Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Course Outline
Introduction to AI in Semiconductor Design Automation
- Overview of AI applications in EDA tools
- Challenges and opportunities in AI-driven design automation
- Case studies of successful AI integration in semiconductor design
Machine Learning for Design Optimization
- Introduction to machine learning techniques for design optimization
- Feature selection and model training for EDA tools
- Practical applications in design rule checking and layout optimization
Neural Networks in Chip Verification
- Understanding neural networks and their role in chip verification
- Implementing neural networks for error detection and correction
- Case studies on the use of neural networks in EDA tools
Advanced AI Techniques for Power and Performance Optimization
- Exploring AI techniques for power and performance analysis
- Integrating AI models to optimize power efficiency
- Real-world examples of AI-driven performance enhancement
EDA Tool Customization with AI
- Customizing EDA tools with AI for specific design challenges
- Developing AI plugins and modules for existing EDA platforms
- Hands-on practice with popular EDA tools and AI integration
Future Trends in AI for Semiconductor Design
- Emerging AI technologies in semiconductor design automation
- Future directions in AI-driven EDA tools
- Preparing for advancements in AI and semiconductor industries
Summary and Next Steps
Requirements
- Experience in semiconductor design and EDA tools
- Advanced knowledge of AI and machine learning techniques
- Familiarity with neural networks
Audience
- Semiconductor design engineers
- AI specialists in semiconductor industries
- EDA tool developers
21 Hours
Testimonials (2)
the ML ecosystem not only MLFlow but Optuna, hyperops, docker , docker-compose
Guillaume GAUTIER - OLEA MEDICAL
Course - MLflow
I enjoyed participating in the Kubeflow training, which was held remotely. This training allowed me to consolidate my knowledge for AWS services, K8s, all the devOps tools around Kubeflow which are the necessary bases to properly tackle the subject. I wanted to thank Malawski Marcin for his patience and professionalism for training and advice on best practices. Malawski approaches the subject from different angles, different deployment tools Ansible, EKS kubectl, Terraform. Now I am definitely convinced that I am going into the right field of application.
