MRI Collaborative Consortium: Acquisition of a Shared Supercomputer by the Rocky Mountain Advanced Computing Consortium

MRI 协作联盟：落基山高级计算联盟收购共享超级计算机

• 批准号: 1532235
• 负责人: Howard Siegel
• 金额: $ 70万
• 依托单位: Colorado 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: 2015-09-01 至 2018-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1532235&HistoricalAwards=false
• 关键词: MRI; Collaborative; Consortium; Acquisition; Shared

A cluster supercomputer is deployed by the University of Colorado Boulder (CU-Boulder) and Colorado State University (CSU) for the Rocky Mountain Advanced Computing Consortium (RMACC). This high-performance computing (HPC) system supports multiple research groups across the Rocky Mountain region in fields including astrophysics, bioinformatics, chemistry, computational fluid dynamics, earth system science, life science, material science, physics, and social sciences with advanced computing capabilities. It also provides a platform to investigate and address the impact of many-core processors on the applications that support research in these fields. The system integrates nodes populated with Intel's conventional multicore Xeon processors and Many-Integrated-Core (MIC) 'Knights Landing' Phi processors interconnected by Intel's new Omni-Path networking technology. Users of the new HPC system have access to existing data management services including data storage, data sharing, metadata consulting, and data publishing, leveraging the NSF-funded high-performance networking infrastructure and long term storage system, as well as additional cyberinfrastructure, at CU-Boulder and CSU. The many-core feature of this HPC system enhances graduate and undergraduate students' education and training as they develop, deploy, test, and run optimized applications for next generation many-core architectures. Training for researchers and students is provided through workshops appropriate for introducing diverse audiences to the efficient and effective use of HPC systems, the challenges of vectorization for single core performance, shared memory parallelism, and issues of data management. Additionally, advanced workshops on large-scale distributed computing, high-throughput computing, and data-intensive computing are offered during the year and at the annual RMACC student-centric HPC Symposium. The Symposium brings together hundreds of students, researchers, and professionals from universities, national laboratories and industry to exchange ideas and best practices in all areas of cyberinfrastructure. For-credit HPC classes will be delivered for online participation, educating the next generation of computational scientists in state-of-the-art computational techniques.

集群超级计算机由科罗拉多大学博尔德分校（CU-Boulder）和科罗拉多州立大学（CSU）为落基山高级计算联盟（RMACC）部署。这个高性能计算（HPC）系统支持横跨落基山脉地区的多个研究小组，这些研究领域包括天体物理学、生物信息学、化学、计算流体动力学、地球系统科学、生命科学、材料科学、物理学和具有先进计算能力的社会科学。它还提供了一个平台来调查和解决多核处理器对支持这些领域研究的应用程序的影响。该系统集成了由英特尔传统的多核至强处理器和多核（MIC）“Knights Landing”Phi处理器组成的节点，这些处理器通过英特尔新的Omni-Path网络技术相互连接。新HPC系统的用户可以访问现有的数据管理服务，包括数据存储、数据共享、元数据咨询和数据发布，利用美国国家科学基金会资助的高性能网络基础设施和长期存储系统，以及科罗拉多大学博尔德分校和科罗拉多州立大学的额外网络基础设施。这种高性能计算系统的多核特性增强了研究生和本科生的教育和培训，因为他们为下一代多核架构开发、部署、测试和运行优化的应用程序。通过适当的研讨会为研究人员和学生提供培训，向不同的受众介绍高性能计算系统的高效和有效使用，单核性能的向量化挑战，共享内存并行性和数据管理问题。此外，在年度和RMACC以学生为中心的HPC研讨会上，还提供了关于大规模分布式计算、高吞吐量计算和数据密集型计算的高级讲习班。研讨会汇集了来自大学、国家实验室和工业界的数百名学生、研究人员和专业人士，在网络基础设施的各个领域交流思想和最佳实践。学分HPC课程将提供在线参与，教育下一代计算科学家的最先进的计算技术。