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The problem of yield estimation and optimization of analog circuits is addressed in this paper. Given convex design-space constraints that define the feasible region for the design, we first linearize the feasible region by approximating it with linear constraints. Using the linear constraints approximating the feasible region, we make primarily two contributions in this paper—first we use the concept...
Evolutionary algorithms are popularly used methods to estimate yield for faster convergence. Monte-Carlo is the method of choice for accurate yield estimation. Standard Monte-Carlo methods suffer from huge computational burden even though they are very accurate. Monte-Carlo efficiency is not high enough to use impartial for Analog Yield Optimization. Population initialization is a decisive task in...
The Monte-Carlo method is the method of choice for accurate yield estimation. Standard Monte-Carlo methods suffer from a huge computational burden even though they are very accurate. Recently a Monte-Carlo method was proposed for the parametric yield estimation of digital integrated circuits [13] that achieves significant computational savings at no loss of accuracy by focusing on those statistical...
We propose a novel framework to solve the combined retiming/gate sizing problem in the context of optimization of acyclic pipelines. The adjustment of sizes to gates in a combinational circuit is a continuous problem, solvable by a variety of convex optimization tools provided the delay model for each gate is placed in a convex framework. Retiming is a discrete problem since it involves physically...
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