Keysight Radio Frequency Device Model Generator Adopted by Samsung Foundry
- New Python-based software accelerates the creation of circuit libraries for Samsung’s advanced radio frequency semiconductor process technologies
- Software empowers engineers to customize device modeling workflows that generate large volumes of data
- Workflow automation significantly reduces extraction time for today’s transistor and next-generation semiconductor device models for RF applications
Modeling today’s industry-standard RF fin field-effect transistors (FinFET) is a complex and time-consuming process involving massive amounts of data. With the IC-CAP MG software framework, Samsung’s RF modeling engineers can efficiently organize large volumes of data to save time extracting transistor models. The MG handles data management and all the details of simulating and displaying multi-device simulations, leaving engineers free to focus on creating and automating custom flows.
Built on Python 3, the MG software is part of Keysight’s flagship modeling platform, PathWave Device Modeling (IC-CAP). The software imports and organizes measured data and circuit netlists for various geometries and temperatures. In addition, the software automatically creates and efficiently simulates RF trend plots of key figures of merit based on user input.
All data, including trend plots, is available to build custom extraction flows through an intuitive and easy-to-use interface. The product enables efficient simulation and real-time tuning of multi-devices with complex RF sub-circuits, including netlists using layout parasitic extraction files. The MG software framework includes model verification and report generation.
Jongwook Kye, Executive Vice President and Head of Foundry Design Platform Development at Samsung Electronics, said: “Over the past few years, we have been collaborating closely with Keysight EDA to improve the efficiency and accuracy of our RF modeling flow. By adopting the Model Generator in our workflow, our efficiency has improved by at least 30 percent. The Model Generator’s ability to handle complex netlists and the variety of measured data, including S-parameters and low and high-frequency noise, is critical to us. The flexibility and powerful performance of this tool helps improve the accuracy of models. We can customize the parameters thanks to Python and adapt the Model Generator to our needs.”
Niels Faché, Vice President and General Manager, Keysight EDA, said: “The modeling of today’s RF FinFET and tomorrow’s innovative devices is hugely complex and time-consuming. Engineers must extract hundreds of parameters to accurately model the RF behavior of devices for different sizes and temperatures. The Model Generator removes critical barriers in the workflow and allows Samsung engineers to focus more on the modeling and less on the programming. We are pleased that this new solution helps Samsung better manage their modeling workflow, shorten process design kits development cycle, and accelerate product time to market.”
Resources
- IC-CAP 2023 Model Generator
- PathWave Device Modeling
- PathWave Model Builder
- PathWave Model QA
- E4727B Advanced Low-Frequency Noise Analyzer
- PathWave WaferPro
To learn more, visit Keysight’s booth at the Samsung SAFE™ Forum on June 28, 2023 in
About Keysight Technologies
At Keysight (NYSE: KEYS), we inspire and empower innovators to bring world-changing technologies to life. As an S&P 500 company, we’re delivering market-leading design, emulation, and test solutions to help engineers develop and deploy faster, with less risk, throughout the entire product lifecycle. We’re a global innovation partner enabling customers in communications, industrial automation, aerospace and defense, automotive, semiconductor, and general electronics markets to accelerate innovation to connect and secure the world. Learn more at Keysight Newsroom and www.keysight.com.
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Geri Lynne LaCombe
+1 303 662 4748
geri_lacombe@keysight.com
Fusako Dohi
+81 42 660-2162
fusako_dohi@keysight.com
Source: Keysight Technologies, Inc.
