ITR/AP(DMR): Billion-Atom Multiscale Simulations of Nanosystems on a Grid

ITR/AP(DMR)：网格上纳米系统的十亿原子多尺度模拟

• 批准号: 0313480
• 负责人: Priya Vashishta
• 金额: $ 41.78万
• 依托单位: University of Southern California
• 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: 2002-09-01 至 2005-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0313480&HistoricalAwards=false
• 关键词: ITR; AP; DMR; Billion; Atom

This award is the result of a proposal submitted to the Information Technology Research initiative. The goal of the research is to develop a scalable software infrastructure for large multiscale simulations on a Grid of geographically distributed, massively parallel supercomputers, as well as on future Petaflop computers.The multiscale simulation approach will combine, in a single Grid software, finite element (FE) calculation, the coarse-grained molecular dynamics (CGMD), molecular dynamics (MD) simulation, and quantum mechanical (QM) calculation based on the density functional theory (DFT). Continuum mechanics calculation based on the FE method will be performed with constitutive relations derived from the CGMD method in conjunction with MD simulations, which in turn will embed QM algorithm described by the DFT. The following will be developed: (1) Grid-based FE/CGMD/MD/QM algorithms based on space-time multiresolution algorithms implemented with hierarchical decomposition on parallel/distributed computers for scalability and constrained-dynamics-based hybridization for seamless coupling of the hybrid simulation componets; (2) Space-time partitioned multiscale simulation combined with kinetic Monte Carlo (KMC) and parallel replica methods to couple disparate length and time scales; (3) Grid-computation tools including adaptive load balancing using wavelet-based computational-space decomposition and space-filling-curve-based adaptive data compression to reduce communication and storage; (4) Immersive and interactive visualization of the large simulation data using octree-based visibility culling and parallel/distributed preprocessing of the visualization data with machine-learning predictive prefetch.The Gridified software will be used to study nanosystems of great importance to future information processing. Multiscale simulations involving 1,000 - 10,000 QM atoms and 100 million - 1 billion MD atoms will be performed to study atomistically-induced phenomena, with emphasis on environmental effects where chemical processes play an important role. The multiscale algorithm will relate the atomistic processes to experimentally observable quantities, by covering an order-of-magnitude larger length scale (10 micron) through continuum mechanics and extending time scales through the KMC and replica methods. The simulations will focus on stress domains and their phonon imaging in Si/Si3N4 and GaAs/Si3N4 nanopixels for sub-0.1 micron microelectronics applications and oxidation effects on them, and on substrate-encoded self-organized growth of lattice-mismatched semiconductor quantum dots (GaAs/InAs). The project will involve close collaborations with scientists at government laboratories (Argonne, NASA Ames, Sandia, Naval Oceanographic Office), industry (Intel, Motorola) and universities, as well as international collaborations in Europe, Japan and South America.%%%

该奖项是提交给信息技术研究倡议的提案的结果。 该研究的目标是开发一个可扩展的软件基础设施，用于在地理分布的大规模并行超级计算机网格上以及在未来的Petaflop计算机上进行大型多尺度模拟。多尺度模拟方法将在单个网格软件中结合联合收割机、有限元（FE）计算、粗粒度分子动力学（CGMD）、分子动力学（MD）模拟、以及基于密度泛函理论（DFT）的量子力学（QM）计算。 基于FE方法的连续介质力学计算将使用CGMD方法推导的本构关系与MD模拟结合进行，这反过来将嵌入DFT描述的QM算法。 （1）基于网格的FE/CGMD/MD/QM算法，该算法基于时空多分辨率算法，在并行/分布式计算机上实现分层分解，以实现可扩展性，并基于约束动力学的混合，以实现混合仿真组件的无缝耦合;（2）结合动力学蒙特卡罗（KMC）的时空分区多尺度模拟（3）网格计算工具，包括使用基于小波的计算空间分解的自适应负载平衡和基于空间填充曲线的自适应数据压缩，以减少通信和存储;（4）使用基于八叉树的可见性剔除对大型模拟数据进行沉浸式和交互式可视化，并使用机器学习预测预取对可视化数据进行并行/分布式预处理。Gridified软件将用于研究对未来信息处理具有重要意义的纳米系统。 将进行涉及1，000 - 10，000个QM原子和1亿-10亿个MD原子的多尺度模拟，以研究原子诱导的现象，重点是化学过程发挥重要作用的环境影响。 多尺度算法将原子过程与实验可观察到的量联系起来，通过连续介质力学覆盖一个数量级的更大长度尺度（10微米），并通过KMC和复制方法扩展时间尺度。 模拟将集中在应力域和它们的声子成像在Si/Si 3 N4和GaAs/Si 3 N4 nanopixels亚0.1微米微电子应用和氧化对它们的影响，并对衬底编码的自组织生长的晶格失配半导体量子点（GaAs/InAs）。该项目将涉及与政府实验室（阿贡、NASA艾姆斯、桑迪亚、海军海洋学办公室）、工业界（英特尔、摩托罗拉）和大学的科学家的密切合作，以及欧洲的国际合作、日本和南美洲。