News Center
Keysight Unveils Machine Learning ToolkitKeysight Unveils Machine Learning Toolkit to Accelerate Device Modeling and PDK DevelopmentArtificial intelligence/Machine Learning-driven modeling reduces time-to-market for faster Design Technology Co-Optimization development and accelerates model parameter extraction for advanced nodes, RF, and power applications Keysight announced the release of the new Machine Learning Toolkit in the latest Keysight Device Modeling Software Suite. This new solution reduces model development and extraction time from weeks to hours, enabling faster Process Design Kit delivery and Design Technology Co-Optimization applications. The semiconductor industry is undergoing rapid transformation, driven by advanced architectures such as gate-all-around transistors, wide-bandgap materials such as GaN and SiC, and heterogeneous integration strategies including chiplets and 3D stacking. While these innovations drive performance, they also create complex modeling and parameter extraction challenges. Traditional workflows rely on physics-based compact models and manual parameter extraction, forcing engineers to adjust hundreds of interconnected parameters across multiple operating conditions, a process that can take weeks and often struggles to achieve optimal results. With increasingly tight schedules, faster, more predictive, and automated artificial intelligence/Machine Learning-driven modeling solutions are now essential. Keysight’s new Machine Learning Toolkit, featuring an ML optimizer, auto-extraction flows, and utilities within Device Modeling MBP 2026 tackles these challenges by introducing a framework that combines advanced neural network architectures with ML-based optimization. Using this toolkit, auto-extraction can reduce the parameter extraction steps from over 200 to fewer than 10, accelerating PDK delivery, automating DTCO, and speeding up time-to-market. Key Features and Benefits:
Nilesh Kamdar, General Manager of Keysight EDA, said: “AI/ML is fundamentally transforming the traditional workflows and methodologies of compact modeling. With the new Machine Learning Toolkit, we empower our customers to deliver more predictive, higher-quality models in significantly less time — accelerating PDK development and helping them keep pace with rapidly evolving semiconductor technologies.” By leveraging AI/ML-driven modeling, Keysight enables semiconductor companies to accelerate innovation, reduce development risk, and maintain a competitive edge in a rapidly evolving market. For more details, visit Keysight Device Modeling Solutions. Additional enhancements across other Keysight device modeling solutions include:
Source: Keysight media announcement | |
