CCF: Medium: Routine Parallelism Enabled by Speculation

CCF：中：通过推测实现常规并行性

• 批准号: 0963759
• 负责人: Michael Scott
• 金额: $ 104.25万
• 依托单位: University of Rochester
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-07-01 至 2015-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0963759&HistoricalAwards=false
• 关键词: CCF; Medium; Routine; Parallelism; Enabled

Parallel programming is notoriously difficult, but essential to the future of computing. Much of the difficulty stems from the need to guarantee, in advance, that parallel computations will not conflict with one another.Speculation provides an attractive alternative. By monitoring behavior at run time, and retrying computations that conflict, speculation can expose significant amounts of otherwise unexploitable parallelism, while imposing little or no conceptual burden on the programmer.The sponsored research aims to make thread- and process-level speculation a fundamental feature of future programming systems, and to employ it in multiple forms and for multiple purposes: to automatically or semi-automatically parallelize sequential applications; to check, dynamically, the independence of explicitly parallel computations; to isolate the execution of semantically atomic functions; to enable optimizations that are not always safe; to parallelize scripting languages with one-thread-at-a-time semantics; and to profile applications in parallel, for feedback-driven optimization.The project adopts a tiered approach that isolates the users of simpler programming idioms from the need to understand more complex alternatives.At the implementation level, it stresses the seamless integration of shared memory and cluster-level distribution, compiler- and binary translator-based software instrumentation, virtual memory, and hardware speculation/transactions where available. Latter phases of the project place major emphasis on profiling tools to identify potentially independent program regions, which can then safely be executed in parallel (via speculation) in future runs.

并行编程是出了名的困难，但对计算的未来至关重要。 大部分困难来自于需要预先保证并行计算不会互相冲突，投机提供了一个有吸引力的选择。 通过在运行时监控行为，并重新尝试冲突的计算，推测可以暴露大量的否则无法利用的并行性，同时对程序员施加很少或根本没有概念上的负担。赞助的研究旨在使线程和进程级推测成为未来编程系统的基本特征，并以多种形式和多种目的使用它：自动或半自动并行化顺序应用程序;动态检查显式并行计算的独立性;隔离语义原子函数的执行;启用并不总是安全的优化;并行化具有一个线程的脚本语言一次语义;该项目采用分层的方法，将使用简单编程习惯的用户与理解更复杂的替代方案的需要隔离开来。在实现层面，它强调共享内存和集群级分布、基于编译器和二进制翻译器的软件插装、虚拟内存、以及硬件推测/事务（在可用的情况下）。 项目的后期阶段主要强调分析工具，以识别潜在的独立程序区域，然后可以在未来的运行中安全地并行执行（通过推测）。

项目成果

Leveraging hardware TM in Haskell

在 Haskell 中利用硬件 TM

• DOI: 10.1145/3293883.3295711
• 发表时间: 2019
• 期刊: Proceedings of the 24th Symposium on Principles and Practice of Parallel Programming
• 作者: Yates, Ryan;Scott, Michael L.
• 通讯作者: Scott, Michael L.