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Duration 21 hours
Course Outline
Introduction to AI in Semiconductor Design Automation
- Overview of AI applications within EDA tools
- Challenges and opportunities presented by AI-driven design automation
- Case studies highlighting successful AI integration in semiconductor design
Machine Learning for Design Optimization
- Foundational concepts of machine learning techniques for design optimization
- Feature selection and model training specifically for EDA tools
- Practical applications in design rule checking and layout optimization
Neural Networks in Chip Verification
- Understanding neural networks and their specific role in chip verification
- Deploying neural networks for error identification and correction
- Case studies demonstrating the use of neural networks within EDA tools
Advanced AI Techniques for Power and Performance Optimization
- Investigating AI techniques for power and performance analysis
- Integrating AI models to maximize power efficiency
- Real-world examples of AI-enhanced performance improvements
EDA Tool Customization with AI
- Tailoring EDA tools using AI to address specific design challenges
- Creating AI plugins and modules for established EDA platforms
- Hands-on practice with popular EDA tools and AI integration
Future Trends in AI for Semiconductor Design
- Emerging AI technologies shaping semiconductor design automation
- Future trajectories for AI-driven EDA tools
- Preparing for future advancements in AI and the semiconductor industry
Summary and Next Steps
Requirements
- Practical experience with semiconductor design and EDA tools
- Proficient understanding of AI and machine learning methodologies
- Proficiency with neural network architectures
Target Audience
- Semiconductor design engineers
- AI specialists working within the semiconductor sector
- EDA tool developers
Testimonials (2)
Getting people that never used AI some repetition in prompting and people that do use AI to consider different methods to using it.
Matthew Gay - Tarsus Pharmaceuticals
Course - Artificial Intelligence (AI) Overview
Working from first principles in a focused way, and moving to applying case studies within the same day
