6533b85afe1ef96bd12ba004

RESEARCH PRODUCT

Performance and energy optimisation in CPUs through fuzzy knowledge representation

Lucian VintanUgo FioreAdrian FloreaArpad GellertPaolo Zanetti

subject

Information Systems and ManagementComputer scienceDesign space exploration02 engineering and technologyFuzzy logicMulti-objective optimizationTheoretical Computer ScienceProcessor design knowledgeArtificial IntelligenceEnergy savingSuperscalar0202 electrical engineering electronic engineering information engineeringAutomatic design space exploration Processor design knowledge Superscalar microarchitecture Dynamic value prediction Energy savingProcessor design05 social sciencesProcess (computing)050301 educationEnergy consumptionComputer Science ApplicationsMicroarchitectureComputer engineeringControl and Systems EngineeringDynamic value prediction020201 artificial intelligence & image processingAutomatic design space exploration; Processor design knowledge; Superscalar microarchitecture; Dynamic value prediction; Energy savingSuperscalar microarchitecture0503 educationAutomatic design space explorationSoftwareEnergy (signal processing)

description

Abstract This paper presents an automatic design space exploration using processor design knowledge for the multi-objective optimisation of a superscalar microarchitecture enhanced with selective load value prediction (SLVP). We introduced new important SLVP parameters and determined their influence regarding performance, energy consumption, and thermal dissipation. We significantly enlarged initial processor design knowledge expressed through fuzzy rules and we analysed its role in the process of automatic design space exploration. The proposed fuzzy rules improve the diversity and quality of solutions, and the convergence speed of the design space exploration process. Experiments show that a set-associative prediction table is more effective than a direct mapped table and that 86% of the configurations in the Pareto front use multiple values per load. In conclusion, our experiments show that integrating an SLVP module into a superscalar microarchitecture is hardware feasible; in comparison with the case without SLVP, performance is better, energy consumption is lower, and the temperatures inside the chip decreases, remaining below 75 °C.

yearjournalcountryeditionlanguage
2019-02-01Information Sciences
https://doi.org/10.1016/j.ins.2018.03.029