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Quadratic placement revisited
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Source Annual ACM IEEE Design Automation Conference archive
Proceedings of the 34th annual Design Automation Conference table of contents
Anaheim, California, United States
Pages: 752 - 757  
Year of Publication: 1997
ISBN:0-89791-920-3
Authors
C. J. Alpert  IBM Austin Research Laboratory, Austin, TX
T. Chan  UCLA Mathematics Dept., Los Angeles, CA
D. J.-H. Huang  UCLA Computer Science Dept., Los Angeles, CA
I. Markov  UCLA Mathematics Dept., Los Angeles, CA
K. Yan  UCLA Computer Science Dept., Los Angeles, CA
Sponsors
EDAC : Electronic Design Automation Consortium
IEEE-CAS : Circuits & Systems
SIGDA: ACM Special Interest Group on Design Automation
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 9,   Downloads (12 Months): 41,   Citation Count: 10
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ABSTRACT

The "quadratic placement" methodology is rooted in [Module Placement Based on Resistive Network Optimization, Proud: A Sea-Of-Gate Placement Algorithm, A Combined Force and Cut Algorithm for Hierarchical VLSI Layout]and is reputedly used in many commercial and in-house tools forplacement of standard-cell and gate-array designs. The methodologyiterates between two basic steps: solving sparse systems oflinear equations, and repartitioning. This work dissects the implementationand motivations for quadratic placement. We firstshow that (i) Krylov subspace engines for solving sparse systemsof linear equations are more effective than the traditional successiveover-relaxation (SOR) engine [A Unified Approach to Partitioning and Placement] and (ii) order convergence criteriacan maintain solution quality while using substantially fewersolver iterations. We then discuss the motivations and relevanceof the quadratic placement approach, in the context of past and futurealgorithmic technology, performance requirements, and designmethodology. We provide evidence that the use of numerical linearsystems solvers with quadratic wirelength objective may be due tothe pre-1990's weakness of min-cut partitioners, i.e., numerical engineswere needed to provide helpful hints to min-cut partitioners.Finally, we note emerging methodology drivers in deep-submicrondesign that may require new placement approaches to the placement problem.


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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C. J. Alpert, T. Chan, D. J.-H. Huang, I. Markov and K. Yan, "Quadratic Placement Revisited", Technical Report #970012, UCLA Computer Science Dept., March 1997.
 
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R. Barret, M. Berry, T. Chan et al "Templates for the Solution of Linear Systems: Building Blocks for Iterative Methods", SlAM 1995, http://netlib2, cs. utk. edu/linalg/html_templates/ Templates. html
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C. K. Cheng and E. S. Kuh. "Module Placement Based on Resistive Network Optimization", IEEE Trans. on CAD 3 (1984), pp. 218-225.
 
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W. Hackbush, "Iterative Solution of Large Sparse Systems" Springer Verlag, 1994.
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J. Kleinhans, G. Sigl, F. Johannes and K. Antreich, "GORDIAN: VLSI Placement by Quadratic Programming and Slicing Optimization", IEEE Trans. on CAD. 10(3) (1991) pp. 356-365.
 
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R. S. Tsay and E. Kuh, "A Unified Approach to Partitioning and Placement", IEEE Trans. on Circuits and Systems, 38(5) (1991), pp. 521-633.
 
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CITED BY  10

Collaborative Colleagues:
C. J. Alpert: colleagues
T. Chan: colleagues
D. J.-H. Huang: colleagues
I. Markov: colleagues
K. Yan: colleagues