Article

A Predictive Model for Dynamic Microarchitectural Adaptivity Control

Authors:

Christophe Dubach,

Timothy M. Jones,

Edwin V. Bonilla,

Michael F. P. O'BoyleAuthors Info & Claims

MICRO '43: Proceedings of the 2010 43rd Annual IEEE/ACM International Symposium on Microarchitecture

Pages 485 - 496

https://doi.org/10.1109/MICRO.2010.14

Published: 04 December 2010 Publication History

Abstract

Adaptive micro architectures are a promising solution for designing high-performance, power-efficient microprocessors. They offer the ability to tailor computational resources to the specific requirements of different programs or program phases. They have the potential to adapt the hardware cost-effectively at runtime to any application's needs. However, one of the key challenges is how to dynamically determine the best architecture configuration at any given time, for any new workload. This paper proposes a novel control mechanism based on a predictive model for micro architectural adaptivity control. This model is able to efficiently control adaptivity by monitoring the behaviour of an application's different phases at runtime. We show that using this model on SPEC 2000, we double the energy/performance efficiency of the processor when compared to the best static configuration tuned for the whole benchmark suite. This represents 74\% of the improvement available if we knew the best micro architecture for each program phase ahead of time. In addition, we show that the overheads associated with the implementation of our scheme have a negligible impact on performance and power.

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https://dl.acm.org/doi/10.1145/3494523
Iskandar VSalama CTaher M(2022)Dynamic thread mapping for power-efficient many-core systems under performance constraintsMicroprocessors & Microsystems10.1016/j.micpro.2022.10461493:COnline publication date: 1-Sep-2022
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Pal SAmarnath AFeng SO'Boyle MDreslinski RDubach C(2021)SparseAdapt: Runtime Control for Sparse Linear Algebra on a Reconfigurable AcceleratorMICRO-54: 54th Annual IEEE/ACM International Symposium on Microarchitecture10.1145/3466752.3480134(1005-1021)Online publication date: 18-Oct-2021
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Index Terms

A Predictive Model for Dynamic Microarchitectural Adaptivity Control

Recommendations

Efficiency trends and limits from comprehensive microarchitectural adaptivity
ASPLOS '08

Increasing demand for power-efficient, high-performance computing requires tuning applications and/or the underlying hardware to improve the mapping between workload heterogeneity and computational resources. To assess the potential benefits of hardware ...
Dynamic microarchitectural adaptation using machine learning

Adaptive microarchitectures are a promising solution for designing high-performance, power-efficient microprocessors. They offer the ability to tailor computational resources to the specific requirements of different programs or program phases. They ...
Dynamic branch prediction and control speculation

Branch prediction schemes have become an integral part of today's superscalar processors. They are one of the key issues in enhancing the performance of processors. Pipeline stalls due to conditional branches are one of the most significant impediments ...

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cover image ACM Conferences

MICRO '43: Proceedings of the 2010 43rd Annual IEEE/ACM International Symposium on Microarchitecture

December 2010

542 pages

ISBN:9780769542997

Sponsors

SIGMICRO: ACM Special Interest Group on Microarchitectural Research and Processing

Publisher

IEEE Computer Society

United States

Publication History

Published: 04 December 2010

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Overall Acceptance Rate 484 of 2,242 submissions, 22%

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Cited By

Wu NXie Y(2022)A Survey of Machine Learning for Computer Architecture and SystemsACM Computing Surveys10.1145/349452355:3(1-39)Online publication date: 3-Feb-2022
https://dl.acm.org/doi/10.1145/3494523
Iskandar VSalama CTaher M(2022)Dynamic thread mapping for power-efficient many-core systems under performance constraintsMicroprocessors & Microsystems10.1016/j.micpro.2022.10461493:COnline publication date: 1-Sep-2022
https://dl.acm.org/doi/10.1016/j.micpro.2022.104614
Pal SAmarnath AFeng SO'Boyle MDreslinski RDubach C(2021)SparseAdapt: Runtime Control for Sparse Linear Algebra on a Reconfigurable AcceleratorMICRO-54: 54th Annual IEEE/ACM International Symposium on Microarchitecture10.1145/3466752.3480134(1005-1021)Online publication date: 18-Oct-2021
https://dl.acm.org/doi/10.1145/3466752.3480134
Rodrigues MGuimarães BPereira FKandemir MJimborean AMoseley T(2019)Generation of in-bounds inputs for arrays in memory-unsafe languagesProceedings of the 2019 IEEE/ACM International Symposium on Code Generation and Optimization10.5555/3314872.3314890(136-148)Online publication date: 16-Feb-2019
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Ding YMishra NHoffmann HManne SHunter HAltman E(2019)Generative and multi-phase learning for computer systems optimizationProceedings of the 46th International Symposium on Computer Architecture10.1145/3307650.3326633(39-52)Online publication date: 22-Jun-2019
https://dl.acm.org/doi/10.1145/3307650.3326633
Tarsa SChowdhury RSebot JChinya GGaur JSankaranarayanan KLin CChappell RSinghal RWang HManne SHunter HAltman E(2019)Post-silicon CPU adaptation made practical using machine learningProceedings of the 46th International Symposium on Computer Architecture10.1145/3307650.3322267(14-26)Online publication date: 22-Jun-2019
https://dl.acm.org/doi/10.1145/3307650.3322267
Rahmani ADonyanavard BMück TMoazzemi KJantsch AMutlu ODutt N(2018)SPECTRACM SIGPLAN Notices10.1145/3296957.317319953:2(169-183)Online publication date: 19-Mar-2018
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Mishra NImes CLafferty JHoffmann H(2018)CALOREEACM SIGPLAN Notices10.1145/3296957.317318453:2(184-198)Online publication date: 19-Mar-2018
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Rahmani ADonyanavard BMück TMoazzemi KJantsch AMutlu ODutt NShen XTuck JBianchini RSarkar V(2018)SPECTRProceedings of the Twenty-Third International Conference on Architectural Support for Programming Languages and Operating Systems10.1145/3173162.3173199(169-183)Online publication date: 19-Mar-2018
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Mishra NImes CLafferty JHoffmann HShen XTuck JBianchini RSarkar V(2018)CALOREEProceedings of the Twenty-Third International Conference on Architectural Support for Programming Languages and Operating Systems10.1145/3173162.3173184(184-198)Online publication date: 19-Mar-2018
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