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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Bibliographic Details

Published in:	2023 60th ACM/IEEE Design Automation Conference (DAC) pp. 1 - 6
Main Authors:	Wang, Duo, Yan, Mingyu, Liu, Xin, Zou, Mo, Liu, Tianyu, Li, Wenming, Ye, Xiaochun, Fan, Dongrui
Format:	Conference Proceeding
Language:	English
Published:	IEEE 09.07.2023
Subjects:	CPU Microarchitecture Design automation Design Space Exploration Measurement Microarchitecture Multi-objective Exploration Pareto Hypervolume Pareto optimization Prediction algorithms Prediction Model Predictive models Space exploration
Online Access:	Get full text
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