AaLLM: An End-to-End Analog Circuit Design Framework from Topology Generation to Sizing Using Large Language Models
Analog circuit design is a time-consuming, iterative process in a nonlinear and high-dimensional design space that relies heavily on expert intuition. Among recent developments, LLMs have introduced a promising approach by bringing natural language reasoning to circuit design tasks. The majority of conventional LLM-based approaches provide fragmented solutions that focus either only on sizing or topology generation. These methods require adding specific technical knowledge manually, which is inefficient and prone to hallucinations during circuit sizing. Moreover, the inherent trade-off in meet
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- FuzzyOverlapping authors or contributors · 62%ollama/ollama →
“Shared author/contributor keys: hart”
- LinkedLinked via arxiv author · 85%Mohammed Ayman Habib →
“AaLLM: An End-to-End Analog Circuit Design Framework from Topology Generation to Sizing Using Large Language Models”
- LinkedLinked via arxiv author · 85%Rylan Hart →
“AaLLM: An End-to-End Analog Circuit Design Framework from Topology Generation to Sizing Using Large Language Models”
- LinkedLinked via arxiv author · 85%Morteza Fayazi →
“AaLLM: An End-to-End Analog Circuit Design Framework from Topology Generation to Sizing Using Large Language Models”