Improving GNN-based accelerator design automation with meta learning

Author:

Bai Yunsheng1,Sohrabizadeh Atefeh1,Sun Yizhou1,Cong Jason1

Affiliation:

1. University of California

Publisher

ACM

Reference21 articles.

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3. C. Finn etal 2017. Model-agnostic meta-learning for fast adaptation of deep networks. In ICML. PMLR 1126--1135. C. Finn et al. 2017. Model-agnostic meta-learning for fast adaptation of deep networks. In ICML. PMLR 1126--1135.

4. T. Hospedales etal 2020. Meta-learning in neural networks: A survey. arXiv preprint arXiv:2004.05439 (2020). T. Hospedales et al. 2020. Meta-learning in neural networks: A survey. arXiv preprint arXiv:2004.05439 (2020).

5. In-Datacenter Performance Analysis of a Tensor Processing Unit

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Robust GNN-Based Representation Learning for HLS;2023 IEEE/ACM International Conference on Computer Aided Design (ICCAD);2023-10-28

2. Democratizing Domain-Specific Computing;Communications of the ACM;2022-12-20

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