Invited Paper: The Inevitability of AI Infusion Into Design Closure and Signoff

SoC design teams embrace new technologies and methodologies that bring clear value. Given this, future infusion of AI into design closure and signoff is inevitable. Predictive AI models help focus the application of last-mile incremental optimizations (sizing, placement and routing) to achieve timing and noise closure; successful examples range from routing-free crosstalk prediction to timing/power evaluation in early RTL development. Design closure becomes more efficient when “imperfect but fast” ML inferencing is used to filter out potential violations, which can then be passed to golden analysis tools. Learning methods also improve the design process in many ways, ranging from smarter PVT corner selection to predicting the CPU and memory usage of signoff tools. At a higher level, AI will help design teams learn to avoid design trajectories that lead to time-consuming closure and signoff iterations. This talk will provide a broad overview of directions in which AI will inevitably improve the cost and efficiency of signoff in the coming years.