High Performance Algorithms for Electronic Materials

电子材料的高性能算法

• 批准号: 0130395
• 负责人: James Chelikowsky
• 金额: $ 42万
• 依托单位: University of Minnesota-Twin Cities
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-03-01 至 2006-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0130395&HistoricalAwards=false
• 关键词: Performance; Algorithms; Electronic; Materials

This grant is supported by the Divisions of Materials Research and Advanced Computational Infrastructure and Research. The research is in the area of computational materials research and involves a collaborative effort in both materials research and computational science. The overall goal of the research is to exploit high performance computers for solving large scale and complex problems that arise in modeling real materials. The research will center on electronic materials with extended and point defects, and non-ideal interfaces and in the form of amorphous solids, atomic clusters, liquids, and glasses.The continuing evolution of high performance computers is creating new opportunities for the application of sophisticated electronic structure techniques to the study of technologically important materials. A few orders of magnitude improvement in speed are feasible in the near future and will enable us to step beyond the current computational limits in materials science and achieve an unprecedented understanding of the physical and electronic properties of materials. Such achievements are not made by progress in computer hardware alone, but depend more so on innovations in algorithms. The development of new algorithms in multidisciplinary research requires an understanding and appreciation of the different disciplines involved by the collaborating members. Based on prior experience of this group, progress can be best made by a close collaboration between computer scientists and materials scientists. Thus, algorithms will be developed, implemented and applied to a number of materials problems.Applications will include: localized systems, atomic clusters and quantum dots; liquids and disordered semiconductors; dilute magnetic semiconductors. Algorithms to be developed include: out-of-core methods; special methods for computing eigenvectors and eigenvalues; avoiding eigenvectors and eigenvalues.%%% This grant is supported by the Divisions of Materials Research and Advanced Computational Infrastructure and Research. The research is in the area of computational materials research and involves a collaborative effort in both materials research and computational science. The overall goal of the research is to exploit high performance computers for solving large scale and complex problems that arise in modeling real materials. The research will center on electronic materials with extended and point defects, and non-ideal interfaces and in the form of amorphous solids, atomic clusters, liquids, and glasses.The continuing evolution of high performance computers is creating new opportunities for the application of sophisticated electronic structure techniques to the study of technologically important materials. A few orders of magnitude improvement in speed are feasible in the near future and will enable us to step beyond the current computational limits in materials science and achieve an unprecedented understanding of the physical and electronic properties of materials. Such achievements are not made by progress in computer hardware alone, but depend more so on innovations in algorithms. The development of new algorithms in multidisciplinary research requires an understanding and appreciation of the different disciplines involved by the collaborating members. Based on prior experience of this group, progress can be best made by a close collaboration between computer scientists and materials scientists. Thus, algorithms will be developed, implemented and applied to a number of materials problems.***

这笔赠款得到了材料研究和高级计算基础设施与研究部门的支持。这项研究是在计算材料研究领域，涉及材料研究和计算科学的合作努力。这项研究的总体目标是开发高性能计算机来解决在模拟真实材料时出现的大规模和复杂问题。这项研究将集中在具有扩展缺陷和点缺陷以及非理想界面的电子材料，以及非晶态固体、原子团簇、液体和玻璃的形式。高性能计算机的不断发展为复杂的电子结构技术在重要技术材料研究中的应用创造了新的机会。在不久的将来，速度上的几个数量级的提高是可行的，将使我们能够超越材料科学目前的计算限制，实现对材料物理和电子性质的前所未有的理解。这样的成就不是仅仅依靠计算机硬件的进步，而是更多地依赖于算法的创新。在多学科研究中开发新的算法需要理解和欣赏合作成员所涉及的不同学科。根据这一小组以前的经验，计算机科学家和材料科学家之间的密切合作可能是取得进展的最佳途径。因此，算法将被开发、实施并应用于许多材料问题。应用将包括：定域系统、原子团簇和量子点；液体和无序半导体；稀磁半导体。将要开发的算法包括：核外方法；计算特征向量和特征值的特殊方法；避免特征向量和特征值。%这笔拨款由材料研究和高级计算基础设施和研究部门支持。这项研究是在计算材料研究领域，涉及材料研究和计算科学的合作努力。这项研究的总体目标是开发高性能计算机来解决在模拟真实材料时出现的大规模和复杂问题。这项研究将集中在具有扩展缺陷和点缺陷以及非理想界面的电子材料，以及非晶态固体、原子团簇、液体和玻璃的形式。高性能计算机的不断发展为复杂的电子结构技术在重要技术材料研究中的应用创造了新的机会。在不久的将来，速度上的几个数量级的提高是可行的，将使我们能够超越材料科学目前的计算限制，实现对材料物理和电子性质的前所未有的理解。这样的成就不是仅仅依靠计算机硬件的进步，而是更多地依赖于算法的创新。在多学科研究中开发新的算法需要理解和欣赏合作成员所涉及的不同学科。根据这一小组以前的经验，计算机科学家和材料科学家之间的密切合作可能是取得进展的最佳途径。因此，算法将被开发、实施并应用于许多材料问题。*