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：美国国家科学基金会授予新不伦瑞克的罗格斯大学的这一奖项是为了表彰一种新的计算机体系结构的开发，该体系结构具有多层互连的存储器，优化了对来自第一性原理计算的强关联材料的模拟。强关联材料具有变革的潜力，这是两个例子：热电材料，它可以高效地从废热中产生电力；以及超导体，它有可能产生更高的临界温度、场和电流，它可以通过降低传输损耗来彻底改变电网。使用计算方法加快发现具有理想性质的材料的速度是凝聚态科学中最大的挑战之一。具有强关联电子系统的材料特别难模拟，因为它们的物理性质不能用以平均势运动的独立粒子系统来准确表示，因此需要新的方法和强大的超级计算机来进行理论描述。非技术描述：美国国家科学基金会授予新不伦瑞克的罗格斯大学的这一奖项是为了表彰一种新的计算机体系结构的开发，该体系结构针对第一性原理计算中的新材料进行了优化。新的计算机将使材料合成小组和计算物理学家之间的合作成为可能。该仪器将推动计算机科学研究，将被用作罗格斯大学计算科学和工程教学的资源，并将作为国家网络基础设施中未来超级计算机的原型。