MRI: Acquisition of High Performance Hybrid Computing Cluster to Advance Cyber-Enabled Science and Education at Penn State

MRI：收购高性能混合计算集群以推进宾夕法尼亚州立大学的网络科学和教育

• 批准号: 1626251
• 负责人: Cindy Gulis
• 金额: $ 92.07万
• 依托单位: Pennsylvania State Univ University Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-10-01 至 2019-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1626251&HistoricalAwards=false
• 关键词: MRI; Acquisition; Performance; Hybrid; Computing

Computers are now becoming the driving forces for ground-breaking discoveries and are transforming the science and education in this new data-driven era. The Cyber-Laboratory for Astronomy, Materials and Physics (CyberLAMP) at Penn State will put together a cutting-edge supercomputer cluster that includes both traditional central processing units (CPUs) and the latest hardware accelerators, such as graphics processing units (GPUs), to advance interdisciplinary research and education in cyberscience. Astronomers and physicists will use this high-performance hybrid computer to analyze data from revolutionary surveys and experiments and to perform state-of-the-art simulations to unravel of the origin of our Universe. Material scientists will run realistic, atomistic-scale, simulations to guide the design and development of next-generation complex materials. Computer scientists will analyze these science applications to inform the design of future computer architectures. These advances in both data analysis and simulations will enable the CyberLAMP members to shed new light on topics prioritized by national strategic plans, such as National Research Council's 2010 Decadal Survey for astronomy and astrophysics to search for habitable planets and to understand the fundamental physics of the cosmos and the White House's Materials Genome Initiative to expedite development of new materials. Furthermore, the CyberLAMP team will employ this cluster to enhance a wide range of outreach programs including: computational education to numerous students at The Pennsylvania State University, including its Commonwealth campuses; summer workshops for researchers and high-school teachers; and partnerships with industry to advance materials research and the co-design of future hardware-software systems. By expediting exploratory data analysis and simulations and catalyzing cross-disciplinary collaboration in developing and prototyping algorithms, the new hybrid cluster will enable the CyberLAMP team to deliver transformative breakthroughs in a number of key research areas. This includes state-of-the-art astrostatistics and astroinformatics for data analysis for world-leading surveys in cosmology and exoplanets, as well as sophisticated simulations to directly address the nature of dark matter and dark energy, and the formation of planetary systems; an order-of-magnitude increase of speed for reconstruction algorithms for the most ambitious astrophysical experiments probing fundamental physics, which will enlarge the discovery space for cosmic sources of neutrinos, gravity waves, and multi-messenger emitters, as well as heighten sensitivity to the neutrino mass hierarchy; dramatic advances in nanosecond-scale fully reactive molecular dynamics simulations for the development of next-generation complex materials; and novel insights for designing the next-generation of hardware accelerators in hybrid systems, highly parallel algorithms and software interfaces which could revolutionize the way hardware accelerators are used by data-intensive applications.

现在，计算机正在成为开创性发现的驱动力，并在这个新的数据驱动时代改变了科学和教育。宾夕法尼亚州的天文学，材料和物理学（网络灯）的网络定位将汇总一个尖端的超级计算机群集，其中包括传统的中央加工单元（CPU）和最新的硬件加速器，例如图形处理单元（GPUS），，GPUS（GPUS），，GPUS）促进网络科学领域的跨学科研究和教育。天文学家和物理学家将使用这种高性能混合计算机来分析革命性调查和实验的数据，并执行最先进的模拟，以解散我们宇宙的起源。 物质科学家将运行现实，原子规模的模拟，以指导下一代复合物材料的设计和开发。计算机科学家将分析这些科学应用程序，以告知未来计算机架构的设计。数据分析和仿真中的这些进步将使网络灯成员能够为国家战略计划优先考虑主题，例如国家研究委员会2010年的《年代际天文学和天体物理学调查》，以寻求可居住的行星，并了解该行星的基本物理。宇宙和白宫材料基因组倡议，以加快新材料的开发。此外，网络灯光团队将采用该集群来增强广泛的外展计划，包括：为宾夕法尼亚州立大学的众多学生，包括其英联邦校园的计算教育；研究人员和高中老师的夏季讲习班；以及与行业的合作伙伴关系，以推进材料研究和未来硬件软件系统的共同设计。通过加快探索性数据分析和模拟，并在开发和原型制定算法中催化跨学科的合作，新的混合群集将使网络灯团队能够在许多关键研究领域提供变革性的突破。 这包括用于宇宙学和系外行星中世界领先调查的数据分析的最先进的天文学和星空信息学，以及直接解决暗物质和暗能量的本质以及行星系统的形成；重建算法速度的速度提高，用于探测基本物理学的最雄心勃勃的天体物理实验，这将扩大中微子，重力波和多电器剂量的宇宙来源的发现空间，以及对高度敏感的敏感性中微子质量等级；纳秒尺度的完全反应性分子动力学模拟的急剧进步，以开发下一代复合物材料；以及设计混合系统中硬件加速器的下一代，高度平行的算法和软件接口的新颖见解，这些算法和软件接口可能会彻底改变数据密集型应用程序使用硬件加速器的方式。