Long Context RTL Optimization
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LongRTL: Graph-Similarity-Guided LLM-driven Long Context RTL Optimization
Announce Type: new Abstract: Large Language Models (LLMs) show great promise in RTL code generation and optimization. However, real-world RTL designs are typically long, entangled, and poorly modularized, posing a major challenge due to context-length limitations and lack of structure. To overcome these obstacles, we propose a scalable LLM-based RTL optimization framework guided by graph similarity.