By Dr. Amith Singhee, Rob A. Rutenbar (auth.)
As VLSI know-how strikes to the nanometer scale for transistor characteristic sizes, the effect of producing imperfections bring about huge diversifications within the circuit functionality. conventional CAD instruments should not well-equipped to address this situation, due to the fact they don't version this statistical nature of the circuit parameters and performances, or in the event that they do, the present strategies are usually over-simplified or intractably sluggish. Novel Algorithms for quick Statistical research of Scaled Circuits attracts upon principles for attacking parallel difficulties in different technical fields, similar to computational finance, computing device studying and actuarial chance, and synthesizes them with leading edge assaults for the matter area of built-in circuits. the result's a suite of novel ideas to difficulties of effective statistical research of circuits within the nanometer regime. particularly, Novel Algorithms for speedy Statistical research of Scaled Circuits makes 3 contributions:
1) SiLVR, a nonlinear reaction floor modeling and performance-driven dimensionality aid technique, that instantly captures the designer’s perception into the circuit habit, by way of extracting quantitative measures of relative international sensitivities and nonlinear correlation.
2) quickly Monte Carlo simulation of circuits utilizing quasi-Monte Carlo, exhibiting speedups of two× to 50× over commonplace Monte Carlo.
3) Statistical blockade, a good strategy for sampling infrequent occasions and estimating their likelihood distribution utilizing restrict effects from severe worth thought, utilized to excessive replication circuits like SRAM cells.
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