Large language models (LLMs) have made headlines for synthesizing correct-sounding responses to a variety of prompts, including code generation. In this paper, we present the prompts used to guide ChatGPT4 to produce a synthesizable and functional verilog description for the entirety of a programmable Spiking Neuron Array ASIC. This design flow showcases the current state of using ChatGPT4 for natural language driven hardware design. The AI-generated design was verified in simulation using handcrafted testbenches and has been submitted for fabrication in Skywater 130nm through Tiny Tapeout 5 using an open-source EDA flow.
@article{arxiv.2402.10920,
title = {Designing Silicon Brains using LLM: Leveraging ChatGPT for Automated Description of a Spiking Neuron Array},
author = {Michael Tomlinson and Joe Li and Andreas Andreou},
journal= {arXiv preprint arXiv:2402.10920},
year = {2024}
}