A new era of EDA powered by AI

For decades, Siemens has been deploying AI, at-scale, for computer chip design and manufacturing to help our customers deliver better products to people all across the globe. This white paper touches briefly on the development of our EDA software with artificial intelligence and machine learning, looking at some solution examples.

AI is integral to closing the semiconductor engineering gap

Society is demanding technology that is smaller, more efficient and faster, requiring ever-increasing volumes of semiconductor-enabled products and systems. And, as new IC process nodes and packaging technologies are introduced to address this demand, the complexity of designing, manufacturing and implementing integrated circuits (ICs), advanced IC packaging and printed circuit board (PCB)-based systems also increases exponentially. Software-defined and silicon-enabled systems are needed to enable continuing innovation and growth. Traditional scaling approaches are not keeping up and this is now leading to a resource gap in the industry.

AI is integral to closing the semiconductor engineering gap

The horizon for systems in which semiconductors are put to work is also expanding as manufacturers are bringing traditionally siloed domains together, such as mechanical and electrical and hardware and software, while working to unify systems capabilities for operations, networking, power management, security, monitoring, learning, verification, validation, and testing across domains.

While semiconductor design activity is growing, universities are not graduating enough semiconductor engineers who can make the chips for tomorrow’s technology. Current engineers are either retiring or seeking other careers. Because of this gap in education, skills and talent, solutions are needed that deliver orders of magnitude improvement, not percentages, to keep up with market demand.