CAREER: Fast Methods for Particle Dynamics and Their Applications

职业：粒子动力学的快速方法及其应用

• 批准号: 9875899
• 负责人: Ananth Grama
• 金额: $ 23.49万
• 依托单位: Purdue Research Foundation
• 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 2004-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9875899&HistoricalAwards=false
• 关键词: CAREER; Fast; Methods; Particle; Dynamics

This project will develop innovative techniques and software for so-called"fast methods" for n-body solvers and their applications. An n-body solvercomputes the behavior of a set of interacting particles; examples run fromthe solar system (9 planets interacting through gravity) to computer chips(billions of atoms that attract or repel electrons). "Fast" methods forthese solvers use data structures such as trees to minimize the number ofcomputations. Typically, the data structure summarizes the interactions ofa group of particles, eliminating the need to compute all of the pairwiseinteractions. Managing the data structure makes these methods difficult toprogram, particularly on modern parallel machines.This project addresses algorithmic issues, serial and parallel performance,portability, and I/O requirements for fast methods for particle dynamics inselected applications. Specifically, the project makes researchcontributions in the following areas:* Error Control and Boundary Conditions: This project will extend recentwork in variable degree multipoles to improve error bounds in non-uniformparticle distributions while minimizing the added computation.* Robust Parallel Algorithms and Libraries: This project will buildcalibrated portable libraries of fast solvers capable of adapting todynamic computational platforms like clusters of multiprocessors.* Data Analysis and I/O Control: This project will investigate compressionschemes capable of effectively handling the huge amounts of data generatedby particle dynamics simulations.The education plan includes a variety of initiatives at various levels. TheComputer Applications in K-12 Education in Science (CAKE) program willintroduce pre-college students to the use of high performance computing andnetworking, using GUIs based on the research libraries as teaching tools.A series of courses, seminars, and workshops on parallel computing and itsapplications will extend the education to the undergraduate and graduatelevels at Purdue University.

该项目将为n体解算器及其应用开发所谓的“快速方法”的创新技术和软件。 n体求解器计算一组相互作用的粒子的行为;例子从太阳系（9个行星通过引力相互作用）到计算机芯片（数十亿吸引或排斥电子的原子）。 这些求解器的“快速”方法使用数据结构，如树，以最大限度地减少计算量。 通常，数据结构总结了一组粒子的相互作用，消除了计算所有成对相互作用的需要。 管理数据结构使得这些方法难以编程，特别是在现代并行机上。这个项目解决了算法问题，串行和并行性能，可移植性和I/O要求的快速方法粒子动力学在选定的应用程序。具体而言，该项目在以下领域做出了研究贡献：* 误差控制和边界条件：该项目将扩展变阶多极子的最近网络，以改善非均匀粒子分布的误差范围，同时最大限度地减少增加的计算。鲁棒并行算法和库：该项目将建立快速求解器的校准便携式库，能够适应动态计算平台，如多处理器集群。数据分析和I/O控制：该项目将研究能够有效处理粒子动力学模拟产生的大量数据的压缩方案。教育计划包括各种不同级别的举措。计算机应用在K-12科学教育（CAKE）计划将引导大学预科学生使用高性能计算和网络，使用基于研究库的GUI作为教学工具。一系列关于并行计算及其应用的课程，研讨会和研讨会将把教育扩展到普渡大学的本科和研究生水平。