Calibre Stress Correction analyzes and corrects distortion of the deep trenches cut through 3D stacks for advanced memory devices.
Calibre Stress Correction conducts full-chip trench shift prediction and executes the required shape alignment. Both the machine learning engine and the stress correction modeling engine can handle billions of trench shifts for full-chip usage.
Calibre Stress Correction is equipped with a neural network machine learning (ML) model that learns historical trench shift data from previous tape-out regardless of the complicated cause of the shift. ML model learning provides a straightforward way to predict the shift values for stress correction on a new layout with similar design rules and the same process.
Calibre Stress Correction performs shift prediction by using a compact physical model when the previous shifting information is unavailable. The shift values can be predicted based on the physical parameters in the model and the surrounding layout information without any requirement from the previous shift measurements.
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Across all process nodes and design styles, the Calibre toolsuite delivers accurate, efficient, comprehensive IC verification and optimization, while minimizing resource usage and tapeout schedules.