Run-time power estimation in high performance microprocessors

By Russ Joseph, Margaret Martonosi. ISLPED'01: Proceedings of the 2001 International Symposium on Low Power Electronics and Design (IEEE Cat. No.01TH8581), 2001

308 citations recorded by the source corpus.

Subfields: Automotive Engineering, Electrical and Electronic Engineering, Hardware and Architecture

View Paper: https://www.semanticscholar.org/paper/3460b2c80fd5b921e792a934569cdebbbd3fae8f

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Citations in the corpus

Full-System Power Analysis and Modeling for Server Environments (2006, background): “Time-multiplexing [15], [16] can address this pr oblem, but at the expense of some loss of coverage.”
Single-ISA heterogeneous multi-core architectures: the potential for processor power reduction (2003, background): “35 micron late-release Pentium Pro [18, 22] for the EV6).”
Real time power estimation and thread scheduling via performance counters (2009, methodology): “The first method estimates power consumption based on monitoring usage of the functional units [11, 16].”
AutoFL: Enabling Heterogeneity-Aware Energy Efficient Federated Learning (2021, methodology): “When the CPU is selected as the execution target, Ecomp is calculated using a utilization-based CPU power model [13, 54, 63, 138], as in (1), where Ei core is the power consumed by”
Runtime power monitoring in high-end processors: methodology and empirical data (2003, methodology): “Or instead, one might use a more conceptual interpretation similar to [16] in which categories such as issue, execution, memory, fetch and reorder-related are considered.”
Estimation of energy consumption in machine learning (2019, methodology): “[76] Instruction Current Analytical Energy Profiling CPU Model Yes [10] Hardware Analytical Analytical Power, Energy, Perf Simu data CPU Theoretical Yes [80] Hardware Analytical Transition-sensitive Energy/Power Simulation CPU, f units Theoretical – [44] Hardware Real Heuristics Power PMC, sim data ”
Data Center Energy Consumption Modeling: A Survey (2016, methodology): “According to [141] performance counters can provide good power estimation results and they have estimated power within 2% of the actual power.”
ECOSystem: managing energy as a first class operating system resource (2002, methodology): “Ideally, one would like to charge differently for different processor behavior (e.g., various types of instructions or the frequency of cache misses, etc.) and this would be compatible with our modeling approach (e.g., by using event counters [2, 17 ]).”
Into the wild: Studying real user activity patterns to guide power optimizations for mobile architectures (2009, background): “Several researchers use performance counters to estimate the power consumption of both high-performance and embedded microprocessors [4, 5, 9, 18, 19].”
Accurate online power estimation and automatic battery behavior based power model generation for smartphones (2010, background): “We then explain the development of training software to exercise the relevant power management and activity states of hardware components with signiﬁcant power consumptions.”