Cadence Design Tool Implements ML for More Effective Digital IC Design

By Rich Nass

Contributing Editor

Embedded Computing Design

August 02, 2021

Blog

Cadence Design Tool Implements ML for More Effective Digital IC Design

When I first heard about this, it sounded like a little smoke and mirrors, to be able to work the latest buzzwords into the product’s announcement. But a deeper dive reveals that ML implementation is really taking place here.

According to the company, combining Cerebrus and Cadence’s RTL-to-signoff flow offers the ability to improve engineering productivity by up to 10X versus a manual approach while also realizing up to a 20% better power, performance and area (PPA).

The list of benefits offered by Cerebrus includes:

  • reinforcement ML, which quickly finds flow solutions humans might not naturally try or explore
  • ML model reuse, which permits design learnings be automatically applied to future designs
  • improved productivity by allowing the engineer to optimize the complete RTL-to-GDS flow automatically for many blocks concurrently
  • massively distributed computing, which provides scalable on-premise or cloud-based designs, resulting in faster flow optimization

Cerebrus fits in well with the broader Cadence digital full flow, working seamlessly with the synthesis, timing, power, and verification tools for a complete design flow.

For more information, visit:www.cadence.com

Rich Nass is a regular contributor to Embedded Computing Design. He has appeared on more than 500 episodes of the popular Embedded Executive podcast series, and is a regular contributor to the Embedded Insiders podcast.

Rich has been in the engineering OEM industry for more than 35 years, and is a recognized expert in the areas of embedded computing, Edge AI, industrial computing, the IoT, and cyber-resiliency and safety and security issues. He writes and speaks regularly on these topics and more.

Rich is currently the Liaison to Industry for the Embedded World North America Exhibition and Conference, and has held similar positions with the global Embedded World Conference and Exhibition.

Previously, Rich was the Brand Director for UBM’s award-winning Design News property. Prior to that, he led the content team for UBM Canon’s Medical Devices Group, as well all custom properties and events.  In prior stints, he led the Content Team at EE Times, handling the Embedded and Custom groups and the TechOnline DesignLine network of design engineering web sites.

Nass holds a BSEE degree from the New Jersey Institute of Technology.

Podcast/Interview Coverage

Sonatus The Garage Podcast

onalytica Interview

Dev Talk with Rich and Vin

Embedded Executive Podcast

Semiconscious Webcast

IEEE Awards Frede Blaabjerg Talks EVS

Atmosic: Embedded Executive: Energy Harvesting Podcast

 

Article Coverage

Embedded AI Isn’t Enterprise AI, and That’s a Good Thing

Tear Down: Google Pixel Watch 4

Protect Your Home from Thieves and Floods

Advantech Teams With AMD To Maximize Performance at the Edge

Tear Down: Noise Luna Ring

 

View additional information

Muck Rack

More from Rich