Yang, K. orcid.org/0000-0002-2844-3810, Liu, H., Zhao, Y. et al. (1 more author) (2023) A new design approach of hardware implementation through natural language entry. IET Collaborative Intelligent Manufacturing, 5 (4). e12087. ISSN 2516-8398
Abstract
OpenAI's ChatGPT (GPT-4) ushers in a superior mode of computer interaction through natural language dialogues. Notably, it generates not only engaging dialogues but also codes aligned to queries and requirements. The potential of ChatGPT in hardware implementation via natural language is implemented and a strategy for “asking the right questions” is outlined. The versatility of ChatGPT is demonstrated through three mainstream hardware designs – systolic array, ResNet and MobileNet accelerators – comparing these with hand-coded designs. The evaluation metrics include design quality, design efforts, and limitations of code generated by ChatGPT/GPT-4/Cursor against prevalent High-Level Synthesis or hand-coded HDL designs. Consequently, a novel design workflow is proposed and the constraints of using GPT, particularly in AI accelerators, are highlighted.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2023 The Authors. IET Collaborative Intelligent Manufacturing published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. https://creativecommons.org/licenses/by/4.0/ |
Keywords: | computer integrated manufacturing; human computer interaction; human-robot interaction; intelligent manufacturing systems |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Electronic and Electrical Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 13 Nov 2023 16:07 |
Last Modified: | 13 Nov 2023 16:07 |
Status: | Published |
Publisher: | Institution of Engineering and Technology (IET) |
Refereed: | Yes |
Identification Number: | 10.1049/cim2.12087 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:205231 |