AutoChip leverages LLMs in an interactive setting to create Verilog modules from design prompts and debugging messages. This study examines the conversion of design concepts into functionally correct HDL code without manual coding.

• Demonstrates the use of LLMs for automated HDL generation.
• Introduces an interactive learning framework named AutoChip.
• Analyzes problem sets from HDLBits to validate the approach.
• Finds that incorporating compiler context increases accuracy by 24.20%.
• Releases evaluation scripts and datasets as open-source contributions.

With the potential to expedite the hardware design process while reducing human error, AutoChip highlights the expanding applications of LLMs beyond traditional software engineering tasks. This initiative could lead to groundbreaking developments in the field of hardware engineering. Read more.