EDA methodologies, techniques and tools are unique in that they approach problems in terms of levels of abstraction, which gives us the power to work on complex problems from a high-level representation. We see complex systems as hierarchies of interacting components. This is reflected in our second strength: the modeling of very large systems by extracting their key behaviors in efficient representations for simulation.
The EDA industry also excels at developing techniques to solve large, complex optimization problems. And we are willing to tackle the black art of synthesis.
These key techniques of abstraction, extraction, optimization and synthesis from the EDA toolbox can be used in a broader context than just for electronic systems design. They are also applicable to other problems characterized by the complex behavior of large numbers of interacting components, in fields as diverse as routing systems for vehicular traffic, drug design, biology and health care. I believe that EDA has a great opportunity in the next decade to apply the tools we have developed for electronic systems design to these and other complex problems.
I think there may be as much, or perhaps even more opportunity these days in applying the skills and methodologies that honed in EDA–abstraction, extraction, optimization, and synthesis–to other fields that would benefit from richer modeling and automation.
This is not to say that we don’t remain interested in assisting EDA startups. Ever since they passed Moore’s Law, the electronic systems design problem continues to get more interesting every year and established firms are continually forced to redesign their product every two to three years to keep up with the semiconductor roadmap. But many other fields languish for the lack of these same techniques applied in an appropriate fashion.