CAREER: Deterministic Shared Memory Multiprocessing: Vision, Architecture, and Impact on Programmability

职业：确定性共享内存多重处理：愿景、架构和对可编程性的影响

• 批准号: 0846004
• 负责人: Luis Ceze
• 金额: $ 45万
• 依托单位: University of Washington
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-03-01 至 2016-02-29
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0846004&HistoricalAwards=false
• 关键词: CAREER; Deterministic; Shared; Memory; Multiprocessing

Software innovation typically relies on performance improvements ofthe underlying hardware. However, technology limitations hinderfurther significant progress in single-thread performance. Therefore,the software industry has the immense problem of rethinking itssoftware development process and techniques to adopt multicoresystems. Popularizing parallel programming is a Grand ResearchChallenge for the systems community [CRA]. Being able to leverage thefull potential of multicores would put us back into exponential growthof usable performance as well as lead to significant power savings.One of the main reasons why parallel programming is hard is thatparallel code in current multicore systems can executenondeterministically. Each time a multicore executes a parallelapplication, it can produce a different output even if supplied withthe same input. This frustrates debugging efforts and limits theability to properly test parallel code, becoming a major obstacle towidespread adoption of parallel programming. This project poses broad intellectual questions with far-reachingimplications in modern computer systems: Can nondeterminism be removedfrom shared-memory multiprocessor systems without degradingperformance? What are the trade-offs in designing deterministicmultiprocessor systems? What are the implications and uses ofdeterministic behavior in programmability? The PI plans to answer thesequestions by devising efficient, general purpose, fully deterministicshared memory multiprocessor systems and demonstrating that they canenable significant changes in how parallel programs are written,tested and deployed. An integral part of the concurrency challenge iseducation, so this project also aims to develop a graduate andundergraduate curriculum that will teach students about concurrencyprinciples and practical parallel programming.

软件创新通常依赖于底层硬件的性能改进。然而，技术限制阻碍了单线程性能的进一步显著进步。因此，软件业面临着重新思考其软件开发过程和技术以采用多核系统的巨大问题。普及并行编程是系统界的一项重大研究挑战[CRA]。能够充分利用多核的潜力将使我们重新进入可用性能的指数增长，并导致显著的节能。并行编程困难的主要原因之一是，当前多核系统中的并行代码可以确定性地执行。每次多核执行并行应用程序时，即使提供相同的输入，它也可能产生不同的输出。这阻碍了调试工作，并限制了正确测试并行代码的能力，成为广泛采用并行编程的主要障碍。这个项目提出了广泛的智力问题，对现代计算机系统具有深远的影响：能否在不降低性能的情况下，从共享内存的多处理器系统中消除不确定性？设计确定性多处理器系统的权衡是什么？确定性行为在可编程性中的含义和用途是什么？PI计划通过设计高效的、通用的、完全确定的共享存储器多处理器系统来回答这些问题，并证明它们能够显著改变并行程序的编写、测试和部署的方式。并发性挑战的一个组成部分是教育，所以这个项目还旨在开发一个研究生和本科生课程，向学生传授并发原理和实用的并行编程。