EAGER: Collaborative Research: Lighthouse: A User- Centered Web System for High-Performance Software Development

EAGER：协作研究：Lighthouse：用于高性能软件开发的以用户为中心的 Web 系统

• 批准号: 1550202
• 负责人: Boyana Norris
• 金额: $ 15万
• 依托单位: University of Oregon Eugene
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-08-01 至 2018-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1550202&HistoricalAwards=false
• 关键词: EAGER; Collaborative; Research; Lighthouse; User

The role of computing in science and engineering has been growing steadily in recent years, leading to ever larger and more complex problems. Their solution requires high-performance resources, which has resulted in many efforts to produce new mathematical approaches, programming models and languages, software libraries, and runtime environments for advanced parallel computers. This vast and growing number of solution methods presents a challenge to scientists who do not want to invest the time needed to locate and learn new computational tools. The PIs are developing Lighthouse, a taxonomy-based system, that equips practitioners with easy discovery and use of high-performance software solutions to a variety of common problems arising in scientific and engineering applications. Lighthouse also integrates information about the performance of multiple implementations of numerical algorithms. It thus allows users to readily find and start using the best method for addressing a particular challenge with the computers available to them. Less time spent in learning numerical packages and faster scientific simulations directly increases scientific productivity.Lighthouse is a web-based framework that offers a solution to two main research challenges. First, it aids in the creation of complex high-performance applications that leverage the latest advances in applied mathematics and computer science research. Second, it facilitates effective intra- and cross-domain communication for computer scientists, applied mathematicians, computational scientists, and students as they tackle scientific and engineering computing problems. Lighthouse incorporates an extensible taxonomy that enables different types of searches for numerical solutions depending on a user?s level of expertise. It then provides a mechanism for generating code templates based on the search results. Lighthouse thereby reduces the substantial learning curves associated with using state-of-the art high-performance software libraries. The Lighthouse system integrates taxonomy information for an expanding number of high-performance numerical libraries that presently comprises the linear algebra packages LAPACK, PETSc, and SLEPc. Lighthouse employs machine learning methods to automatically classify routines based on their performance attributes. In this way, it helps to provide more accurate search results that take into account not only functionality but also problem scale, performance, and available computational resource requirements. Finally, Lighthouse improves communication within and between communities by providing an accessible web-based interface to taxonomies of numerical packages that includes documentation, references, and performance information.

近年来，计算在科学和工程中的作用一直在稳步增长，导致了越来越大，越来越复杂的问题。 他们的解决方案需要高性能的资源，这导致了许多努力，以产生新的数学方法，编程模型和语言，软件库，以及先进的并行计算机的运行时环境。这种数量庞大且不断增长的求解方法对不想投入时间来定位和学习新计算工具的科学家提出了挑战。PI正在开发Lighthouse，这是一个基于分类学的系统，它使从业者能够轻松发现和使用高性能软件解决方案，以解决科学和工程应用中出现的各种常见问题。 Lighthouse还集成了有关数值算法的多种实现的性能的信息。 因此，它使用户能够很容易地找到并开始使用最佳方法来解决他们可用的计算机的特定挑战。花在学习数值包和更快的科学模拟上的时间更少，直接提高了科学生产力。Lighthouse是一个基于Web的框架，为两个主要的研究挑战提供了解决方案。 首先，它有助于创建复杂的高性能应用程序，这些应用程序利用了应用数学和计算机科学研究的最新进展。 其次，它促进了计算机科学家、应用数学家、计算科学家和学生在解决科学和工程计算问题时的有效域内和跨域通信。Lighthouse集成了一个可扩展的分类法，可以根据用户的不同搜索不同类型的数值解。的专业水平。 然后，它提供了一种基于搜索结果生成代码模板的机制。 Lighthouse因此减少了与使用最先进的高性能软件库相关的大量学习曲线。Lighthouse系统集成了大量高性能数值库的分类信息，这些库目前包括线性代数包LAPACK、PETSc和SLEPc。 Lighthouse使用机器学习方法根据例程的性能属性自动对其进行分类。 通过这种方式，它有助于提供更准确的搜索结果，不仅考虑功能，而且考虑问题规模，性能和可用的计算资源要求。最后，Lighthouse通过提供一个可访问的基于Web的数字包分类界面（包括文档，参考和性能信息）来改善社区内部和社区之间的通信。