SI2-SSE: Dynamic Adaptive Runtime Systems for Advanced Multipole Method-based Science Achievement

SI2-SSE：基于先进多极方法的科学成就的动态自适应运行时系统

• 批准号: 1440396
• 负责人: Matthew Anderson
• 金额: $ 49.84万
• 依托单位: Indiana University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-10-01 至 2017-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1440396&HistoricalAwards=false
• 关键词: SI2; SSE; Dynamic; Adaptive; Runtime

Multipole methods, including the fast multipole method and the Barnes-Hut algorithm, contribute to a broad range of end-user science applications extending from molecular dynamics to galaxy formation. Multipole methods are widely applied to N-body like problems where the individual interactions of a large number of distant objects can be treated as a single interaction under the appropriate conditions. This simplification eliminates the need for computing individual pairwise interactions and results in a drastic speed-up of computation. However, conventional parallel multipole methods are facing serious challenges to remain competitive as computational resources approach Exascale. Many applications employing multipole methods describe very dynamic physical processes, both in their time dependence and in their range of relevant spatial scales, while conventional implementations of multipole methods are essentially static in nature leading to computational inefficiencies. This project provides a fine-grained data-driven approach for multipole methods in order to address the limitations of conventional practices and improve scalability and efficiency. The software library employs dynamic adaptive execution methods with multipole-specific strategies for fault tolerance and exception handling while simplifying the implementation of the fast multipole method and the Barnes-Hut algorithm for end-users. The project software library immediately impacts science applications based on multipole methods by improving application scalability and efficiency and providing fault tolerance, a global address space, and an Exascale-ready execution model which integrates the entire system stack. The software library provides a portable and easy-to-use interface that allows scientists to work more efficiently and take advantage of high performance computing resources more effectively. The software library also serves to inform the evolution and development of other languages and programming models aiming to improve performance by shifting to message-driven techniques.

多极方法，包括快速多极方法和 Barnes-Hut 算法，有助于从分子动力学到星系形成的广泛最终用户科学应用。多极方法广泛应用于类似 N 体的问题，其中大量远处物体的个体相互作用在适当的条件下可以被视为单个相互作用。 这种简化消除了计算个体成对相互作用的需要，并导致计算速度大幅加快。 然而，随着计算资源接近百亿亿级，传统的并行多极方法正面临着保持竞争力的严峻挑战。许多采用多极方法的应用描述了非常动态的物理过程，无论是在时间依赖性还是在相关空间尺度范围内，而多极方法的传统实现本质上本质上是静态的，导致计算效率低下。该项目为多极方法提供了细粒度的数据驱动方法，以解决传统实践的局限性并提高可扩展性和效率。该软件库采用动态自适应执行方法以及针对容错和异常处理的多极特定策略，同时为最终用户简化了快速多极方法和 Barnes-Hut 算法的实现。 该项目软件库通过提高应用程序可扩展性和效率、提供容错能力、全局地址空间以及集成整个系统堆栈的 Exascale 就绪执行模型，立即影响基于多极方法的科学应用程序。 该软件库提供了一个便携且易于使用的界面，使科学家能够更高效地工作并更有效地利用高性能计算资源。 该软件库还可以为其他语言和编程模型的演变和开发提供信息，旨在通过转向消息驱动技术来提高性能。