EAGER: Resilient, Energy Efficient HPC System Configuration

EAGER：弹性、节能的 HPC 系统配置

• 批准号: 1349521
• 负责人: Daniel Reed
• 金额: $ 29.88万
• 依托单位: University of Iowa
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-10-01 至 2016-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1349521&HistoricalAwards=false
• 关键词: EAGER; Resilient; Energy; Efficient; HPC

High-performance computing systems (supercomputers) continue to grow in size and complexity. Today's leading edge systems contain tens of thousands of server nodes, and proposed, next-generation systems are likely to contain hundreds of thousands of nodes. At this scale, maintaining system operation when hardware components may fail every few minutes or hours is increasingly difficult. Increasing system sizes bring a complementary challenge surrounding energy availability and costs, with projected systems expected to consume ten or more megawatts of power. For future high-performance computing systems to be useable and cost effective, we must develop new design methodologies and operating principles that embody the two important realities of large-scale systems: frequent hardware component failures are a part of normal operation and (b) energy consumption and power costs must be managed as carefully as performance and resilience. As part of this research, the principal investigator will apply new ideas from commercial cloud computing to HPC systems, focusing on reliability and energy efficiency. This includes models of high-performance computing system design based on right-sizing hardware building blocks to balance operating costs for component replacement and repair against capital costs for over-provisioning, and incorporation of energy costs and constraints into scheduling systems and resource allocations, making computing costs visible to researchers. The deployment of very large-scale computing systems, which target science, engineering and defense problems of critical national interest, is currently limited by both system reliability and energy consumption. New design and operating approaches for reliability and energy management can both reduce costs and increase access, allowing computer companies to design larger systems, research institutions to deploy systems more widely, and researchers to better manage computational resources.

高性能计算系统（超级计算机）的规模和复杂性持续增长。 当今的前沿系统包含数万个服务器节点，而拟议的下一代系统可能包含数十万个节点。在这种规模下，当硬件组件可能每隔几分钟或几小时就出现故障时，维护系统操作变得越来越困难。随着系统规模的不断扩大，围绕能源可用性和成本的挑战也随之而来，预计系统将消耗10兆瓦或更多的电力。对于未来的高性能计算系统是可用的和具有成本效益的，我们必须开发新的设计方法和操作原则，体现了两个重要的现实大规模系统：频繁的硬件组件故障是正常操作的一部分和（B）能源消耗和电力成本必须小心管理的性能和弹性。 作为这项研究的一部分，首席研究员将把商业云计算的新想法应用到HPC系统中，重点关注可靠性和能源效率。这包括高性能计算系统设计的模型，其基于适当大小的硬件构建块，以平衡组件更换和维修的运营成本与过度配置的资本成本，并将能源成本和约束纳入调度系统和资源分配，使计算成本对研究人员可见。部署超大规模的计算系统，其目标是关键的国家利益的科学，工程和国防问题，目前受到系统可靠性和能源消耗的限制。 可靠性和能源管理的新设计和操作方法既可以降低成本，又可以增加访问，使计算机公司能够设计更大的系统，研究机构能够更广泛地部署系统，研究人员能够更好地管理计算资源。