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About this paper
Manar Abdelatty, Jacob Rosenstein, Sherief Reda
An LLM-powered multi-agent framework enables hardware engineers to explore complex designs and Process Design Kits (PDKs) using natural language queries, achieving 97.39% execution accuracy. This system facilitates data retrieval 5.63 times faster and reduces human errors by 5.25 times over manual approaches, while outperforming generic LLM workflows by 29.78% in accuracy.
Key insights
- Specialized multi-agent LLM architectures, designed with domain-specific knowledge, are more effective than generic LLM workflows for complex, structured, and heterogeneous hardware design data.
- Representing PDKs in relational databases and hardware designs in graph databases, combined with a multi-agent system, enables accurate cross-database reasoning.
- The Dispatcher agent plays a critical role in managing structured redundancy within hardware data, ensuring queries are routed efficiently and enabling dynamic loading of relevant data for scalability.
Summary by alphaXiv.
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