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OpenROAD-Assistant: An Open-Source Large Language Model for Physical Design Tasks

appsOther research productkeyboard_double_arrow_right Model 01 Jan 2024Publisher:Zenodo

Authors: Sharma, Utsav; Wu, Bing-Yue; Kankipati, Sai Rahul Dhanvi; Chhabria, Vidya; Rovinski, Austin;

doi: 10.5281/zenodo.13013370 , 10.5281/zenodo.13265165 , 10.5281/zenodo.13013369 , 10.5281/zenodo.13293473 , 10.5281/zenodo.13119166

OpenROAD-Assistant: An Open-Source Large Language Model for Physical Design Tasks

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Abstract

This paper presents OpenROAD-Assistant, an open-source chatbot designed for OpenROAD, leveraging only public data to respond to queries in prose or Python script using the OpenROAD APIs. OpenROAD-Assistant uses the foundational Llama3-8B model, enhanced with retrieval-aware fine-tuning (RAFT) for physical design-specific applications. OpenROAD-Assistant, its RAG database, and all related scripts are available on Zinodo and GitHub. It includes the prompt-script and question-answer adaptors and the associated codes to train the models and perform inference. The minimal hardware requirements are 2 CPU cores, 32GB of RAM, and 4 NVIDIA RTX A5500 GPUs for the Script Adaptor or 1 NVIDIA V100 GPU for the QA Adaptor. The software requirements are Python version >= 3.8 but <3.11.

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