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越传统线性代数算法的速度和规模处理数据，这在解决前沿科学和工程问题方面造成了实质性的瓶颈。为了克服这一挑战，线性代数算法被增强了随机化来压缩输入数据，这一技术在理论上已经显示出巨大的前景。不幸的是，这些理论进展并没有转化为实际实施，因为缺乏网络基础设施，使这些算法的快速和可重复的原型。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，在昂贵的软件开发之前，这个项目可以很容易地在科学计算中测试随机线性代数算法。因此，该项目准备支持解决尖端的计算科学和工程问题。此外，该项目利用网络基础设施提供可公开访问的随机线性代数理论和实现教育模块。该项目开发了一个随机算法的网络基础设施，重点是线性代数问题的算法。该项目将我们的随机线性代数算法的创新理论模块化映射到计算核，计算核可以很容易地组成和扩展，以快速开发针对特定科学计算的新颖，定制的方法。此外，该网络基础设施包括可重复测试算法的框架，并允许在部署之前对代码进行基准测试。这种网络基础设施通过直接解决气候应用中的前沿数据问题，展示了它的力量。该项目强调最佳科学软件实践，以开发可持续、社区参与和有影响力的网络基础设施。该奖项由美国国家科学基金会高级网络基础设施办公室颁发，并得到数学科学部的联合支持。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。