Accelerate Functional Coverage Closure Using Co-simulation and Machine Learning

The course aims to teach participants how to accelerate functional coverage closure using co-simulation and machine learning techniques. The learning outcomes include understanding the basic concept and flow of a co-simulation based verification environment, learning about test selection in constrained randomized testing, and gaining knowledge about an autoencoder-based test selection system. The course will equip learners with the skills to implement machine learning solutions in the design and verification of complex systems, specifically focusing on 5G telecommunications systems. The teaching method involves a presentation covering examples and case studies. This course is intended for FPGA engineers, design verification engineers, and professionals working in the field of telecommunications who are interested in leveraging machine learning for functional coverage closure in complex designs.