Designing Silicon Brains using LLM: Leveraging ChatGPT for Automated Description of a Spiking Neuron Array
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Abstract (arXiv)
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.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 5 of its 11 references that are in the map. First posted on arXiv 25 Jan 2024.
Builds on
5 of 11 references.
References · 5
- 2023GPT-4 Technical Reportcited by 18,132
- 2023Chip-Chat: Challenges and Opportunities in Conversational Hardware Designcited by 136
- 2023ChipGPT: How far are we from natural language hardware designcited by 101
- 2023Is ChatGPT the Ultimate Programming Assistant -- How far is it?cited by 72
- 2023ChatGPT for Programming Numerical Methodscited by 26
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Citing papers per year: 2024: 1.
1 paper.