{"id":2098,"date":"2020-12-09T12:18:47","date_gmt":"2020-12-09T17:18:47","guid":{"rendered":"https:\/\/blogs.sw.siemens.com\/calibre\/?p=2098"},"modified":"2026-03-26T16:20:26","modified_gmt":"2026-03-26T20:20:26","slug":"globalfoundries-and-mentor-launch-a-new-innovative-drc-hotspot-solution-using-machine-learning-in-calibre","status":"publish","type":"post","link":"https:\/\/blogs.sw.siemens.com\/calibre\/2020\/12\/09\/globalfoundries-and-mentor-launch-a-new-innovative-drc-hotspot-solution-using-machine-learning-in-calibre\/","title":{"rendered":"GLOBALFOUNDRIES and Mentor Launch a New Innovative DRC+ Hotspot Solution using Machine Learning in Calibre"},"content":{"rendered":"\n

By Shelly Stalnaker – Mentor, A Siemens Business<\/p>\n\n\n\n

I recently had the chance to attend an on-demand webinar introducing the new GLOBALFOUNDRIES DRC+ hotspot solution that incorporates machine learning in the Calibre toolsuite. Presented by Sriram Madhavan (GLOBALFOUNDRIES) and Michael White (Mentor, a Siemens Business), the webinar walks through the new DRC+ DFM solution, and explains how the addition of machine learning expands and improves both the capabilities and results.<\/p>\n\n\n\n

I remember when DRC+ was first introduced by GLOBALFOUNDRIES and made its way into the public eye about ten years ago. Pretty innovative stuff, using pattern matching to identify and modify potential yield-limiting geometries in an otherwise DRC-clean layout. Of course, there\u2019s a whole host of technology and process that goes on behind the scenes to identify, classify, and prioritize these hotspots, and turn them into \u201cyield detractor patterns\u201d that can be recognized in any design.<\/p>\n\n\n\n

Enter machine learning. As it turns out, using machine learning for pattern definition provides expanded depth and breadth to the whole DRC+ solution. Not only can machine learning more easily capture critical patterns (especially for complex failure modes), but it is also more effective at identifying previously unrecognized hotspot patterns, with fewer false errors, than the traditional methods. Here\u2019s a sneak peek at the evolution:<\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

Even better, the integration of machine learning into DRC+ is seamless. At least within the Calibre toolsuite. The new ML checks are integrated within the same pattern matching DRC+ deck customers have been familiar with and using for years. This makes access and use to GLOBALFOUNDRES customers easy and uniform. Providing a consistent interface across design tools gives design teams the same look and feel, regardless of their implementation environments.<\/p>\n\n\n\n

This collaborative effort between GLOBALFOUNDRIES and Mentor provides joint customers with a more effective design and development experience, and ultimately, a better product and a faster time to market.<\/p>\n\n\n\n

Want to get all the details? The webinar is available here<\/a>, and it\u2019s only about 12 minutes long. A good coffee break view, and well worth your time!<\/p>\n","protected":false},"excerpt":{"rendered":"

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