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70% of engineering time is spent verifying a design but it is largely a manual effort. As the industry faces ongoing engineering shortages companies are forced to make their engineering teams 10 times more productive at finding and isolating bugs per day. Increasing design complexities are also driving up the compute resources needed to verify todays designs.

To address these resource challenges, teams need to shift from an entirely manual verification process to utilizing autonomous verification - where human interaction is reduced, enabling the ability to achieve coverage closure faster. The goal is that once a coverage target is set, the system works autonomously to reach the target as quickly and cheaply as possible with the highest quality of results.

This ²ÝÁñÉçÇø webinar will introduce and explore the ²ÝÁñÉçÇø VSO.ai? solution, Verification Space Optimization, using machine learning technologies to identify and eliminate redundancies in regressions, automate coverage root cause analysis, and infer coverage from RTL and stimulus to identify coverage gaps and provide coverage guidance.