SPICEPilot: Navigating SPICE Code Generation and Simulation with AI Guidance

Document Type

Conference Proceeding

Publication Date

1-1-2024

Abstract

Large Language Models (LLMs) have shown great potential in automating code generation; however, their ability to generate accurate circuit-level SPICE code remains limited due to a lack of hardware-specific knowledge. In this paper, we analyze and identify the typical limitations of existing LLMs in SPICE code generation. To address these limitations, we present SPICEPilot—a novel Python-based dataset generated using PySpice, along with its accompanying framework. This marks a significant step forward in automating SPICE code generation across various circuit configurations. Our framework automates the creation of SPICE simulation scripts, introduces standardized benchmarking metrics to evaluate LLM’s ability for circuit generation, and outlines a roadmap for integrating LLMs into the hardware design process. SPICEPilot is open-sourced under the permissive MIT license at https://github.com/ACADLab/SPICEPilot.git.

Identifier

105002709169 (Scopus)

ISBN

[9798331541279]

Publication Title

2024 IEEE International Conference on Rebooting Computing, ICRC 2024

External Full Text Location

https://doi.org/10.1109/ICRC64395.2024.10937006

Grant

2216772

Fund Ref

Semiconductor Research Corporation

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