，超越性能的能量和弹性的提高，与数据分析应用程序的协同作用以及大量主内存或SSD技术的普及。这些趋势为在该项目中探索的各种科学，医学和企业应用程序提供了机会和挑战。