Home News AI Reshapes Device Modeling: An Exclusive Look at Keysight’s ML Optimizer

AI Reshapes Device Modeling: An Exclusive Look at Keysight’s ML Optimizer

2025-06-04

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With the rapid development of semiconductor technology, device models are becoming increasingly complex, and compact model parameter extraction has become a major challenge facing the industry. Traditional optimization algorithms are plagued by unclear gradient changes and are easily trapped in local optimality, but the final extraction results are unsatisfactory. In addition, there are a large number of interrelated parameters in modern semiconductor models, which makes traditional methods even less efficient. Modeling engineers often need to break down the parameter extraction process into multiple lengthy and tedious sub-steps. The entire process may take days or even weeks, seriously restricting development progress.

Machine Learning Revolutionizes Parameter Extraction

To break through this technical bottleneck, Keysight Technologies (Keysight) has launched a global optimizer based on machine learning, ML Optimizer, which brings a revolutionary solution to semiconductor parameter extraction!

Compared with traditional methods, it can simultaneously process massive graphics and parameters in a single step, greatly simplifying the parameter extraction process, and greatly shortening the original long parameter extraction cycle from several days to just a few hours, greatly improving work efficiency.

In addition, ML Optimizer is particularly good at dealing with non-convex parameter spaces. With advanced machine learning algorithms, it can break through the limitations of traditional methods, find the global optimal solution more accurately, significantly improve the accuracy of parameter extraction and the consistency of overall fitting, and provide a solid guarantee for the accurate construction of semiconductor device models.

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