A Compositional Approach to Scalable Parallel Software

可扩展并行软件的组合方法

• 批准号: 0833199
• 负责人: Lawrence Rauchwerger
• 金额: $ 99.96万
• 依托单位: Texas A&M Engineering Experiment Station
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-09-01 至 2015-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0833199&HistoricalAwards=false
• 关键词: Compositional; Approach; Scalable; Parallel; Software

High-end computing systems are needed to study important, compute-intensive applications such as scientific simulations, multimedia stream processing, and geographical information systems. While these systems are still evolving, it is clear that they will be extremely large and complex, with tens to hundreds of thousands of processors providing a deep hierarchy of systems and resources. This research will develop the theory, techniques, and building blocks that can be used by domain scientists who are not expert parallel programmers to compose efficient applications for such complex systems.Hence, the outcomes of the research should greatly increase the number of potential users of high-end machines to include essentially all scientists whose problems could take advantage of such systems. The software resulting from this research, including the testbed applications for important problems in computational biology and physics, will be made publically available.Composition is a natural way to construct and reason about large, complex systems. This research will develop compositional strategies for building applications and for optimizing and controlling the application and its use of system resources.This project will use the STAPL (the Standard Template Adaptive Parallel Library) infrastructure for parallel C++ code. STAPL includes of a collection of generic parallel algorithms and distributed containers. In this research, STAPL's existing adaptive capabilities will be further refined and novel techniques will be developed for compositional performance modeling and for providing fault-tolerance capabilities that can be set individually for each container or algorithm instance in the program. A modern programming interface will be designed based on composition of parallel operations that will be modeled on the range abstractions in STAPL and C++0x and directly supported by a high-level compiler.

需要高端计算系统来研究重要的计算密集型应用，例如科学模拟，多媒体流处理和地理信息系统。 尽管这些系统仍在不断发展，但很明显，它们将非常大而复杂，成千上万的处理器提供了深厚的系统和资源层次结构。 这项研究将开发域科学家可以使用的理论，技术和构建基础，这些科学家不是专家并行程序员来为这种复杂系统构成有效的应用程序。因此，研究结果应大大增加高端机器的潜在用户的数量，以包括所有科学家都可以利用此类系统的所有科学家。 这项研究产生的软件，包括用于计算生物学和物理学重要问题的测试床应用程序，将公开可用。.position是一种自然的构建和理由的方式，可以构建大型，复杂的系统。 这项研究将制定用于构建应用程序的组成策略，并以优化和控制应用程序资源的应用及其使用。本项目将使用stapl（标准模板自适应平行库）用于并行C ++代码。 STAPL包括一系列通用并行算法和分布式容器的集合。 在这项研究中，将进一步完善Stapl现有的自适应能力，并为组成性能建模和提供可耐故障的功能而开发新的技术，这些功能可以为程序中的每个容器或算法实例分别设置。 现代编程界面将基于平行操作的组成设计，该操作将以Stapl和C ++ 0x的范围抽象进行建模，并由高级编译器直接支持。