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Looking Back on the Language and Hardware Revolutions: Measured Power, Performance, and Scaling

机译:回顾语言和硬件革命:测得的功率,性能和扩展

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This paper reports and analyzes measured chip power and performance on five process technology generations executing 61 diverse benchmarks with a rigorous methodology. We measure representative Intel IA32 processors with technologies ranging from 130nm to 32nm while they execute sequential and parallel benchmarks written in native and managed languages. During this period, hardware and software changed substantially: (1) hardware vendors delivered chip multiprocessors instead of uniprocessors, and independently (2) software developers increasingly chose managed languages instead of native languages. This quantitative data reveals the extent of some known and previously unobserved hardware and software trends. Two themes emerge. (I) Workload: The power, performance, and energy trends of native workloads do not approximate managed workloads. For example, (a) the SPEC CPU2006 native benchmarks on the i7 (45) and i5 (32) draw significantly less power than managed or scalable native benchmarks; and (b) managed runtimes exploit parallelism even when running single-threaded applications. The results recommend architects always include native and managed workloads when designing and evaluating energy efficient hardware. (II) Architecture: Clock scaling, microarchitecture, simultaneous multithreading, and chip multiprocessors each elicit a huge variety of power, performance, and energy responses. This variety and the difficulty of obtaining power measurements recommends exposing on-chip power meters and when possible structure specific power meters for cores, caches, and other structures. Just as hardware event counters provide a quantitative grounding for performance innovations, power meters are necessary for optimizing energy.
机译:本文采用严格的方法报告并分析了五种制程技术世代的实测芯片功率和性能,这些技术执行了61种不同的基准。我们测量具有代表性的Intel IA32处理器,其技术范围从130nm到32nm,同时它们执行以本机和托管语言编写的连续和并行基准测试。在此期间,硬件和软件发生了巨大变化:(1)硬件供应商交付了芯片多处理器而不是单处理器,并且独立地(2)软件开发人员越来越选择托管语言而不是本地语言。这些定量数据揭示了一些已知的和以前未曾观察到的硬件和软件趋势的程度。出现了两个主题。 (I)工作负载:本机工作负载的功率,性能和能耗趋势与托管工作负载不相近。例如,(a)i7(45)和i5(32)上的SPEC CPU2006本机基准测试比托管或可伸缩本机基准测试功耗要低得多; (b)托管运行时即使在运行单线程应用程序时也利用并行性。结果建议架构师在设计和评估节能硬件时始终包括本机和托管工作负载。 (II)体系结构:时钟缩放,微体系结构,同步多线程和芯片多处理器各自引发了各种各样的功率,性能和能量响应。由于种类繁多且难以获得功率测量结果,建议您公开片上功率计,并在可能的情况下,针对内核,高速缓存和其他结构使用特定于结构的功率计。正如硬件事件计数器为性能创新提供定量的基础一样,功率计对于优化能源也必不可少。

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