1. [Publications](/publications) 2. DREAMPlace: Deep Learning Toolkit-Enabled GPU Acceleration for Modern VLSI Placement # DREAMPlace: Deep Learning Toolkit-Enabled GPU Acceleration for Modern VLSI Placement ![](/sites/default/files/styles/wide/public/publications/DREAMPlace_Capture_0.PNG?itok=8DOG6J_Q) Placement for very-large-scale integrated (VLSI) circuits is one of the most important steps for design closure. We propose a novel GPU-accelerated placement framework DREAMPlace, by casting the analytical placement problem equivalently to training a neural network. Implemented on top of a widely-adopted deep learning toolkit PyTorch, with customized key kernels for wirelength and density computations, DREAMPlace can achieve around 40× speedup in global placement without quality degradation compared to the state-of-the-art multi-threaded placer RePlAce. We believe this work shall open up new directions for revisiting classical EDA problems with advancements in AI hardware and software. ## Authors Yibo Lin (Peking University) Zixuan Jiang (UT-Austin) Jiaqi Gu (UT-Austin) Wuxi Li (Xilinx) Shounak Dhar (Intel) Mark Haoxing Ren (NVIDIA) [Brucek Khailany](/person/brucek-khailany) David Z. Pan (UT-Austin) ## Publication Date Monday, June 22, 2020 ## Published in [IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (…](https://ieeexplore.ieee.org/document/9122053) ## Research Area [Algorithms and Numerical Methods](/research-area/algorithms) [Artificial Intelligence and Machine Learning ](/research-area/machine-learning-artificial-intelligence) [Circuits and VLSI Design](/research-area/circuits) ## Award 2021 IEEE Transactions on Computer-Aided Design Donald O. Pederson Best Paper Award ## Copyright This material is posted here with permission of the IEEE. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to .