TY - JOUR
T1 - Xplace: An Extremely Fast and Extensible Placement Framework
T2 - An Extremely Fast and Extensible Placement Framework
AU - Liu, Lixin
AU - Fu, Bangqi
AU - Lin, Shiju
AU - Liu, Jinwei
AU - Young, Evangeline F.Y.
AU - Wong, Martin D.F.
N1 - This work was supported in part by ACCESS - AI Chip Center for Emerging Smart Systems, Hong Kong SAR.
PY - 2024/6
Y1 - 2024/6
N2 - Placement serves as a fundamental step in VLSI physical design. Recently, GPU-based placer DREAMPlace [1] demonstrated its superiority over CPU-based placers. In this work, we develop an extremely fast GPU-accelerated placer Xplace which considers factors at operator-level optimization. Xplace achieves around 2x speedup with better-solution quality compared to DREAMPlace. We also plug a novel Fourier neural network into Xplace as an extension. Besides, we enable Xplace to handle the detailed-routability-driven placement problem and demonstrate its superiority in terms of quality and performance. We believe this work not only proposes an extremely fast and extensible placement framework but also illustrates a possibility of incorporating a neural network component into a GPU-accelerated analytical placer. The source code of Xplace is released on GitHub.
AB - Placement serves as a fundamental step in VLSI physical design. Recently, GPU-based placer DREAMPlace [1] demonstrated its superiority over CPU-based placers. In this work, we develop an extremely fast GPU-accelerated placer Xplace which considers factors at operator-level optimization. Xplace achieves around 2x speedup with better-solution quality compared to DREAMPlace. We also plug a novel Fourier neural network into Xplace as an extension. Besides, we enable Xplace to handle the detailed-routability-driven placement problem and demonstrate its superiority in terms of quality and performance. We believe this work not only proposes an extremely fast and extensible placement framework but also illustrates a possibility of incorporating a neural network component into a GPU-accelerated analytical placer. The source code of Xplace is released on GitHub.
KW - GPU acceleration
KW - neural network
KW - physical design
KW - placement
KW - routability optimization
UR - http://www.scopus.com/inward/record.url?scp=85181579294&partnerID=8YFLogxK
U2 - 10.1109/TCAD.2023.3346291
DO - 10.1109/TCAD.2023.3346291
M3 - Journal article
AN - SCOPUS:85181579294
SN - 0278-0070
VL - 43
SP - 1872
EP - 1885
JO - IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
JF - IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
IS - 6
ER -