ALEA: Fine-Grain Energy Profiling with Basic Block Sampling
- Submitting institution
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Queen's University of Belfast
- Unit of assessment
- 12 - Engineering
- Output identifier
- 80896692
- Type
- E - Conference contribution
- DOI
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10.1109/PACT.2015.16
- Title of conference / published proceedings
- Proceedings of the 24th International Conference on Parallel Architectures and Compilation Techniques (PACT)
- First page
- 87
- Volume
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- Issue
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- ISSN
- -
- Open access status
- -
- Month of publication
- October
- Year of publication
- 2015
- URL
-
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- Supplementary information
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- Request cross-referral to
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- 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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2
- Research group(s)
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C - Electrical and Electronic
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Published in the top IEEE and ACM conference in the field, this paper was the first to solve the problem of limited accuracy and sampling granularity of power sensing instruments in computing systems. A culmination of effort funded by the EPSRC ALEA project (EP/L000055/1), this work successfully modelled and measured power variation in commercial hardware, with accuracy two orders of magnitude finer than the state of the art. ALEA provided unprecedented insight into how energy is consumed in modern, complex servers. The tool presented in the paper is now under evaluation for future product integration by ARM.
- Author contribution statement
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- Non-English
- No
- English abstract
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