Machine learning for electronic design automation: A survey

G Huang, J Hu, Y He, J Liu, M Ma, Z Shen… - ACM Transactions on …, 2021 - dl.acm.org
With the down-scaling of CMOS technology, the design complexity of very large-scale
integrated is increasing. Although the application of machine learning (ML) techniques in …

MLCAD: A survey of research in machine learning for CAD keynote paper

M Rapp, H Amrouch, Y Lin, B Yu… - … on Computer-Aided …, 2021 - ieeexplore.ieee.org
Due to the increasing size of integrated circuits (ICs), their design and optimization phases
(ie, computer-aided design, CAD) grow increasingly complex. At design time, a large design …

FI-SHAP: explanation of time series forecasting and improvement of feature engineering based on boosting algorithm

Y Zhang, O Petrosian, J Liu, R Ma, K Krinkin - Proceedings of SAI …, 2022 - Springer
Boosting Algorithm (BA) is state-of-the-art in major competitions, especially in the M4 and
M5 time series forecasting competitions. However, the use of BA requires tedious feature …

Autodmp: Automated dreamplace-based macro placement

A Agnesina, P Rajvanshi, T Yang, G Pradipta… - Proceedings of the …, 2023 - dl.acm.org
Macro placement is a critical very large-scale integration (VLSI) physical design problem
that significantly impacts the design power-performance-area (PPA) metrics. This paper …

How good is your verilog rtl code? a quick answer from machine learning

P Sengupta, A Tyagi, Y Chen, J Hu - Proceedings of the 41st IEEE/ACM …, 2022 - dl.acm.org
Hardware Description Language (HDL) is a common entry point for designing digital circuits.
Differences in HDL coding styles and design choices may lead to considerably different …

PTPT: Physical design tool parameter tuning via multi-objective Bayesian optimization

H Geng, T Chen, Y Ma, B Zhu… - IEEE transactions on …, 2022 - ieeexplore.ieee.org
Physical design flow through associated electronic design automation (EDA) tools plays an
imperative role in the advanced integrated circuit design. Mostly, the parameters fed into …

Preplacement net length and timing estimation by customized graph neural network

Z Xie, R Liang, X Xu, J Hu, CC Chang… - … on Computer-Aided …, 2022 - ieeexplore.ieee.org
Net length is a key proxy metric for optimizing timing and power across various stages of a
standard digital design flow. However, the bulk of net length information is not available until …

Metrics2. 1 and flow tuning in the ieee ceda robust design flow and openroad iccad special session paper

J Jung, AB Kahng, S Kim… - 2021 IEEE/ACM …, 2021 - ieeexplore.ieee.org
In today's RTL-to-GDS flow domain, there is a lack of standards for reporting of design and
tool metrics. Moreover, each tool or engine has its own set of parameters that can change …

MasterRTL: A Pre-Synthesis PPA Estimation Framework for Any RTL Design

W Fang, Y Lu, S Liu, Q Zhang, C Xu… - 2023 IEEE/ACM …, 2023 - ieeexplore.ieee.org
In modern VLSI design flow, the register-transfer level (RTL) stage is a critical point, where
designers define precise design behavior with hardware description languages (HDLs) like …

The dawn of ai-native eda: Promises and challenges of large circuit models

L Chen, Y Chen, Z Chu, W Fang, TY Ho… - arXiv preprint arXiv …, 2024 - arxiv.org
Within the Electronic Design Automation (EDA) domain, AI-driven solutions have emerged
as formidable tools, yet they typically augment rather than redefine existing methodologies …