High Performance Algorithms for Electronic Materials

9525885切利科夫斯基这项计算材料科学基金由材料研究部的材料理论项目和高级科学计算部门的新技术项目共同资助。一位首席研究员是计算材料科学家，而另一位是计算科学家。这项研究的一个主要目标是利用这两位研究人员的结合专业知识，在先进的平台上开发用于材料建模的计算机代码。这项研究的目标是开发充分利用高性能计算机创新的计算方法，以打开电子结构代码在复杂材料中的新应用。研究的重点将是通过高阶有限差分技术来解决电子结构问题的实空间方法。有限差分技术结合从头算赝势可以为复杂系统提供一种简单、准确和有效的方法。与更传统的平面波技术相比，有限差分技术的一些优点包括：在不损失精度的情况下，有限差分技术比平面波编码更容易实现，特别是对于并行实现；这些技术不需要在局部系统中使用超级单元。不存在细胞间的相互作用。充电系统可以在没有人工补偿背景的情况下直接处理。与扩展的基集相比，真空的复制是自然的，并且最小化；对于共享存储器体系结构，有限差分算法的速度比平面波技术至少快4-5倍。大规模并行平台的性能预期会显著提高；不需要进行快速傅立叶变换。全球通信被最小化。应用将集中在电子材料上，如大团簇、液体和无定形S固体。算法开发将集中于设计特征值问题的并行预条件，以及这些技术在各种并行平台上的实现。这笔计算材料科学补助金由材料研究部的材料理论计划和高级科学计算部门的新技术计划共同资助。一位首席研究员是计算材料科学家，而另一位是计算科学家。这项研究的一个主要目标是利用这两位研究人员的结合专业知识，在先进的平台上开发用于材料建模的计算机代码。这项研究的目标是开发充分利用高性能计算机创新的计算方法，以打开电子结构代码在复杂材料中的新应用。***

9525885 Chelikowsky This computational materials science grant is co-funded by the Materials Theory Program in the Division of Materials Research and the New Technologies Program in the Advanced Scientific Computing Division. One principal investigator is a computational materials scientist while the other is a computational scientist. A primary objective of this research is to develop computer codes for materials modeling on advanced platforms which utilize the combined expertise of these two researchers. The goal of the research is to develop computational methods which fully utilize innovations in high performance computers in order to open new applications of electronic structure codes to complex materials. The focus of the research will be on real space methods through higher order finite difference techniques to electronic structure problems. Finite difference techniques coupled with ab initio pseudopotentials can provide a simple, yet accurate and efficacious, approach to complex systems. A few of the advantages of finite difference techniques over more traditional plane wave techniques include: finite difference techniques are far easier to implement than plane wave codes with no loss of accuracy, especially for parallel implementations; these techniques to not require the use of supercells for localized systems. No cell-cell interactions are present. Charged systems can be handled directly without artificial compensating backgrounds. Replication of vacuum is natural and minimized compared to extended basis sets; finite difference algorithms result in a minimum factor of 4-5 gain in speed over plane wave techniques for shared memory architectures. Significantly better performance is expected for massively parallel platforms; no fast-Fourier transforms are required. Global communications are minimized. Applications will center on electronic materials such as large clusters, liquids and amorphous s olids. Algorithm development will concentrate on designing parallel preconditioners for the eigenvalue problem, as well as the implementation of these techniques on various paralllel platforms. %%% This computational materials science grant is co-funded by the Materials Theory Program in the Division of Materials Research and the New Technologies Program in the Advanced Scientific Computing Division. One principal investigator is a computational materials scientist while the other is a computational scientist. A primary objective of this research is to develop computer codes for materials modeling on advanced platforms which utilize the combined expertise of these two researchers. The goal of the research is to develop computational methods which fully utilize innovations in high performance computers in order to open new applications of electronic structure codes to complex materials. ***