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Mathematics Novel Algorithms for Fast Statistical Analysis of Scaled Circuits

Posted on 2010-04-13




Name:Mathematics Novel Algorithms for Fast Statistical Analysis of Scaled Circuits
ASIN/ISBN:9048130999
Language:English
File size:2.3 Mb
Publish Date: 2009-08-07
ISBN: 9048130999
Pages: 195 pages
File Type: PDF
File Size: 2,3 MB
Other Info: Springer
   Mathematics Novel Algorithms for Fast Statistical Analysis of Scaled Circuits

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Amith Singhee, Rob A. Rutenbar, "Novel Algorithms for Fast Statistical Analysis of Scaled Circuits"

As VLSI technology moves to the nanometer scale for transistor feature sizes, the impact of manufacturing imperfections result in large variations in the circuit performance. Traditional CAD tools are not well-equipped to handle this scenario, since they do not model this statistical nature of the circuit parameters and performances, or if they do, the existing techniques tend to be over-simplified or intractably slow. Novel Algorithms for Fast Statistical Analysis of Scaled Circuits draws upon ideas for attacking parallel problems in other technical fields, such as computational finance, machine learning and actuarial risk, and synthesizes them with innovative attacks for the problem domain of integrated circuits. The result is a set of novel solutions to problems of efficient statistical analysis of circuits in the nanometer regime.

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