A High-accurate Multi-objective Exploration Framework for Design Space of CPU

To accelerate time-consuming multi-objective design space exploration of CPU, previous work trains prediction models using a set of performance metrics derived from few simulations, then predicts the rest. Unfortunately, the low accuracy of models limits the exploration effect, and how to achieve a...

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Vydané v:	2023 60th ACM/IEEE Design Automation Conference (DAC) s. 1 - 6
Hlavní autori:	Wang, Duo, Yan, Mingyu, Liu, Xin, Zou, Mo, Liu, Tianyu, Li, Wenming, Ye, Xiaochun, Fan, Dongrui
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 09.07.2023
Predmet:	CPU Microarchitecture Design automation Design Space Exploration Measurement Microarchitecture Multi-objective Exploration Pareto Hypervolume Pareto optimization Prediction algorithms Prediction Model Predictive models Space exploration
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