editor's blog
Subscribe Now

Faster Extraction from Cadence

Cadence recently announced new extraction tools, claiming both greater speed (5x) and best-in-class accuracy for full-chip extraction. And what is it that lets them speed up without sacrificing results?

The answer is the same thing that has benefited so many EDA tools over the last few years: parallelism. Both within a box (multi-threading) and using multiple boxes (distributed computing). The tools can scale up to hundreds of CPUs, although they’re remaining mum on the details of how they did this…

They have two new tools:  a new random-walk field solver (Quantus FS) and the full-chip extraction tool (Quantus QRC). They say that the field solver is actually running around 20 times faster than their old one.

The field solver is much more detailed and accurate than the full-chip extraction tool. It’s intended for small circuits and high precision; its results are abstracted for use on a larger scale by the full-chip tool. That said, they claim good correlation between QRC and FS, so not much is lost in the abstraction.

They’ve also simplified the FinFET model, cutting the size of the circuit in half and increasing analysis speed by 2.5x.

While QRC is intended for the entire chip, it can also be used incrementally – in which case it can be three times again as fast. Both the Encounter digital implementation tool and their Tempus timing analysis tool can take advantage of this incremental capability to do real-time extraction as the tools make decisions. It’s also integrated into the Virtuoso analog/custom tool.

As to accuracy, they say they meet all of TSMC’s golden FinFET data, that they achieve consistent results with single- and multi-corner analysis, and that they’ve been certified by TSMC for the 16-nm node.

Their fundamental capabilities are summarized in the following figure, although this coverage is consistent with the prior tools.

QRC_functions_500.png

Image courtesy Cadence

You can read more in their announcement.

Leave a Reply

featured blogs
Feb 22, 2024
The new Cadence training website is online! This newly redesigned website provides an overview of our well-respected training methods and courses, plus offerings that might be new to you. Modern design and top-of-the-page navigation make it easy to find just what you need'”q...
Feb 15, 2024
This artist can paint not just with both hands, but also with both feet, and all at the same time!...

featured video

Tackling Challenges in 3DHI Microelectronics for Aerospace, Government, and Defense

Sponsored by Synopsys

Aerospace, Government, and Defense industry experts discuss the complexities of 3DHI for technological, manufacturing, & economic intricacies, as well as security, reliability, and safety challenges & solutions. Explore DARPA’s NGMM plan for the 3DHI R&D ecosystem.

Learn more about Synopsys Aerospace and Government Solutions

featured paper

Reduce 3D IC design complexity with early package assembly verification

Sponsored by Siemens Digital Industries Software

Uncover the unique challenges, along with the latest Calibre verification solutions, for 3D IC design in this new technical paper. As 2.5D and 3D ICs redefine the possibilities of semiconductor design, discover how Siemens is leading the way in verifying complex multi-dimensional systems, while shifting verification left to do so earlier in the design process.

Click here to read more

featured chalk talk

IoT Data Analysis at the Edge
No longer is machine learning a niche application for electronic engineering. Machine learning is leading a transformative revolution in a variety of electronic designs but implementing machine learning can be a tricky task to complete. In this episode of Chalk Talk, Amelia Dalton and Louis Gobin from STMicroelectronics investigate how STMicroelectronics is helping embedded developers design edge AI solutions. They take a closer look at the benefits of STMicroelectronics NanoEdge-AI® Studio and  STM32Cube.AI and how you can take advantage of them in your next design. 
Jun 28, 2023
28,507 views