Accurate and stable run-time power modeling for mobile and embedded CPUs
- Submitting institution
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University of Southampton
- Unit of assessment
- 12 - Engineering
- Output identifier
- 20808262
- Type
- D - Journal article
- DOI
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10.1109/TCAD.2016.2562920
- Title of journal
- IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
- Article number
- -
- First page
- 106
- Volume
- 36
- Issue
- 1
- ISSN
- 0278-0070
- Open access status
- Compliant
- Month of publication
- May
- Year of publication
- 2016
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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6
- Research group(s)
-
-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This industrially co-authored paper proposed the first statistically sound approach to run-time power estimation on mobile/embedded CPUs, validated extensively with real hardware and workloads. Tutorials were run at MICRO'15, ISPASS'16, training >40 academics/engineers. A tool for using the approach was released open-source (http://bit.ly/2RxcBxE), used by Arm, and integrated into the popular gem5 simulator (http://bit.ly/2AyO41n). The paper was nominated for IEEE TCAD Best Paper award, and led to an invited talk at Arm Research Summit (http://bit.ly/33YNBkN) 2017. Direct knowledge transfer was supported by the first author undertaking internships with Arm and Intel (totalling >1yr), and employment by Arm on graduation.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -