As the electronics industry looks to develop advanced solutions for 5G/6G and data centre applications, Keysight’s new suite of EDA tools leverages AI, machine learning (ML), and Python integrations to significantly reduce design time for complex RF and chiplet products.
Keysight’s EDA 2025 software addresses critical challenges in the development lifecycle by enhancing data manipulation, integration, and control of best-in-class simulators, allowing engineers to build more efficient workflows seamlessly across multiple tools.
AI-enhanced workflows and high-performance computing further reduce the time-to-insight, enabling engineers to move from simulation to verification and compliance.
For simulating fast digital interconnects, the software is equipped with end-to-end component models and measurements that conform to digital standards, providing an efficient and high-accuracy digital twin for complex digital electronic design challenges.
Core benefits of the EDA 2025 software portfolio include:
RF Circuit Design: Accelerates RF design cycles through open, automatable workflows featuring Python integration and multi-domain simulation. Additionally, the Python toolkit enables engineers to quickly consolidate measured load pull data from various files and formats into a single, cohesive dataset to train fast AI/ML models.
High-speed Digital Design: Creates precise digital twins for complex standard-specific SerDes designs, including Universal Chiplet Interconnect Express (UCIe) chiplets, memory, USB, and PCIe, with the Advanced Design System (ADS) 2025 release.
Device Modelling and Characterisation: Reduces model re-centring time by 10X through AI/ML capabilities in the IC-CAP 2025 release, while Python integrations streamline and automate the modelling process.
According to Nilesh Kamdar, EDA Design & Verification General Manager at Keysight, "AI is transforming how engineers approach complex design challenges. Automating traditionally time-intensive tasks enables engineers to focus on innovation rather than repetitive refinements, resulting in real productivity gains. The foundation for the practical application of AI and ML is first having an open, interoperable workflow and then providing turn-key solutions tuned for specific applications. It's a fascinating time, and AI and ML will undoubtedly be a huge driver of design innovation in the future."
“With this release, engineers can easily import data from measurements or swept simulations to train neural network models, which then execute very quickly in subsequent simulations,” said Stephen Slater, Director of Product Management at Keysight. “This unlocks new possibilities for abstracting and co-optimising large parts of the RF design together, dramatically accelerating the development process.”
