A High-accurate Multi-objective Exploration Framework for Design Space of CPU
Author:
Affiliation:
1. Chinese Academy of Sciences,SKLP, Institute of Computing Technology,Beijing,China
Funder
Research and Development
National Natural Science Foundation of China
Youth Innovation Promotion Association
Beijing Nova Program
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10247654/10247655/10247790.pdf?arnumber=10247790
Reference18 articles.
1. A statistically rigorous approach for improving simulation methodology
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1. CoNAX: Towards Comprehensive Co-Design Neural Architecture Search Using HW Abstractions;2024 IEEE 35th International Conference on Application-specific Systems, Architectures and Processors (ASAP);2024-07-24
2. A Transfer Learning Framework for High-Accurate Cross-Workload Design Space Exploration of CPU;2023 IEEE/ACM International Conference on Computer Aided Design (ICCAD);2023-10-28
3. MoDSE: A High-Accurate Multi-Objective Design Space Exploration Framework for CPU Microarchitectures;IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems;2023
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