Russian Federation
The paper discusses a neural AI assistant designed to automate floorplanning in Cadence Virtuoso. The module generates optimized placement variants based on past project data and defined PPA constraints, reducing early design time by 25–40%.
floorplanning, VLSI design, AI-assisted EDA, machine learning, Cadence Virtuoso, placement optimization, PPA metrics, reinforcement learning, physical design, multi-objective optimization
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