Software-controlled Processor Stalls for Time and Energy Efficient Data Locality Optimization

Abstract : Data locality optimization is a well-known goal when handling programs that must run as fast as possible or use a minimum amount of energy. However, usual techniques never address the significant impact of numerous stalled processor cycles that may occur when consecutive load and store instructions are accessing the same memory location. We show that two versions of the same program may exhibit similar memory performance, while performing very differently regarding their execution times because of the stalled processor cycles generated by many pipeline hazards. We propose a new programming structure called ''xfor'', enabling the explicit control of the way data locality is optimized in a program and thus, to control the amount of stalled processor cycles. We show the benefits of xfor regarding execution time and energy saving.
Type de document :
Communication dans un congrès
International Conference on Embedded Computer Systems: Architectures, Modeling and Simulation - SAMOS XIV, Jul 2014, Agios Konstantinos, Greece. 2014
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https://hal.inria.fr/hal-01003228
Contributeur : Philippe Clauss <>
Soumis le : mardi 10 juin 2014 - 11:13:38
Dernière modification le : mercredi 29 novembre 2017 - 15:59:59

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  • HAL Id : hal-01003228, version 1

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Philippe Clauss, Imen Fassi, Alexandra Jimborean. Software-controlled Processor Stalls for Time and Energy Efficient Data Locality Optimization. International Conference on Embedded Computer Systems: Architectures, Modeling and Simulation - SAMOS XIV, Jul 2014, Agios Konstantinos, Greece. 2014. 〈hal-01003228〉

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