Article

Power prediction for intel XScale® processors using performance monitoring unit events

Authors:

Gilberto Contreras,

Margaret MartonosiAuthors Info & Claims

ISLPED '05: Proceedings of the 2005 international symposium on Low power electronics and design

Pages 221 - 226

https://doi.org/10.1145/1077603.1077657

Published: 08 August 2005 Publication History

Abstract

This paper demonstrates a first-order, linear power estimation model ha uses performance counters to estimate run-time CPU and memory power consumption of the Intel PXA255 processor. Our model uses a set of power weights that map hardware performance counter values to processor and memory power consumption. Power weights are derived offline once per processor voltage and frequency configuration using parameter estimation echniques. They can be applied in a dynamic voltage/frequency scaling environment by setting six descriptive parameters. We have tested our model using a wide selection of benchmarks including SPEC2000, Java CDC and Java CLDC programming environments. The accuracy is quite good; average estimated power consumption is within 4% of he measured average CPU power consumption. We believe such power estimation schemes can serve as a foundation for intelligent, power-aware embedded systems tha dynamically adapt to the device's power consumption

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Cited By

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https://doi.org/10.1109/JVA60410.2023.00019
Chinnakkonda DRajamani KSrinivas M(2022)Architecture slack exploitation for phase classification and performance estimation in server-class processorsJournal of Parallel and Distributed Computing10.1016/j.jpdc.2022.06.017169(157-170)Online publication date: Nov-2022
https://doi.org/10.1016/j.jpdc.2022.06.017
Soriano TNovo DBenoit P(2021)An FPGA-based Emulation Platform for Edge Computing Node Design Exploration2021 IEEE International Workshop on Rapid System Prototyping (RSP)10.1109/RSP53691.2021.9806230(8-14)Online publication date: 14-Oct-2021
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Index Terms

Power prediction for intel XScale® processors using performance monitoring unit events
1. Computer systems organization
  1. Embedded and cyber-physical systems
  2. Real-time systems
2. Software and its engineering
  1. Software notations and tools
    1. Compilers
      1. Runtime environments

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Published In

cover image ACM Conferences

ISLPED '05: Proceedings of the 2005 international symposium on Low power electronics and design

August 2005

400 pages

ISBN:1595931376

DOI:10.1145/1077603

General Chairs:
Kaushik Roy
Purdue University
,
Vivek Tiwari
Intel

Copyright © 2005 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 08 August 2005

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ISLPED05

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ISLPED05: International Symposium on Low Power Electronics and Design

August 8 - 10, 2005

CA, San Diego, USA

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Overall Acceptance Rate 398 of 1,159 submissions, 34%

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Kosar T(2023)Towards Zero-Carbon Data Movement at the HPC and Cloud Data Centers2023 IEEE John Vincent Atanasoff International Symposium on Modern Computing (JVA)10.1109/JVA60410.2023.00019(54-55)Online publication date: 5-Jul-2023
https://doi.org/10.1109/JVA60410.2023.00019
Chinnakkonda DRajamani KSrinivas M(2022)Architecture slack exploitation for phase classification and performance estimation in server-class processorsJournal of Parallel and Distributed Computing10.1016/j.jpdc.2022.06.017169(157-170)Online publication date: Nov-2022
https://doi.org/10.1016/j.jpdc.2022.06.017
Soriano TNovo DBenoit P(2021)An FPGA-based Emulation Platform for Edge Computing Node Design Exploration2021 IEEE International Workshop on Rapid System Prototyping (RSP)10.1109/RSP53691.2021.9806230(8-14)Online publication date: 14-Oct-2021
https://doi.org/10.1109/RSP53691.2021.9806230
Barboza EJacob SKetkar MKishinevsky MGratz PHu J(2021)Automatic Microprocessor Performance Bug Detection2021 IEEE International Symposium on High-Performance Computer Architecture (HPCA)10.1109/HPCA51647.2021.00053(545-556)Online publication date: Feb-2021
https://doi.org/10.1109/HPCA51647.2021.00053
Wu XTaylor V(2021)Utilizing ensemble learning for performance and power modeling and improvement of parallel cancer deep learning CANDLE benchmarksConcurrency and Computation: Practice and Experience10.1002/cpe.651635:15Online publication date: 22-Jul-2021
https://doi.org/10.1002/cpe.6516
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Ou ZChen JZhang YDong YYuan YWang Z(2020)Power modeling for Phytium FT-2000+/64 multi-core architectureProceedings of the Workshop on Benchmarking in the Datacenter10.1145/3380868.3398199(1-7)Online publication date: 22-Feb-2020
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Karsten MBarghi S(2020)User-level ThreadingProceedings of the ACM on Measurement and Analysis of Computing Systems10.1145/33794834:1(1-30)Online publication date: 5-Jun-2020
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Yang LHajiesmaili MSitaraman RWierman AMallada EWong W(2020)Online Linear Optimization with Inventory Management ConstraintsProceedings of the ACM on Measurement and Analysis of Computing Systems10.1145/33794824:1(1-29)Online publication date: 5-Jun-2020
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