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摘要，例如功能和面向对象的类型，以组织计算和数据，而这些计算和数据又通过调用各种较低级别的库支持而平行。正确且有效的软件实施需要对编码细节的细致注意，并且通常容易出错。但是，作为软件演化和维护过程的一部分，通常需要对这些实现进行调整以在不同的硬件平台上运行。该项目开发了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，性能和硬件便携性。该项目与现代软件工程中的面向对象的设计原理保持一致，因此有望通过自动探索​​替代性并行化和数据结构设计来影响现代软件实践，以提高性能，可维护性和硬件可移植性。 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软件工程，特别是抽象的数据类型，抽象适配器和应用抽象层次结构，以自动发现用户定义的抽象的更高级别的语义，并将算法级别的结构和物流隔离到其低级实现中。然后开发模式驱动的分析技术以自动发现整个应用任务图，并在抽象边界上应用协调的优化，以最大程度地提高整体应用效率。统一的界面旨在简洁地记录抽象的高级语义。经验性能调整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的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛的影响评估标准通过评估来支持的。

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