POET: Power-Oriented Evolutionary Tuning for LLM-Based RTL PPA Optimization

1. 1Identify the key challenges in applying LLMs to RTL code optimization, including functional correctness and power reduction
2. 2Develop a framework that addresses these challenges, such as POET
3. 3Implement evolutionary tuning to systematically prioritize power reduction within the multi-objective PPA trade-off space
4. 4Evaluate the effectiveness of the framework in optimizing PPA and ensuring functional correctness

This research benefits AI engineers and ML researchers working on large language models and hardware optimization, as it provides a novel approach to addressing challenges in functional correctness and power reduction

💡 POET addresses the challenges of functional correctness and power reduction in LLM-based RTL code optimization

🤖 POET: A novel framework for power-oriented evolutionary tuning of LLM-based RTL PPA optimization