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CircuitNet: An Open-Source Dataset for Machine Learning Applications in Electronic Design Automation (EDA)

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arxiv 2208.01040 v4 pith:RU4SJYWV submitted 2022-08-01 cs.LG

classification cs.LG
keywords designautomationcircuitnetdatasetdatasetselectroniclargelearning
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The electronic design automation (EDA) community has been actively exploring machine learning (ML) for very large-scale integrated computer-aided design (VLSI CAD). Many studies explored learning-based techniques for cross-stage prediction tasks in the design flow to achieve faster design convergence. Although building ML models usually requires a large amount of data, most studies can only generate small internal datasets for validation because of the lack of large public datasets. In this essay, we present the first open-source dataset called CircuitNet for ML tasks in VLSI CAD.

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Cited by 1 Pith paper

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  1. ForgeEDA: A Comprehensive Multimodal Dataset for Advancing EDA

    cs.AR 2025-05 conditional novelty 5.0 of 10

    ForgeEDA introduces a large multimodal circuit dataset spanning RTL code, post-mapping netlists, placed netlists, and AIGs, with small benchmark experiments on synthesis tools and AI4EDA models.

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