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.%%%

该奖项是提交信息技术研究计划的提案的结果。 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）基于密度功能理论（DFT）的计算。 基于FE方法的连续性力学计算将使用从CGMD方法得出的本构关系与MD模拟一起进行，这又将嵌入由DFT描述的QM算法。 将开发以下内容：（1）基于基于网格的FE/CGMD/MD/QM算法，基于时空的多分辨率算法在并行/分布式计算机上以分层分解为实施，用于可伸缩性和基于约束的杂交杂种，以实现Hybrid SimoNETS Componulation Componulation Componulation Componulation Complution Complution Complution Complatuly Complation; （2）时空分区的多尺度模拟与动力学蒙特卡洛（KMC）和平行复制方法相结合，以使长度和时间尺度相对; （3）网格计算工具，包括使用基于小波的计算空间分解和基于空间曲线的自适应数据压缩的自适应负载平衡，以减少通信和存储； （4）使用基于OCTREE的可见性扣除和并行/分布式的可视化数据对可视化数据的并行/分布式预处理，对大型仿真数据进行了沉浸式和交互式可视化。使用机器学习预测的可视化数据。网格化软件将用于研究对未来信息处理非常重要的纳米系统。 涉及1,000-10,000 QM原子和1亿-10亿MD原子的多尺度模拟将进行研究，以研究原子引起的现象，重点是化学过程起着重要作用的环境影响。 多尺度算法将通过连续力学覆盖较大的长度尺度（10微米）并通过KMC和Replica方法延长时间尺度，将原子过程与实验可观察到的数量联系起来。 这些模拟将重点关注SI/SI3N4和GAAS/SI3N4纳米固定中的应力域及其声子成像，用于SUB-0.1微米微观微电子的应用以及对其的氧化效果，以及晶状体匹配的半导体量子dots（Gaas/Inass）的基质编码的自组织的自组织的生长。该项目将涉及与政府实验室（Argonne，NASA Ames，Sandia，海军海洋学办公室），工业（英特尔，摩托罗拉）和大学以及欧洲，日本和南美的国际合作。