EAGER: Collaborative Research: Lighthouse: A User- Centered Web System for High-Performance Software Development
EAGER: Collaborative Research: Lighthouse: A User- Centered Web System for High-Performance Software Development
批准号:
1550202
负责人:
Boyana Norris
金额:
$15.0万
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
项目状态:
已结题
起止时间:
2015-08-01 至 2018-07-31
中文摘要
近年来,计算机在科学和工程中的作用一直在稳步增长,导致了更大、更复杂的问题。他们的解决方案需要高性能的资源,这导致了为高级并行计算机产生新的数学方法、编程模型和语言、软件库和运行时环境的许多努力。对于那些不愿意花时间去寻找和学习新的计算工具的科学家来说,数量庞大且不断增长的解决方法是一个挑战。pi正在开发Lighthouse,这是一个基于分类法的系统,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,它允许用户很容易地找到并开始使用最好的方法来解决他们可用的计算机的特定挑战。更少的时间花在学习数值包和更快的科学模拟上,直接提高了科学生产力。Lighthouse是一个基于网络的框架,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,利用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处理科学和工程计算问题时有效的内部和跨领域交流。Lighthouse集成了一个可扩展的分类法,可以根据用户对数值解决方案进行不同类型的搜索。S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。因此,Lighthouse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系统集成了分类信息,用于扩展数量的高性能数值库,目前包括线性代数包LAPACK, PETSc和SLEPc。Lighthouse采用机器学习方法根据例程的性能属性自动分类。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,还考虑问题规模、性能和可用的计算资源需求。最后,Lighthouse通过为数字包的分类(包括文档、参考和性能信息)提供可访问的基于web的接口,改善了社区内部和社区之间的通信。
英文摘要
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.
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Collaborative Research: Framework Implementation: CSSI: CANDY: Cyberinfrastructure for Accelerating Innovation in Network Dynamics
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批准号:2104115
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项目类别:Standard Grant
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资助金额:$121.4万
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财政年份:2021
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负责人:Boyana Norris
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依托单位:
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项目类别:Continuing Grant
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资助金额:$22.5万
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财政年份:2017
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负责人:Boyana Norris
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依托单位:
SHF: Small: Collaborative Research: Automated Numerical Solver EnviRonment (ANSER)
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批准号:1717883
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项目类别:Standard Grant
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资助金额:$22.5万
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财政年份:2017
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负责人:Boyana Norris
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依托单位:
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批准号:0916474
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项目类别:Standard Grant
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资助金额:$0.0万
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财政年份:2009
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负责人:Boyana Norris
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依托单位:
海外基金