OCB (Open Circuit Benchmark)

Introduced by Dong et al. in CktGNN: Circuit Graph Neural Network for Electronic Design Automation

OCB contains two graph datasets, Ckt-Bench-101 and Ckt-Bench-301, for representation learning over analog circuits. Ckt-Bench-101 and Ckt-Bench-301 contain graphs (DAGs) that represent analog circuits and provide their corresponding graph-level properties: DC gain (Gain), bandwidth (BW), phase margin (PM),Figure of Merit (FoM), which characterize the circuit performance.

  • Motivation: Facilitate research in representation learning and automation of analog circuits.
  • Tasks: graph-level prediction/regression; analog circuit search (ACS).
  • Node features: discrete feature that characterize device type (e.g. capacitor); and continues feature of the device (e.g. capacitance).
  • First open source benchmark for graph learning in analog circuits.


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