From Concept to Practice: an Automated LLM-aided UVM Machine for RTL Verification
arXiv cs.AI / 4/7/2026
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Key Points
- The paper argues that RTL verification is a major IC development bottleneck, with verification often consuming around 70% of total effort, largely due to the cost of building UVM testbenches and generating adequate stimuli.
- It introduces UVM^2, an automated UVM verification framework that uses LLMs to generate UVM testbenches and then iteratively improves them using coverage feedback.
- The framework is evaluated on a new benchmark suite of RTL designs up to 1.6K lines of code to test both scalability and verification quality.
- Reported results indicate UVM^2 can significantly reduce testbench setup time compared with experienced engineers while achieving strong average code coverage (87.44%) and function coverage (89.58%).
- The authors claim improvements over state-of-the-art approaches of roughly 20.96% (code coverage) and 23.51% (function coverage), suggesting LLM-guided coverage-driven iteration can materially boost verification effectiveness.
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