Data-driven power modeling and monitoring via hardware performance counter tracking

IF 3.7 2区 计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE
Sergio Mazzola , Gabriele Ara , Thomas Benz , Björn Forsberg , Tommaso Cucinotta , Luca Benini
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引用次数: 0

Abstract

Energy-centric design is paramount in the current embedded computing era: use cases require increasingly high performance at an affordable power budget, often under real-time constraints. Hardware heterogeneity and parallelism help address the efficiency challenge, but greatly complicate online power consumption assessments, which are essential for dynamic hardware and software stack adaptations. We introduce a novel power modeling methodology with state-of-the-art accuracy, low overhead, and high responsiveness, whose implementation does not rely on microarchitectural details. Our methodology identifies the Performance Monitoring Counters (PMCs) with the highest linear correlation to the power consumption of each hardware sub-system, for each Dynamic Voltage and Frequency Scaling (DVFS) state. The individual, simple models are composed into a complete model that effectively describes the power consumption of the whole system, achieving high accuracy and low overhead. Our evaluation reports an average estimation error of 7.5% for power consumption and 1.3% for energy. We integrate these models in the Linux kernel with Runmeter, an open-source, PMC-based monitoring framework. Runmeter manages PMC sampling and processing, enabling the execution of our power models at runtime. With a worst-case time overhead of only 0.7%, Runmeter provides responsive and accurate power measurements directly in the kernel. This information can be employed for actuation policies in workload-aware DVFS and power-aware, closed-loop task scheduling.
通过硬件性能计数器跟踪数据驱动的电源建模和监控
以能源为中心的设计在当前的嵌入式计算时代是至关重要的:用例需要在可承受的功率预算下越来越高的性能,通常是在实时限制下。硬件异构性和并行性有助于解决效率挑战,但会使在线功耗评估变得非常复杂,而在线功耗评估对于动态硬件和软件堆栈适应至关重要。我们介绍了一种新颖的功率建模方法,它具有最先进的精度、低开销和高响应性,其实现不依赖于微架构细节。我们的方法确定了性能监控计数器(pmc)与每个硬件子系统的功耗在每个动态电压和频率缩放(DVFS)状态下具有最高的线性相关性。单个的、简单的模型被组合成一个完整的模型,有效地描述了整个系统的功耗,实现了高精度和低开销。我们的评估报告平均估计误差为7.5%的电力消耗和1.3%的能源。我们将这些模型与Runmeter(一个开源的、基于pmc的监控框架)集成到Linux内核中。Runmeter管理PMC采样和处理,使我们的功率模型在运行时执行。由于最坏情况时间开销仅为0.7%,Runmeter直接在内核中提供响应性和精确的功率测量。此信息可用于工作负载感知的DVFS和功率感知的闭环任务调度中的驱动策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Systems Architecture
Journal of Systems Architecture 工程技术-计算机:硬件
CiteScore
8.70
自引率
15.60%
发文量
226
审稿时长
46 days
期刊介绍: The Journal of Systems Architecture: Embedded Software Design (JSA) is a journal covering all design and architectural aspects related to embedded systems and software. It ranges from the microarchitecture level via the system software level up to the application-specific architecture level. Aspects such as real-time systems, operating systems, FPGA programming, programming languages, communications (limited to analysis and the software stack), mobile systems, parallel and distributed architectures as well as additional subjects in the computer and system architecture area will fall within the scope of this journal. Technology will not be a main focus, but its use and relevance to particular designs will be. Case studies are welcome but must contribute more than just a design for a particular piece of software. Design automation of such systems including methodologies, techniques and tools for their design as well as novel designs of software components fall within the scope of this journal. Novel applications that use embedded systems are also central in this journal. While hardware is not a part of this journal hardware/software co-design methods that consider interplay between software and hardware components with and emphasis on software are also relevant here.
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