Progress of Placement Optimization for Accelerating VLSI Physical Design

Y Qiu, Y Xing, X Zheng, P Gao, S Cai, X Xiong - Electronics, 2023 - mdpi.com
Placement is essential in very large-scale integration (VLSI) physical design, as it directly
affects the design cycle. Despite extensive prior research on placement, achieving fast and …

Large circuit models: opportunities and challenges

L Chen, Y Chen, Z Chu, W Fang, TY Ho… - Science China …, 2024 - Springer
Within the electronic design automation (EDA) domain, artificial intelligence (AI)-driven
solutions have emerged as formidable tools, yet they typically augment rather than redefine …

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 …

FedFRR: Federated Forgetting-Resistant Representation Learning

H Wang, J Sun, T Wo, X Liu - 2024 IEEE International …, 2024 - ieeexplore.ieee.org
Continuous learning faces the challenge of catastrophic forgetting. Our research findings
indicate that in unsupervised federated continual learning (UFCL), the limited model …

The dark side: Security concerns in machine learning for EDA

Z Xie, J Pan, CC Chang, Y Chen - arXiv preprint arXiv:2203.10597, 2022 - arxiv.org
The growing IC complexity has led to a compelling need for design efficiency improvement
through new electronic design automation (EDA) methodologies. In recent years, many …

Embracing Privacy, Robustness, and Efficiency with Trustworthy Federated Learning on Edge Devices

M Tang, J Sun, HH Li, Y Chen - 2024 IEEE Computer Society …, 2024 - ieeexplore.ieee.org
While Federated Learning (FL) offers a privacy guarantee as a promising distributed
learning paradigm, the robustness and efficiency issues hinder the practice of FL on …

The Dark Side: Security and Reliability Concerns in Machine Learning for EDA

Z Xie, J Pan, CC Chang, J Hu… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The growing integrated circuit complexity has led to a compelling need for design efficiency
improvement through new electronic design automation (EDA) methodologies. In recent …

Deep learning for routability

Z Xie, J Pan, CC Chang, R Liang, EC Barboza… - … learning applications in …, 2022 - Springer
Abstract Design rule checking (DRC) clean is a fundamental chip manufacturing
requirement. However, achieving this is increasingly challenging with the advance of …

Optimization of Area and Wirelength Using Hybrid BPSO Algorithm in VLSI Floorplan and Placement for IC Design

S Karimullah, D Vishnuvardhan, VK Gunjan… - Modern Approaches in …, 2024 - Springer
For hierarchical, building-block design methodologies, floorplanning is a crucial physical
design stage. As the size of the circuit grows, so does the intricacy of the circuitrises. To deal …

Data-Driven EDA: Harnessing the Power of Machine Learning for Chip Design

AB Chowdhury - 2024 - search.proquest.com
Over the years, the exponential increase in the complexity of chip design and the shrinking
of complementary metal-oxide semiconductor (CMOS) technology scaling have presented …