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Traditional diagnosis of defects is based on an assumed fault model. A failing chip is diagnosed to find the subset of faults that can best explain the failure. This paper illustrates a link between this traditional perspective of diagnosis and a new perspective where diagnosis is seen as a form of data learning. We explain that both defect diagnosis and data learning are solving so-called ill-posed...
As device and interconnect feature sizes shrink, silicon chip behavior becomes more sensitive to process and environmental variations and uncertainties. During the design phase, many effects of these variations are not explicitly or accurately modeled and simulated, either because doing so is too expensive or because the designer is not aware that a particular effect can significantly alter chip timing...
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