Confluence of AI/ML with EDA and Software Engineering

Investments into AI/ML to solve EDA problems with ever-increasing complexities of chip-design is starting to come to light. Recent product announcements like the DSO.ai from Synopsys revolutionizes chip design by massively scaling exploration of options in design workflows. Similarly, there are many applications in production solving different challenges in areas like verification, place & route, dfm etc., that have harnessed the power of AI/ML, Big-Data and Compute to provide a new set of tools and techniques for EDA to address both existing and new challenges. Not only do these technologies aid EDA, they are also helping us address challenges during software engineering development of these complex EDA products. By harnessing the data from code, tests, and bugs one can now improve product quality, improve productivity, and provide greater customer experience. In my talk I will be also going over such applications that are in production. With such potential, companies now need to build good data strategies to harness these benefits across their organizations. They will also need to invest in good data and AI/ML infrastructures to expedite building these solutions. It is now time to have data generate algorithms instead of the other way around! While these investments are starting to come to fruition, semiconductor design industry is still in the early stages and future promise is very alluring and exciting. Keynote Speaker: Arun Venkatachar - Vice President, Artificial Intelligence and Central Engineering , Synopsys