CNS Core: Medium: A Systems and User-based Approach to Floating Point Correctness and Resilience

CNS 核心：中：基于系统和用户的浮点正确性和弹性方法

• 批准号: 2211315
• 负责人: Peter Dinda
• 金额: $ 79.48万
• 依托单位: Northwestern University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-10-01 至 2026-03-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2211315&HistoricalAwards=false
• 关键词: CNS; Core; Medium; Systems; User

Computer arithmetic approximates the forms of arithmetic that humans use. This approximation can lead to errors for at least two reasons: computer arithmetic is inherently limited in the range and precision of numbers it can handle, and some familiar rules of “human arithmetic” may not apply, leading software developers to introduce bugs that lead to errors. In addition, computer arithmetic implementations, both in hardware and software, are quickly becoming more complex, potentially making developers more conservative out of fear of introducing new kinds of bugs by using them. This project will approach these problems from two new perspectives. From the user perspective, the project will study scientific and other software developers to better gauge their understanding of floating point arithmetic, the most common form of computer arithmetic in scientific applications, and to develop insights on how to better train developers. From the systems perspective, the project will study how to virtualize floating point arithmetic with high performance, making it easier to plug in alternative computer arithmetic systems with different properties, and tools for detecting problems with particular arithmetic systems. The project will also study important scientific applications using the tools it develops, as well as those developed by others.Science and engineering applications are increasingly critical to the economic, military, and environmental health of the nation. It is essential that such applications produce trustworthy results, regardless of the complexity of computer arithmetic and its implementations. Because computer arithmetic, and, more specifically, the IEEE standard for floating point arithmetic on which the project focuses, is a common denominator for most such applications, the project has the potential to improve such applications. Additionally, the project has the potential to better understand software developers, particularly scientific software developers, and thus develop better ways to train them with regard to floating point arithmetic. A collaboration with two national labs forms part of the project, and this will allow access both to scientific developers and to scientific applications that will serve to ground the project and hopefully also provide direct benefit beyond the expected research contributions. The project will also develop a training methodology for scientific developers, and an appropriate lab for undergraduates.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.

计算机算术近似于人类使用的算术形式，这种近似可能会导致错误，原因至少有两个：计算机算术本质上限制了它可以处理的数字的范围和精度，而一些熟悉的“人类算术”规则可能不受限制。应用，导致软件开发人员引入导致错误的错误。此外，硬件和软件中的计算机算术实现正在迅速变得更加复杂，可能使开发人员因担心引入新类型而变得更加保守。该项目将从两个新的角度来解决这些问题，该项目将研究科学和其他软件开发人员，以更好地衡量他们对浮点运算（科学应用中最常见的计算机运算形式）的理解。 ，并从系统角度深入了解如何更好地培训开发人员，该项目将研究如何虚拟化高性能浮点运算，从而更容易插入具有不同属性的替代计算机运算系统以及检测问题的工具。与特别的该项目还将使用其开发的工具以及其他人开发的工具来研究重要的科学应用。科学和工程应用对于国家的经济、军事和环境健康越来越重要。无论计算机算术及其实现的复杂性如何，应用程序都会产生值得信赖的结果，因为计算机算术，更具体地说，该项目所关注的浮点算术标准，是大多数此类应用程序的共同点，因此该项目。此外，该项目还有可能更好地了解软件开发人员，特别是科学软件开发人员，从而开发出更好的方法来培训他们的浮点运算。项目，这将允许科学开发人员和科学应用程序，这将有助于该项目的基础，并有望提供超出预期研究贡献的直接利益，该项目还将为科学开发人员开发一种培训方法，以及适当的方法。本科生实验室。该奖项反映了 NSF 的法定使命通过使用基金会的智力优点和更广泛的影响审查标准进行评估，并被认为值得支持。