Presentation
Accelerating Bandgap Reference High-Sigma Verification with Additive AI Technology
DescriptionThis case study presents a detailed methodology for the verification of a bandgap reference circuit in an advanced FinFET process. The verification process leverages Additive AI technology to address the complexities inherent in analog circuits, particularly those involving a large number of elements. The verification analysis was conducted at a high-sigma target, and the circuit encompassed 17,000 devices. The application of this AI technology significantly reduced the simulation count by 40.4 times and the wall clock time by 19.4 times, converting a typical 6-hour verification job into an 18-minute task with the same accuracy. This AI-powered approach operates seamlessly, requiring no additional designer effort, and ensures accuracy by self-verifying and running full jobs when necessary. It is particularly effective for incremental and iterative workflows, such as PVT changes, sizing and layout revisions, toolchain updates, and PDK updates. Our analysis included several VDD changes, ranging from nominal to extreme variations, with a target sigma of 5 sigma. The results demonstrate the efficacy of the technology in significantly reducing verification time and effort, enabling multiple iterations per day, and ensuring robust verification of complex analog circuits in advanced technology nodes.
Event Type
Engineering Presentation
TimeMonday, June 2311:00am - 11:15am PDT
Location2010, Level 2
AI
IP