Progress of Placement Optimization for Accelerating VLSI Physical Design
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 …
affects the design cycle. Despite extensive prior research on placement, achieving fast and …
Large circuit models: opportunities and challenges
Within the electronic design automation (EDA) domain, artificial intelligence (AI)-driven
solutions have emerged as formidable tools, yet they typically augment rather than redefine …
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
Within the Electronic Design Automation (EDA) domain, AI-driven solutions have emerged
as formidable tools, yet they typically augment rather than redefine existing methodologies …
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 …
indicate that in unsupervised federated continual learning (UFCL), the limited model …
The dark side: Security concerns in machine learning for EDA
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 …
through new electronic design automation (EDA) methodologies. In recent years, many …
Embracing Privacy, Robustness, and Efficiency with Trustworthy Federated Learning on Edge Devices
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 …
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
The growing integrated circuit complexity has led to a compelling need for design efficiency
improvement through new electronic design automation (EDA) methodologies. In recent …
improvement through new electronic design automation (EDA) methodologies. In recent …
Deep learning for routability
Abstract Design rule checking (DRC) clean is a fundamental chip manufacturing
requirement. However, achieving this is increasingly challenging with the advance of …
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 …
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 …
of complementary metal-oxide semiconductor (CMOS) technology scaling have presented …