SHF: AF: Large: Collaborative Research: Parallelism without Concurrency

SHF：AF：大型：协作研究：无并发的并行性

• 批准号: 1314590
• 负责人: Guy Blelloch
• 金额: $ 99.95万
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-07-01 至 2019-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1314590&HistoricalAwards=false
• 关键词: SHF; AF; Large; Collaborative; Research

The widespread deployment of parallel machines --- from multicores to supercomputers --- has made it critical to develop simple approaches to programming them. Significant progress has been made in simplifying parallel programming by developing programming models to support parallelism without concurrency, that is, without the nondeterminacies in the logic of programs caused by the relative and nondeterministic timing of communicating processes. Yet most parallel programs in practice are concurrent, and hence, nondeterministic, leading to code that can only be programmed and understood by experts. This research project aims to understand how parallel computers can be made easier to use by the vast majority of programmers by developing software technology that enables deterministic parallel computing.The project takes a holistic view of the problem from the key perspectives of programming linguistics, software systems, algorithmic analysis, and absolute performance. It acknowledges the reality that parallel programming cannot be fully deterministic at every level of abstraction. It is pursuing three key strategies for dealing with concurrency: encapsulating concurrency so that it is hidden by layered abstractions at appropriate abstraction levels, avoiding concurrency by restructuring programs to employ deterministic approaches, and managing concurrency when it is impractical to either encapsulate or avoid concurrency completely. Among the specific techniques being studied are commutative building blocks, deterministic nonassociative reducers, deterministic pipelined parallelism, deterministic interfaces, and generalized race detection for detecting invariant races. The project is developing open-source libraries, tools, and runtime extensions integrated into a multicore-software platform, as well as a problem-based benchmark suite to compare approaches.

并行机器的广泛部署-从多核到超级计算机--使得开发简单的方法来对它们进行编程变得至关重要。通过开发编程模型来支持无并发的并行，也就是没有通信进程的相对和不确定的定时导致的程序逻辑中的不确定性，在简化并行编程方面已经取得了重大进展。然而，大多数并行程序在实践中都是并发的，因此是不确定的，导致代码只能由专家编程和理解。这个研究项目旨在了解如何通过开发能够实现确定性并行计算的软件技术来使并行计算机更容易被大多数程序员使用。该项目从编程语言学、软件系统、算法分析和绝对性能等关键角度全面地看待这个问题。它承认了这样一个事实，即并行编程不可能在每个抽象级别都是完全确定的。它正在追求三个处理并发的关键策略：封装并发，以便在适当的抽象级别通过分层抽象将其隐藏；通过重组程序以采用确定性方法来避免并发；以及在完全封装或避免并发不切实际的情况下管理并发。正在研究的具体技术包括交换构建块、确定性非关联归约器、确定性流水线并行、确定性接口以及用于检测不变竞争的广义竞争检测。该项目正在开发集成到多核软件平台中的开源库、工具和运行时扩展，以及用于比较方法的基于问题的基准测试套件。