DiffCkt uses three diffusion networks to predict amplifier component counts, topology, and transistor sizes from performance specifications, and reports 2.21x to 8365x higher generation efficiency than prior analog EDA tools.
Gcn-rl circuit designer: Transferable transistor sizing with graph neural networks and reinforcement learning,
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DiffCkt: A Diffusion Model-Based Hybrid Neural Network Framework for Automatic Transistor-Level Generation of Analog Circuits
DiffCkt uses three diffusion networks to predict amplifier component counts, topology, and transistor sizes from performance specifications, and reports 2.21x to 8365x higher generation efficiency than prior analog EDA tools.