XPS: FULL: SDA: Collaborative Research: SCORE: Scalability-Oriented Optimization

XPS：完整：SDA：协作研究：SCORE：面向可扩展性的优化

• 批准号: 1439008
• 负责人: Emery Berger
• 金额: $ 64.8万
• 依托单位: University of Massachusetts Amherst
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-01 至 2020-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1439008&HistoricalAwards=false
• 关键词: XPS; FULL; SDA; Collaborative; Research

Title: XPS: FULL: SDA: Collaborative Research: SCORE: Scalability-Oriented OptimizationModern CPUs, which contain an increasingly large number of processing units or "cores", offer the promise of continued increases in performance as the number of cores increases. Unfortunately, it is notoriously difficult for programmers to fully take advantage of this processing power. Computations can be viewed as cars on a network of highways: we want traffic to flow as fast as possible without any crashes. Programming languages offer "synchronization operations"---the programmer equivalent of traffic lights---which improve safety but reduce speed. For large programs, managing the tension between the twin goals of safety (more lights) and performance (fewer lights) can be out of reach for all but expert programmers. This project, SCORE (scalability-oriented optimization), lifts this burden by automatically maximizing program performance while maintaining correctness. The intellectual merits of this work are the development of a suite of techniques to identify bottlenecks in programs, and transform their code or execution environment to eliminate those bottlenecks. The project's broader significance and importance are to enable non-expert programmers to achieve high performance on modern, multicore platforms, and thus dramatically increase the performance and efficiency of existing and new software; contributing to the national software research infrastructure; and increasing access to science research opportunities and training for students.As with optimizing compilation for sequential code, SCORE lifts the burden of concurrency optimization from programmers, letting them focus exclusively on getting the logic of their program right. By handling architectural and synchronization optimizations without programmer involvement, SCORE lets programmers deliver applications that portably and effectively harness a wide range of multicore architectures. SCORE comprises a suite of new dynamic analyses, static analyses, and runtime systems to enable scalability-oriented optimization. It uncovers bottlenecks and ranks them by the performance impact of removing them. This information guides a bottleneck-remediation dynamic analysis to identify a range of opportunities for concurrency optimizations. Finally, a code robustification phase augments the optimized code with lightweight checking and recovery code to ensure correct execution.

标题：XPS：FULT：SDA：协作研究：分数：面向可伸缩性的优化型CPU，其中包含越来越多的处理单元或“核心”，随着核心数量的增加，持续增强性能的承诺。不幸的是，众所周知，程序员很难充分利用这种处理能力。可以将计算视为高速公路网络上的汽车：我们希望流量尽可能快地流动而不会发生任何崩溃。编程语言提供“同步操作” ---相当于交通信号灯的程序员 - - 提高安全性但降低速度。对于大型计划，除了专家程序员之外，所有安全性的双重目标（更多灯光）和性能（更少的灯光）之间的紧张关系可能无法实现。该项目是分数（以可伸缩性为导向的优化），通过自动提高程序性能，同时保持正确性，从而负担这一负担。这项工作的智力优点是开发了一套技术，以识别程序中的瓶颈，并改变其代码或执行环境以消除这些瓶颈。该项目的更广泛的意义和重要性是使非专家程序员能够在现代，多核心平台上实现高性能，从而大大提高现有软件和新软件的性能和效率；为国家软件研究基础设施做出贡献；并增加了为学生获得科学研究机会和培训的机会。随着对顺序代码的优化，得分会增加程序员的并发优化负担，让他们专注于正确地掌握其程序的逻辑。通过处理无需程序员参与的体系结构和同步优化，得分可以使程序员提供便便有效地利用广泛的多项架构的应用程序。得分包括一系列新的动态分析，静态分析和运行时系统，以实现面向可伸缩性的优化。它可以通过删除它们的性能影响来发现瓶颈并将其排名。该信息指导了瓶颈解析动态分析，以确定一系列并发优化的机会。最后，代码鲁棒化阶段通过轻巧的检查和恢复代码增加了优化的代码，以确保正确执行。