Leveraging pre-silicon data to diagnose out-of-specification failures in mixed-signal circuits

摘要

Diagnosing out-of-specification failures in mixed-signal circuits has become increasingly challenging due to: (1) failures caused by interactions between input-signal conditions and design uncertainties, and (2) the need to identify critical input and uncertainty conditions that cause these regions. We propose a simulation-driven approach that first uses ensemble learning to extract if - then rules that naturally solve both problems. By ranking, pruning and clustering these rules, we then construct non-linear failure regions which can be directly employed for pre-silicon debug, as demonstrated on a phase-locked loop circuit. Furthermore, these regions can be used to guide test pattern generation and/or assist with post-silicon debug.