基于工作负载分解的动态电压和频率缩放

Kihwan Choi, R. Soma, Massoud Pedram
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引用次数: 226

摘要

本文提出了一种称为“工作负载分解”的技术,将CPU工作负载分解为片内和片外两部分。片上工作负载表示在CPU中执行指令所需的CPU时钟周期,而片外工作负载捕获执行外部内存事务所需的外部内存访问时钟周期的数量。当与动态电压和频率缩放(DVFS)技术相结合以最大限度地减少能耗时,这种工作负载分解方法可以节省更多的能源。工作负载分解本身是在运行时根据性能监视单元(PMU)报告的统计数据执行的,不需要应用程序分析或编译器支持。我们在BitsyX平台(ADS公司生产的基于Intel pxa255的平台)上实现了采用工作负载分解技术的DVFS,并进行了详细的能量测量。这些测量表明,对于许多广泛使用的软件应用程序,在满足用户指定的时间约束的情况下,可以实现内存受限程序80%的CPU节能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Dynamic voltage and frequency scaling based on workload decomposition
This paper presents a technique called "workload decomposition" in which the CPU workload is decomposed in two parts: on-chip and off-chip. The on-chip workload signifies the CPU clock cycles that are required to execute instructions in the CPU whereas the off-chip workload captures the number of external memory access clock cycles that are required to perform external memory transactions. When combined with a dynamic voltage and frequency scaling (DVFS) technique to minimize the energy consumption, this workload decomposition method results in higher energy savings. The workload decomposition itself is performed at run time based on statistics reported by a performance monitoring unit (PMU) without a need for application profiling or compiler support. We have implemented the proposed DVFS with workload decomposition technique on the BitsyX platform, an Intel PXA255-based platform manufactured by ADS Inc., and performed detailed energy measurements. These measurements show that, for a number of widely used software applications, a CPU energy saving of 80% can be achieved for memory-bound programs while satisfying the user-specified timing constraints.
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