High Performance Algorithms for Electronic Materials

电子材料的高性能算法

• 批准号: 9873664
• 负责人: James Chelikowsky
• 金额: $ 63万
• 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: 1999
• 资助国家: 美国
• 起止时间: 1999-02-15 至 2002-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9873664&HistoricalAwards=false
• 关键词: Performance; Algorithms; Electronic; Materials

9873664Chelikowsky and SaadThis is an interdisciplinary research grant funded jointly by the Divisions of Materials Research, of Advanced Computational Infrastructure and Research, and of Mathematical Sciences. The research involves algorithm development and implementation on massively parallel computers, and calculations of the properties of real materials using electronic structure theory. Materials of interest include amorphous materials, atomic clusters, liquids, glasses, extended defects, reconstructed point defects, non-ideal interfaces, etc. The recent development of high performance and novel architecture computers is creating new opportunities for the application of sophisticated electronic structure techniques to study these materials. Another two or more orders of magnitude improvement in speed, which is likely in the near future, will enable us to step beyond the current computational limits in materials science and reach an exciting era of understanding and discovery in real materials. These gains are not achieved by progress in hardware alone, but may depend more on innovations in algorithms. Developing new algorithms in multidisciplinary research requires an understanding of the different disciplines involved by the collaborating members, in this case a close collaboration between computer scientists and physical scientists.We will use real space algorithms (based on ab initio pseudopotentials) to predict the dielectric properties of quantum dots and nanostructured matter. We will apply a variety of methodologies to this problem including quasiparticle energies determined from density functional theory. We will consider quantum dots up to several thousand atoms in size. This will allow us to examine the transition from "atomic" to "crystalline" in terms of optical and dielectric response functions. Also, we will examine the structural properties of quantum dots, and extrinsic properties such as photoluminescence. We intend to continue our ongoing activities in other areas such as defects in solids, the structure and electronic properties of semiconductor liquids, and crystal growth.We will continue to examine new and efficient algorithms for computing eigenvectors and eigenvalues, with an emphasis on methods for computing a large number of eigenvectors. These algorithms include, but are not limited to, spectrum slicing via polynomial iterations and preconditioning techniques. In addition, we will examine new algorithms which avoid the computation of eigenvalues and eigenvectors altogether. One of these methods will be based on utilizing the Lanczos procedure.%%% This is an interdisciplinary research grant funded jointly by the Divisions of Materials Research, of Advanced Computational Infrastructure and Research, and of Mathematical Sciences. The research involves algorithm development and implementation on massively parallel computers, and calculations of the properties of real materials using electronic structure theory. Materials of interest include amorphous materials, atomic clusters, liquids, glasses, extended defects, reconstructed point defects, non-ideal interfaces, etc. The recent development of high performance and novel architecture computers is creating new opportunities for the application of sophisticated electronic structure techniques to study these materials. Another two or more orders of magnitude improvement in speed, which is likely in the near future, will enable us to step beyond the current computational limits in materials science and reach an exciting era of understanding and discovery in real materials. These gains are not achieved by progress in hardware alone, but may depend more on innovations in algorithms. Developing new algorithms in multidisciplinary research requires an understanding of the different disciplines involved by the collaborating members, in this case a close collaboration between computer scientists and physical scientists.***

9873664Chelikowsky和Saadthis是一项跨学科研究赠款，由材料研究，先进的计算基础设施和研究以及数学科学的划分共同资助。 该研究涉及对大量平行计算机的算法开发和实施，以及使用电子结构理论计算真实材料的性质。 感兴趣的材料包括无定形材料，原子簇，液体，眼镜，扩展缺陷，重建点缺陷，非理想接口等。高性能和新型建筑计算机的最新开发为精致电子结构技术的应用创造了新的机会研究这些材料。 在不久的将来，速度的另外两个或多个数量级的提高将使我们能够超越材料科学的当前计算限制，并在真实材料中达到令人兴奋的理解和发现时代。 这些收益不是仅通过硬件的进度来实现的，而是更多地取决于算法中的创新。 在多学科研究中开发新算法需要了解协作成员所涉及的不同学科，在这种情况下，计算机科学家和物理科学家之间进行了密切的合作。我们将使用真实的空间算法（基于从头开始的伪电势）来预测介电属性量子点和纳米结构物质。 我们将在此问题上应用多种方法，包括根据密度功能理论确定的准粒子能量。 我们将考虑量子大小的量子点。 这将使我们能够从光学和介电响应函数方面检查从“原子”到“晶体”的过渡。 此外，我们将检查量子点的结构特性以及诸如光致发光之类的外部特性。 我们打算在其他领域继续进行正在进行的活动，例如固体缺陷，半导体液体的结构和电子特性以及晶体生长。我们将继续研究用于计算特征向量和特征值的新且有效的算法，并重点介绍了用于方法的方法。计算大量特征向量。 这些算法包括但不限于通过多项式迭代和预处理技术进行频谱切片。 此外，我们将检查新的算法，这些算法避免了特征值和特征向量的计算。 这些方法之一将基于利用兰开斯程序。%% %%这是由材料研究，先进的计算基础设施和研究以及数学科学的分区共同资助的跨学科研究赠款。 该研究涉及对大量平行计算机的算法开发和实施，以及使用电子结构理论计算真实材料的性质。 感兴趣的材料包括无定形材料，原子簇，液体，眼镜，扩展缺陷，重建点缺陷，非理想接口等。高性能和新型建筑计算机的最新开发为精致电子结构技术的应用创造了新的机会研究这些材料。 在不久的将来，速度的另外两个或多个数量级的提高将使我们能够超越材料科学的当前计算限制，并在真实材料中达到令人兴奋的理解和发现时代。 这些收益不是仅通过硬件的进度来实现的，而是更多地取决于算法中的创新。 在多学科研究中开发新的算法需要了解合作成员所涉及的不同学科，在这种情况下，计算机科学家和物理科学家之间进行了密切的合作。***