Novel Algorithms for Fast Statistical Analysis of Scaled Circuits
Singhee, Amith; Rutenbar, Rob A.
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Description for Novel Algorithms for Fast Statistical Analysis of Scaled Circuits
Hardback. This book presents novel solutions to problems of efficient statistical analysis of circuits in the nanometer regime. It draws on theories from a wide variety of scientific fields and applies them to parallel problems in numerous other fields. Series: Lecture Notes in Electrical Engineering. Num Pages: 210 pages, biography. BIC Classification: TJFC. Category: (P) Professional & Vocational. Dimension: 234 x 156 x 12. Weight in Grams: 1050.
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 ... Read more
Show LessProduct Details
Format
Hardback
Publication date
2009
Publisher
Springer Netherlands
Number of pages
210
Condition
New
Series
Lecture Notes in Electrical Engineering
Number of Pages
195
Place of Publication
Dordrecht, Netherlands
ISBN
9789048130993
SKU
V9789048130993
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15
Reviews for Novel Algorithms for Fast Statistical Analysis of Scaled Circuits
The Statistical Blockade method proposed by Singhee and Rutenbar will make a significant impact on the design of next-generation digital integrated circuits. It has the potential to dramatically reduce simulation time compared to a traditional Monte Carlo approach. Their award winning work is well received by industry and has influenced research directions in academia. - Prof. Anantha Chandrakasan, MIT