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

标题：XPS: FULL: SDA：协作研究：SCORE：面向可扩展性的优化现代cpu包含越来越多的处理单元或“核心”，随着核心数量的增加，提供了性能持续提高的承诺。不幸的是，程序员要充分利用这种处理能力是非常困难的。计算可以被看作是高速公路网络上的汽车：我们希望车流尽可能快，而不会发生碰撞。编程语言提供“同步操作”——在编程中相当于红绿灯——这提高了安全性，但降低了速度。对于大型程序来说，管理安全（更多的灯光）和性能（更少的灯光）这两个目标之间的紧张关系，除了专家级的程序员之外，几乎是遥不可及的。这个项目SCORE（面向可伸缩性的优化）通过在保持正确性的同时自动最大化程序性能，减轻了这种负担。这项工作的智力优点是开发了一套技术来识别程序中的瓶颈，并转换它们的代码或执行环境以消除这些瓶颈。该项目更广泛的意义和重要性是使非专业程序员能够在现代多核平台上实现高性能，从而大大提高现有和新软件的性能和效率；为国家软件研究基础设施作出贡献；增加学生获得科学研究机会和培训的机会。与优化顺序代码的编译一样，SCORE减轻了程序员并发性优化的负担，让他们专注于使程序的逻辑正确。通过在没有程序员参与的情况下处理体系结构和同步优化，SCORE允许程序员交付可移植且有效地利用各种多核体系结构的应用程序。SCORE包括一套新的动态分析、静态分析和运行时系统，以支持面向可伸缩性的优化。它揭示瓶颈，并根据消除瓶颈对性能的影响对它们进行排序。此信息指导瓶颈补救动态分析，以确定并发优化的一系列机会。最后，代码健壮化阶段用轻量级检查和恢复代码增强优化后的代码，以确保正确执行。

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.