Shorten Your CDC Debug Cycle by 10X with ML-based RCA
April 5 @ 1:00 am - 11:00 am PDT
Over the last few decades System on Chip (SoC) design size has dramatically increased, and more complexity has been introduced to deliver the desired functionality. Growing design sizes lead to the introduction of several asynchronous clocks which can result in the reporting of millions of clock domain crossings (CDC) at the IP/SoC level. This leads to significantly long CDC debug cycles. The manual approach to analyze and debug CDCs is time consuming and error prone. Synopsys machine learning (ML) based Root Cause Analysis (RCA) addresses these problems seamlessly.
This Synopsys webinar will cover how you can achieve 10X faster debug using Synopsys VC SpyGlass RTL signoff platform machine-learning technology.
Listed below is the industry leader scheduled to speak.
Navneet Kumar Chaurasia
Applications Engineer, Staff
Navneet has 10+ year of experience in CDC. He currently works with customers across the globe, helping them with CDC signoff at the IP, Subsystem and SoC level. He studied M Tech in VLSI design at the Centre for Development of Advanced Computing.