POET: Power-Oriented Evolutionary Tuning for LLM-Based RTL PPA Optimization
#POET #RTL optimization #PPA #evolutionary tuning #LLM #power efficiency #hardware design
📌 Key Takeaways
- POET introduces a power-focused evolutionary tuning method for optimizing RTL designs using LLMs.
- The approach targets Power, Performance, and Area (PPA) optimization in hardware design.
- It leverages evolutionary algorithms to enhance LLM-based RTL generation for improved efficiency.
- The method aims to reduce power consumption while maintaining performance and area constraints.
📖 Full Retelling
arXiv:2603.19333v1 Announce Type: cross
Abstract: Applying large language models (LLMs) to RTL code optimization for improved power, performance, and area (PPA) faces two key challenges: ensuring functional correctness of optimized designs despite LLM hallucination, and systematically prioritizing power reduction within the multi-objective PPA trade-off space. We propose POET (Power-Oriented Evolutionary Tuning), a framework that addresses both challenges. For functional correctness, POET intro
🏷️ Themes
Hardware Optimization, AI in Design
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Original Source
arXiv:2603.19333v1 Announce Type: cross
Abstract: Applying large language models (LLMs) to RTL code optimization for improved power, performance, and area (PPA) faces two key challenges: ensuring functional correctness of optimized designs despite LLM hallucination, and systematically prioritizing power reduction within the multi-objective PPA trade-off space. We propose POET (Power-Oriented Evolutionary Tuning), a framework that addresses both challenges. For functional correctness, POET intro
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