A Transfer Learning Framework for High-Accurate Cross-Workload Design Space Exploration of CPU-Reference-Cited by-同舟云学术

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A Transfer Learning Framework for High-Accurate Cross-Workload Design Space Exploration of CPU

Published:2023-10-28 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE/ACM International Conference on Computer Aided Design (ICCAD)
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Author:

Wang Duo¹,Yan Mingyu¹,Teng Yihan¹,Han Dengke¹,Dang Haoran¹,Ye Xiaochun¹,Fan Dongrui¹

Affiliation:

1. Institute of Computing Technology, Chinese Academy of Sciences,SKLP,Beijing,China

Funder

National Key Research and Development Program

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10323590/10323543/10323840.pdf?arnumber=10323840

Reference29 articles.

1. Accurate and efficient processor performance prediction via regression tree based modeling

2. A statistically rigorous approach for improving simulation methodology

3. SimPoint 3.0: Faster and More Flexible Program Phase Analysis;hamerly;J Instruction-Level Parallelism,2005

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

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Boosted regression for predicting CPU utilization in the cloud with periodicity;The Journal of Supercomputing;2024-08-18

2. Recent Trends in 3D Reconstruction of General Non‐Rigid Scenes;Computer Graphics Forum;2024-04-30

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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