Learning to Compare Hardware Designs for High-Level Synthesis-Reference-Cited by-同舟云学术

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Learning to Compare Hardware Designs for High-Level Synthesis

Published:2024-09-09 Issue: Volume:36 Page:1-7
ISSN:
Container-title:Proceedings of the 2024 ACM/IEEE International Symposium on Machine Learning for CAD
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Author:

Bai Yunsheng¹^ORCID,Sohrabizadeh Atefeh²^ORCID,Ding Zijian²^ORCID,Liang Rongjian³^ORCID,Li Weikai²^ORCID,Wang Ding²^ORCID,Ren Haoxing³^ORCID,Sun Yizhou²^ORCID,Cong Jason²^ORCID

Affiliation:

1. NVIDIA Corporation and University of California, Los Angeles

2. University of California, Los Angeles

3. NVIDIA Corporation

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3670474.3685940

Reference41 articles.

1. 2023. Ranked Choice Voting. https://www.fairvote.org/rcv. Accessed: May 22, 2024.

2. AMD. 2024. AMD/Xilinx. https://www.xilinx.com/products/design-tools/vitis/vitis-hls.html. Accessed: June 1, 2024.

3. Towards a Comprehensive Benchmark for High-Level Synthesis Targeted to FPGAs;Bai Yunsheng;Advances in Neural Information Processing Systems,2023

4. Curriculum learning

5. Learning to rank using gradient descent

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