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OpenABC-D is a large-scale labeled dataset generated by synthesizing open source hardware IPs. This dataset can be used for various graph level prediction problems in chip design.
This is work-in-progress (WIP) refactored implementation of "Retreival-guided Reinforcement Learning for Boolean Circuit Minimization" work published in ICLR 2024.