SHF: Medium: Collaborative Research: Extending Declarative Parallel Programming with State and Nondeterminism

SHF：媒介：协作研究：使用状态和非确定性扩展声明式并行编程

• 批准号: 1065099
• 负责人: Matthew Fluet
• 金额: $ 41.23万
• 依托单位: Rochester Institute of Tech
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-01 至 2016-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1065099&HistoricalAwards=false
• 关键词: SHF; Medium; Collaborative; Research; Extending

This project addresses parallelism in applications with the goal of improving the efficiency of those applications.Today's multicore and manycore computers provide increasing amounts of computational power in the form of parallel processing. But, before a software application can take advantage of such parallel hardware and exhibit speedups in execution, a software developer must (re)write the program to indicate which portions may be executed in parallel and which portions must be executed sequentially. The Manticore research project designed and implemented the Parallel ML programming language, a functional programming language with a rich collection of explicitly- and implicitly-parallel programming features. To date, this team built an implementation of PML that is efficient and scalable. However, PML lacks some features present in other languages, such as shared state, which grants the ability to freely modify data shared between parallel threads, and nondeterminism, which grants the ability to return results that may depend upon the order of parallel execution. These features are generally considered difficult to use correctly and difficult to implement efficiently in a parallel setting; yet, they have the potential to make greater portions of an application amenable to parallel execution.Therefore, this project focuses on the significant problem of increasing the amount of parallelism exposed by applications by extending Parallel ML with mechanisms like shared state and nondeterminism in a safe and efficient manner. A key feature of the design is that it provides ways to isolate the stateful and nondeterministic components of a program; this isolation makes these mechanisms easier and safer to use by software developers. Another key feature of the design is that it captures common programming idioms, such as caching to avoid redundant computations and make independent writes to a shared sparse data structure in a manner that ensures safe and efficient program execution. Thus, this proejct frees the software developer from the difficult and error-prone task of explicitly programming the low-level details that manage the parallel execution of an application; instead, the software developer focuses on the high-level application logic, while the compiler and runtime system allocates the parallel execution over the available computational resources. This research is helping guide future language design efforts and transforming programming practice toward higher-level and more declarative models, yielding improved productivity, correctness, performance, and scalability.

该项目解决了应用程序中的并行性，以提高这些应用程序的效率。TODAY的多计算机和多核计算机以并行处理的形式提供了越来越多的计算能力。 但是，在软件应用程序可以利用这种并行硬件和执行中的展览加速度之前，软件开发人员必须（重新）编写程序以指示可以并行执行哪些部分，并且必须顺序执行哪些部分。 Manticore研究项目设计和实施了并行的ML编程语言，这是一种功能编程语言，具有丰富的明确和隐式并行编程功能。 迄今为止，该团队建立了有效且可扩展的PML的实现。 但是，PML缺少其他语言中存在的某些功能，例如共享状态，这些功能赋予了在并行线程之间自由修改数据和非确定性之间共享数据的能力，这些数据赋予了返回结果的能力，这些结果可能取决于并行执行的顺序。 通常认为这些功能难以正确使用，并且在平行设置中难以有效地实现；然而，他们有可能使更大的应用程序的更大部分适合并行执行。因此，该项目着重于通过以安全有效的方式将并行ML与共享状态和非确定性等机制扩展到相同的ML，以增加应用程序所曝光的并行量。 该设计的一个关键特征是它提供了隔离程序的状态和非确定性组件的方法；这种隔离使这些机制更容易，更安全地由软件开发人员使用。 设计的另一个关键功能是，它捕获了常见的编程成语，例如缓存，以避免冗余计算，并以确保安全有效的程序执行的方式对共享的稀疏数据结构进行独立写入。 因此，此主张将软件开发人员摆脱出严格且容易出错的任务，这些任务明确地编程了管理应用程序并行执行的低级详细信息；取而代之的是，软件开发人员专注于高级应用程序逻辑，而编译器和运行时系统则分配了可用的计算资源的并行执行。 这项研究正在帮助指导未来的语言设计工作，并将编程实践转变为更高级别和更高的声明性模型，从而提高了生产力，正确性，性能和可扩展性。