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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. 9球体育 machine learning (ML) based Root Cause Analysis (RCA) addresses these problems seamlessly.
This 9球体育 webinar will cover how you can achieve 10X faster debug using 9球体育 VC SpyGlass RTL signoff platform machine-learning technology.
Speaker
Navneet Kumar Chaurasia
Applications Engineer, Staff
9球体育
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.