An optimal algorithm for approximate nearest neighbor searching fixed dimensions
Journal of the ACM (JACM)
Multidimensional binary search trees used for associative searching
Communications of the ACM
Remembrance of circuits past: macromodeling by data mining in large analog design spaces
Proceedings of the 39th annual Design Automation Conference
Support vector machines for analog circuit performance representation
Proceedings of the 40th annual Design Automation Conference
Robust analog/RF circuit design with projection-based posynomial modeling
Proceedings of the 2004 IEEE/ACM International conference on Computer-aided design
GA-SVM feasibility model and optimization kernel applied to analog IC design automation
Proceedings of the 17th ACM Great Lakes symposium on VLSI
On the Use of Hash Tables for Efficient Analog Circuit Synthesis
VLSID '08 Proceedings of the 21st International Conference on VLSI Design
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We present an efficient analog synthesis algorithm employing regression models of circuit matrices. Circuit matrix models achieve accurate and speedy synthesis of analog circuits. In this paper, synthesis is accelerated by eliminating numerous computations of the matrix elements during a synthesis run. Computations are avoided by reusing exact or nearby design points visited during previous synthesis iterations. Hashing and multidimensional nearest neighbor lookup are used in incremental evaluation of design solutions encountered during synthesis. Sensitivity of the design variables is considered for locating a neighboring solution. Neighbor lookup is efficiently performed using box-decomposition trees. The proposed method is used to synthesize three benchmark circuits. Results show that with hashing and neighbor lookup, synthesis is 6x--13x faster than with the use of matrix models alone.