Large-scale, high-fidelity analog circuit datasets generated using industrial Cadence Spectre simulations, enabling reproducible AI-driven circuit design research.
Two complementary datasets covering different scales and design hierarchies β both open-source under MIT license.
The largest foundry-grade analog circuit dataset to date. Contains over 1,000,000 Cadence Spectre-simulated circuit instances across 20 expert-designed topologies, with process fidelity, noise characteristics, and layout-dependent behavior of foundry-calibrated flows — far surpassing symbolic SPICE alternatives.
Spanning core analog/RF building blocks
The foundational dataset and benchmark that enabled the FALCON research program. AICircuit introduces a comprehensive multi-level dataset of 7 core analog/RF circuits and 2 complex wireless transceiver systems, simulated with Cadence Spectre. It evaluates MLPs, Transformers, SVRs, and other ML models for circuit design tasks — establishing rigorous baselines for AI-driven analog design.
From individual components to complete transceiver systems