Collaborative Research: Elements: A Cyberlaboratory for Randomized Numerical Linear Algebra

合作研究：Elements：随机数值线性代数网络实验室

• 批准号: 2309445
• 负责人: Vivak Patel
• 金额: $ 33.16万
• 依托单位: University of Wisconsin-Madison
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-07-01 至 2026-06-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2309445&HistoricalAwards=false
• 关键词: Collaborative; Research; Elements; Cyberlaboratory; Randomized

Modern scientific and engineering computations require processing data at speeds and scales that overwhelm traditional linear algebra algorithms, which creates a substantial bottleneck in solving cutting-edge scientific and engineering problems. To overcome this challenge, linear algebra algorithms are being augmented with randomization to compress input data, a technique that has shown tremendous promise in theory. Unfortunately, these theoretical advances have not transformed into practical implementations because of a lack of a cyberinfrastructure that enables rapid and reproducible prototyping of such algorithms. To address this deficit, this project creates an innovative cyberinfrastructure to enable rapid implementation and reproducible comparison of these randomized linear algebra algorithms. Additionally, this project enables easily testing randomized linear algebra algorithms in scientific computations prior to expensive software development. Thus, this project is poised to support the solution of cutting-edge computational science and engineering problems. Moreover, this project utilizes the cyberinfrastructure to deliver publicly accessible educational modules on randomized linear algebra theory and implementation.This project develops a cyberinfrastructure for randomized algorithms with a focus on algorithms for linear algebra problems. This project maps our innovative theoretical modularization of randomized linear algebra algorithms to computational kernels, which can be readily composed and extended to rapidly develop novel, tailored methods for specific scientific computations. Moreover, this cyberinfrastructure includes a framework for reproducibly testing algorithms, and enables benchmarking codes prior to deployment. This cyberinfrastructure demonstrates its power by directly addressing cutting-edge data problems in climate applications. The project emphasizes best scientific software practices to develop a sustainable, community-engaging and impactful cyberinfrastructure.This award by the NSF Office of Advanced Cyberinfrastructure is jointly supported by the Division of Mathematical Sciences.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

现代科学和工程计算需要以超过传统线性代数算法的速度和规模处理数据，这在解决尖端科学和工程问题方面造成了巨大的瓶颈。为了克服这一挑战，线性代数算法正在通过随机化来压缩输入数据，这种技术在理论上已经显示出巨大的前景。不幸的是，由于缺乏能够快速且可重复地构建此类算法原型的网络基础设施，这些理论进展尚未转化为实际实现。为了解决这一缺陷，该项目创建了一个创新的网络基础设施，以实现这些随机线性代数算法的快速实施和可重复比较。此外，该项目可以在昂贵的软件开发之前在科学计算中轻松测试随机线性代数算法。因此，该项目旨在支持尖端计算科学和工程问题的解决。此外，该项目利用网络基础设施提供有关随机线性代数理论和实现的可公开访问的教育模块。该项目开发了随机算法的网络基础设施，重点关注线性代数问题的算法。该项目将我们随机线性代数算法的创新理论模块化映射到计算内核，该内核可以轻松组合和扩展，以快速开发用于特定科学计算的新颖的、定制的方法。此外，该网络基础设施包括一个用于可重复测试算法的框架，并可以在部署之前对代码进行基准测试。该网络基础设施通过直接解决气候应用中的尖端数据问题来展示其力量。该项目强调最佳科学软件实践，以开发可持续的、社区参与的和有影响力的网络基础设施。该奖项由 NSF 高级网络基础设施办公室颁发，并得到数学科学部的共同支持。该奖项反映了 NSF 的法定使命，并被认为值得通过使用基金会的智力优势和更广泛的影响审查标准进行评估来提供支持。