Sensitivity Analysis for Active Sampling, with Applications to the Simulation of Analog Circuits

2024/05/13 by Reda Chhaibi, Fabrice Gamboa, Chhaibi, Reda +9
Computer Science · Engineering · #Analog and Mixed-Signal Circuit Design #Applications (stat.AP) #Control Systems and Identification #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Methodology (stat.ME) #VLSI and Analog Circuit Testing

paper · pdf · doi:10.48550/arxiv.2405.07971

openalex publication_date 2024/05/13 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

We propose an active sampling flow, with the use-case of simulating the impact of combined variations on analog circuits. In such a context, given the large number of parameters, it is difficult to fit a surrogate model and to efficiently explore the space of design features. By combining a drastic dimension reduction using sensitivity analysis and Bayesian surrogate modeling, we obtain a flexible active sampling flow. On synthetic and real datasets, this flow outperforms the usual Monte-Carlo sampling which often forms the foundation of design space exploration.

Related

• Methodology for Biasing Random Simulation for Rapid Coverage of Corner Cases in AMS Designs
• GLOVA: Global and Local Variation-Aware Analog Circuit Design with Risk-Sensitive Reinforcement Learning
• Adaptively Sampling via Regional Variance-Based Sensitivities
• Global sensitivity metrics from active subspaces
• RobustAnalog: Fast Variation-Aware Analog Circuit Design Via Multi-task RL