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lvzhengyang
macroplacement
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9ef9154f
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9ef9154f
authored
Jun 11, 2022
by
ZhiangWang033
Committed by
GitHub
Jun 11, 2022
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@@ -96,7 +96,17 @@ while allowing soft macros (standard-cell clusters) to also find good locations.
## **Related Links**
-
R. Cheng and J. Yan, "On joint learning for solving placement and routing in chip design'',
*Proc. NeurIPS*
, 2021.
\[
[
paper
](
https://arxiv.org/pdf/2111.00234v1.pdf
)
\]
[
Code
](
https://github.com/Thinklab-SJTU/EDA-AI
)
-
F. -C. Chang, Y. -W. Tseng, Y. -W. Yu, S. -R. Lee, A. Cioba et al.,
*Proc. NeurIPS*
, 2021.
\[
[
paper
](
https://arxiv.org/pdf/2111.00234v1.pdf
)
\]
\[
[
Code
](
https://github.com/Thinklab-SJTU/EDA-AI
)
\]
-
F. -C. Chang, Y. -W. Tseng, Y. -W. Yu, S. -R. Lee, A. Cioba
,
et al.,
"Flexible multiple-objective reinforcement learning for chip placement",
*arXiv:2204.06407*
, 2022.
[
paper
](
https://arxiv.org/pdf/2204.06407.pdf
)
*arXiv:2204.06407*
, 2022.
\[
[
paper
](
https://arxiv.org/pdf/2204.06407.pdf
)
\]
-
S. Guadarrama, S. Yue, T. Boyd, J. Jiang, W. Joe, et al.,
"Circuit training: an open-source framework for generating chip floor plans with distributed deep reinforcement learning",
2021.
\[
[
code
](
https://github.com/google-research/circuit_training
)
\]
-
A. Mirhoseini, A. Goldie, M. Yazgan, J. Jiang, E. Songhori, et al.,
"A graph placement methodology for fast chip design",
*Nature*
, 594(7862) (2021), pp. 207-212.
\[
[
paper
](
https://www.nature.com/articles/s41586-021-03544-w
)
\]
-
A. Mirhoseini, A. Goldie, M. Yazgan, J. Jiang, E. Songhori, et al.,
"Chip Placement with Deep Reinforcement Learning",
*arXiv:2004.10746*
, 2020.
\[
[
paper
](
https://arxiv.org/pdf/2004.10746.pdf
)
\]
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