LLM evaluation for RTL generation identifies three performance tiers with frontier models reaching high synthesis quality and reveals systematic failure differences between proprietary and open models.
In: Proceed- ings of the 43rd IEEE/ACM International Conference on Computer- Aided Design
2 Pith papers cite this work. Polarity classification is still indexing.
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AutoPPA learns generalizable PPA optimization rules automatically via contrastive abstraction from diverse code pairs and applies them through adaptive search, outperforming manual methods and prior tools SymRTLO and RTLRewriter.
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Synthesis-in-the-Loop Evaluation of LLMs for RTL Generation: Quality, Reliability, and Failure Modes
LLM evaluation for RTL generation identifies three performance tiers with frontier models reaching high synthesis quality and reveals systematic failure differences between proprietary and open models.
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AutoPPA: Automated Circuit PPA Optimization via Contrastive Code-based Rule Library Learning
AutoPPA learns generalizable PPA optimization rules automatically via contrastive abstraction from diverse code pairs and applies them through adaptive search, outperforming manual methods and prior tools SymRTLO and RTLRewriter.