Cloud native EDA tools & pre-optimized hardware platforms
Synopsys VSO.ai? (Verification Space Optimization) delivers the industry¡¯s first AI-driven verification solution to help verification teams achieve coverage closure faster and with higher quality. The system works autonomously to reach coverage targets as quickly and as cheaply as possible with the highest quality of results. Machine learning technologies are used 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.
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Automated discovery of elusive gaps in test coverage
Exploring infinite design states with no manual intervention or analysis
Allowing engineers to focus on fixing bugs, not finding them
Synopsys VSO.ai easily integrates into existing VCS(R)-regression environments without any code changes in the design or testbench. It supports functional coverage metrics (covergroups and assertion coverage) and code coverage metrics (line, toggle, and FSM coverage). It automatically identifies and orchestrates tests to minimize a user-selected objective function such as regression CPU time, number of test runs, simulation cycles, or cycles-per-second.
Synopsys VSO.ai operates within the simulator to expertly target and improve coverage at the constraint solver, test, and test-option levels. Get ready to experience unparalleled precision and efficiency like never before!
Synopsys VSO.ai analyzes the coverage results and performs root cause analysis (RCA) to determine why specific coverage bins are not being bit.?
Using AI-driven verification with Synopsys VCS, part of Synopsys.ai, we¡¯ve achieved up to 10x improvement in reducing functional coverage holes and up to 30% increase in IP verification productivity demonstrating the ability of AI to help us address the challenges of our increasingly complex designs."
Takahiro Ikenobe
|IP Development Director, Renesas