EAGER: A Data-Intensive Instrument for Strongly Correlated System Material Design

EAGER：用于强相关系统材料设计的数据密集型工具

• 批准号: 1342921
• 负责人: Gabriel Kotliar
• 金额: $ 29.72万
• 依托单位: Rutgers University New Brunswick
• 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: 2013-09-01 至 2015-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1342921&HistoricalAwards=false
• 关键词: EAGER; Data; Intensive; Instrument; Strongly

Technical Description:This award from the National Science Foundation to Rutgers University in New Brunswick is for the development of a new computer architecture with multiple levels of interconnected memory, optimized for the simulation of strongly correlated materials from first principles calculations. Strongly correlated materials have the potential to be transformative, two examples: thermoelectric materials, which can generate electricity from waste heat with high efficiency; and, superconductors with potential for higher critical temperatures, fields, and currents, which can revolutionize the electric grid by reducing transmission losses. The use of computational methods to accelerate the pace of discovery of materials with desirable properties is one of the greatest challenges in condensed matter science. Materials with strongly correlated electron systems are particularly difficult to simulat because their physical properties cannot be accurately represented in terms of a system of independent particles moving in an average potential, thus requiring new methodologies and powerful supercomputers for their theoretical description. Non-Technical Description:This award from the National Science Foundation to Rutgers University in New Brunswick is for the development of a new computer architecture optimized for the dsicovery of new materials from first principles calculations. The new computer will enable collaborations between material synthesis groups and computational physicists. The instrument will drive computer science research, will be used as a resource for teaching computational science and engineering at Rutgers, and will serve as a prototype for a future supercomputer in the national cyber-infrastructure.

技术描述：新不伦瑞克省的国家科学基金会（National Science Foundation）到罗格斯大学（Rutgers University）的奖项是为了开发具有多个互连内存的新计算机架构，优化了用于模拟第一原理计算中强相关的材料。 密切相关的材料具有变革性的潜力，这是两个例子：热电材料，可以以高效率从废热中产生电力；并且，具有较高临界温度，田间和电流潜力的超导体，可以通过减少传输损失来彻底改变电网。 使用计算方法加速具有理想特性的材料的速度是凝结物质科学的最大挑战之一。 具有密切相关的电子系统的材料特别难以模拟，因为其物理性能不能准确地以平均电势移动的独立粒子系统来准确表示，因此需要新的方法论和强大的超级计算机来进行理论描述。 非技术描述：New Brunswick的国家科学基金会（National Science Foundation）的该奖项是为开发新的计算机体系结构，以优化用于从第一原理计算中新材料进行优化的新计算机架构。 新计算机将实现材料合成组与计算物理学家之间的合作。 该仪器将推动计算机科学研究，将用作罗格斯（Rutgers）教授计算科学和工程学的资源，并将作为国家网络基础设施中未来超级计算机的原型。