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An Effective Routing Refinement Algorithm Based on Incremental Replacement and Rerouting
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AI
DOI：10.1109/TCSII.2023.3306036.png)
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Abstract
En 中文
To reduce the design complexity of physical design, placement and routing are commonly regarded as two problems. However, since the correlation and aims of placement and routing are not totally consistent, the complete separation of the two stages might limit the final routing quality. To narrow the gap between the two stages and improve the routing solution, this brief proposes an effective routing refinement algorithm based on incremental replacement and rerouting. We first propose an R-tree-based parallel net rerouting scheme to remove redundant routing segments, which offers more precise information for the subsequent cell replacement. Then, two location prediction methods are proposed and performed alternately in adjacent rounds of cell replacement. The first method predicts the cell locations sequentially based on the current routing results, while the second one adopts a gradient-descent-based method to predict the cell locations simultaneously from a more global perspective. Finally, we present an A*-based partial rerouting to generate the new routing results, followed by a simulated-annealing-based acceptance strategy to judge whether to accept the new routing results. Compared with the champion of the ICCAD 2020 contest and the state-of-the-art works, experimental results show that our algorithm is effective and efficient.
Keywords:
Routing
Prediction methods
Prediction algorithms
Three-dimensional displays
Table lookup
Simulated annealing
Physical design
placement
global routing
cell replacement
rerouting
Journal
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4.9
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8.8K
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2.5W