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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