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CDCTree: novel obstacle-avoiding routing tree construction based on current driven circuit model
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Source Asia and South Pacific Design Automation Conference archive
Proceedings of the 2006 Asia and South Pacific Design Automation Conference table of contents
Yokohama, Japan
SESSION: New routing techniques table of contents
Pages: 630 - 635  
Year of Publication: 2006
ISBN:0-7803-9451-8
Authors
Yiyu Shi  UCLA, Los Angeles, California
Tong Jing  Tsinghua University, Beijing, P.R. China
Lei He  UCLA, Los Angeles, California
Zhe Feng  Tsinghua University, Beijing, P.R. China
Xianlong Hong  Tsinghua University, Beijing, P.R. China
Sponsors
: IEEE Circuits and Systems Society
SIGDA: ACM Special Interest Group on Design Automation
IEICE ESS : Institute of Electronics, Information and Communication Engineers, Engineering Sciences Society
IPSJ SIG-SLDM : Information Processing Society of Japan, SIG System LSI Design Methodology
Publisher
IEEE Press  Piscataway, NJ, USA
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Downloads (6 Weeks): 4,   Downloads (12 Months): 13,   Citation Count: 5
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ABSTRACT

Routing tree construction is a fundamental problem in modern VLSI design. In this paper we propose CDC-Tree, an Obstacle-Avoiding Rectilinear Steiner Minimum Tree (OARSMT) heuristic algorithm to construct an OARSMT. CDC-Tree is based on the current driven circuit (CDC) model mapped from an escape graph. The circuit structure comes from the topology of the escape graph, with each edge replaced by a resistor indicating the wirelength of that edge. By performing DC analysis on the circuit and selecting the edges according to the current distribution to construct an OARSMT, the wirelength of the resulting tree is short. The algorithm has been implemented and tested on cases of different scales and with different shapes of obstacles. Experiments show that CDCTree can achieve shorter wirelength than the existing best algorithm, An-OARSMan, when the terminal number of a net is less than 50.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Yiyu Shi: colleagues
Tong Jing: colleagues
Lei He: colleagues
Zhe Feng: colleagues
Xianlong Hong: colleagues