SHF: Small: Whole-application Coordiated Parallelization Through The Optimization Of Abstraction Hierarchies

SHF：小型：通过抽象层次结构的优化实现全应用程序协调并行化

• 批准号: 1910488
• 负责人: Qing Yi
• 金额: $ 49.95万
• 依托单位: University of Colorado at Colorado Springs
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-10-01 至 2024-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1910488&HistoricalAwards=false
• 关键词: SHF; Small; Whole; application; Coordiated

Large computer software is based on programming abstractions, e.g., functions and object-oriented types, to organize computation and data, which are in turn parallelized by invoking a variety of lower-level library support. A correct and efficient software implementation requires meticulous attention to coding details and is often error-prone. However, these implementations frequently need to be adapted to run on different hardware platforms as part of the software evolution and maintenance process. This project develops new cutting-edge compiler technology to automatically enhance the parallelization efficiency of large computer software, thereby simultaneously enhancing their productivity, correctness assurance, performance, and hardware portability. This project is aligned with object-oriented design principles in modern software engineering and therefore is expected to impact a modern software practices by enabling automatic exploration of alternative parallelization and data structure designs for better performance, maintainability, and hardware portability. The compiler toolsets developed in this project will be disseminated open source and will be used as an educational toolkit in the teaching of programming languages, compilers, high performance computing, and parallel programming courses.The research methodology of this project explores a new scope of optimization at the user-defined abstraction level, by grouping and encapsulating related operations into hierarchies of abstractions, and by adapting a set of concepts traditionally used in the practice of software engineering, specifically abstract data types, abstraction adapters, and application abstraction hierarchy, to automatically discover higher-level semantics of user-defined abstractions and to isolate algorithm-level structures and logistics from their lower-level implementations. Pattern-driven analysis techniques are then developed to automatically discover a whole-application task graph, and coordinated optimizations are applied across abstraction boundaries to maximize overall application efficiency. A uniform interface is designed to concisely document the higher-level semantics of abstractions. Empirical performance tuning is used to support the performance portability of applications on a variety of modern computing platforms.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.

大型计算机软件基于编程抽象，例如，函数和面向对象的类型来组织计算和数据，这些计算和数据又通过调用各种较低级别的库支持来并行化。一个正确而有效的软件实现需要对编码细节进行细致的关注，而且往往容易出错。然而，作为软件演进和维护过程的一部分，这些实现经常需要进行调整以在不同的硬件平台上运行。该项目开发新的尖端编译器技术，以自动提高大型计算机软件的并行化效率，从而同时提高其生产率，正确性保证，性能和硬件可移植性。该项目符合现代软件工程中面向对象的设计原则，因此预计将通过自动探索替代并行化和数据结构设计来影响现代软件实践，以获得更好的性能，可维护性和硬件可移植性。该项目开发的编译器工具集将以开放源代码的方式传播，并将作为编程语言、编译器、高性能计算和并行编程课程教学的教育工具包。该项目的研究方法探索了一种新的优化范围，即在用户定义的抽象级别上，通过将相关操作分组并封装到抽象层次中，并且通过调整传统上在软件工程实践中使用的一组概念，特别是抽象数据类型、抽象适配器和应用抽象层次结构，来自动发现用户定义的抽象的高级语义，并将算法级结构和逻辑与它们的低级实现隔离。然后开发模式驱动的分析技术来自动发现整个应用程序任务图，并跨抽象边界应用协调优化以最大限度地提高整体应用程序效率。一个统一的接口被设计成简洁地记录抽象的高级语义。经验性能调优用于支持各种现代计算平台上应用程序的性能可移植性。该奖项反映了NSF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。

项目成果

Enhancing the Effectiveness of Inlining in Automatic Parallelization

增强自动并行化中内联的有效性

• DOI: 10.1007/s10766-021-00722-1
• 发表时间: 2022
• 期刊: International Journal of Parallel Programming
• 影响因子: 1.5
• 作者: Guo, Jichi;Yi, Qing;Psarris, Kleanthis
• 通讯作者: Psarris, Kleanthis

Automating Non-Blocking Synchronization In Concurrent Data Abstractions

• DOI: 10.1109/ase.2019.00074
• 发表时间: 2019-11
• 期刊: 2019 34th IEEE/ACM International Conference on Automated Software Engineering (ASE)
• 作者: Jiange Zhang;Qing Yi;D. Dechev

Modeling optimization of stencil computations via domain-level properties

通过域级属性对模板计算进行建模优化

• DOI: 10.1145/3528425.3529103
• 发表时间: 2022
• 期刊: Thirteenth International Workshop on Programming Models and Applications for Multicores and Manycores
• 作者: Nesterenko, Brandon;Yi, Qing;Lin, Pei-Hung;Liao, Chunhua;Runnels, Brandon
• 通讯作者: Runnels, Brandon