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FastPlace: efficient analytical placement using cell shifting, iterative local refinement and a hybrid net model
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Source International Symposium on Physical Design archive
Proceedings of the 2004 international symposium on Physical design table of contents
Phoenix, Arizona, USA
SESSION: Placement techniques table of contents
Pages: 26 - 33  
Year of Publication: 2004
ISBN:1-58113-817-2
Authors
Natarajan Viswanathan  Iowa State University, Ames, IA
Chris Chong-Nuen Chu  Iowa State University, Ames, IA
Sponsors
ACM: Association for Computing Machinery
SIGDA: ACM Special Interest Group on Design Automation
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 6,   Downloads (12 Months): 29,   Citation Count: 42
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ABSTRACT

In this paper, we present FastPlace -- a fast, iterative, flat placement algorithm for large-scale standard cell designs. FastPlace is based on the quadratic placement approach. The quadratic approach formulates the wirelength minimization problem as a convex quadratic program, which can be solved efficiently by some analytical techniques. However it suffers from some drawbacks. First, the resulting placement has a lot of overlap among cells. Second, the resulting total wirelength may be long as the quadratic wirelength objective is only an indirect measure of the linear wirelength. Third, existing net models tend to create a lot of non-zero entries in the connectivity matrix, which slows down the quadratic program solver. To handle the above problems we propose: (1) An efficient Cell Shifting technique to remove cell overlap from the quadratic program solution and produce a global placement with even cell distribution. (2) An Iterative Local Refinement technique, to reduce the wirelength according to the half-perimeter measure. (3) A Hybrid Net Model which is a combination of the traditional clique and star models. This net model greatly reduces the number of non-zero entries in the connectivity matrix and results in a significant speedup of the solver. Experimental results show that FastPlace is on average 13.0 and 97.4 times faster than Capo and Dragon respectively. Correspondingly, the average wirelength is just 1.0% and 1.6% higher.


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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CITED BY  42

Collaborative Colleagues:
Natarajan Viswanathan: colleagues
Chris Chong-Nuen Chu: colleagues