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RISA: accurate and efficient placement routability modeling

Chih-liang Eric Cheng·1994·International Conference on Computer Aided Design
DOI 10.5555/191326.191632

Abstract

The prevalence of net list synthesis tools raises great concern on routability of cell placement created with state-of-the-art placement techniques. In this paper, an accurate and efficient placement routability modeling technique is proposed and incorporated into the prevailing simulated annealing approach. This accurate and efficient modeling is based on the supply versus demand analysis of routing resource over an array of regions on a chip. Vertical and horizontal routability is analyzed separately due to the bias of routing resource in multiple-metal-layer ASIC designs. A special technique on net bounding box partitioning is also proposed and critical to the accuracy of this modeling at the presence of mega cells, which tend to cause local routing congestion. By incorporating this efficient modeling into the cost function of simulated annealing, experiments conducted on small to large industrial designs indicate that placement routability evaluated with a global router is greatly improved as a result of the proposed accurate modeling.

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Metadata

Authors
Cheng, C.-L. E.
Venue
International Conference on Computer Aided Design
Published
1994-11-06
Pages
690-695
ISSN
1933-7760 (ISSN-L)
DOI
10.5555/191326.191632
OpenAlex
W2111104699
Cited by
204
References
0
FWCI
4.63
Type
conference paper
Language
en
Open access
closed

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CoChat. (2026). Citation check: RISA: accurate and efficient placement routability modeling. https://app.cochat.ai/papers/10.5555/191326.191632
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Cheng, C.-L. E. (1994). RISA: accurate and efficient placement routability modeling. International Conference on Computer Aided Design. https://doi.org/10.5555/191326.191632

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.