Computer Science > Artificial Intelligence
arXiv:2207.12229 (cs)
[Submitted on 22 Jun 2022]
Title:Towards Systems Education for Artificial Intelligence: A Course Practice in Intelligent Computing Architectures
View a PDF of the paper titled Towards Systems Education for Artificial Intelligence: A Course Practice in Intelligent Computing Architectures, by Jianlei Yang and 2 other authors
View PDFAbstract:With the rapid development of artificial intelligence (AI) community, education in AI is receiving more and more attentions. There have been many AI related courses in the respects of algorithms and applications, while not many courses in system level are seriously taken into considerations. In order to bridge the gap between AI and computing systems, we are trying to explore how to conduct AI education from the perspective of computing systems. In this paper, a course practice in intelligent computing architectures are provided to demonstrate the system education in AI era. The motivation for this course practice is first introduced as well as the learning orientations. The main goal of this course aims to teach students for designing AI accelerators on FPGA platforms. The elaborated course contents include lecture notes and related technical materials. Especially several practical labs and projects are detailed illustrated. Finally, some teaching experiences and effects are discussed as well as some potential improvements in the future.
| Comments: | This paper is published on ACM GLSVLSI 2020 |
| Subjects: | Artificial Intelligence (cs.AI); Hardware Architecture (cs.AR); Computers and Society (cs.CY) |
| Cite as: | arXiv:2207.12229 [cs.AI] |
| (orarXiv:2207.12229v1 [cs.AI] for this version) | |
| https://doi.org/10.48550/arXiv.2207.12229 arXiv-issued DOI via DataCite |
Full-text links:
Access Paper:
- View PDF
- TeX Source
- Other Formats
View a PDF of the paper titled Towards Systems Education for Artificial Intelligence: A Course Practice in Intelligent Computing Architectures, by Jianlei Yang and 2 other authors
References & Citations
Bookmark
Bibliographic and Citation Tools
Bibliographic Explorer(What is the Explorer?)
Connected Papers(What is Connected Papers?)
Litmaps(What is Litmaps?)
scite Smart Citations(What are Smart Citations?)
Code, Data and Media Associated with this Article
alphaXiv(What is alphaXiv?)
CatalyzeX Code Finder for Papers(What is CatalyzeX?)
DagsHub(What is DagsHub?)
Gotit.pub(What is GotitPub?)
Hugging Face(What is Huggingface?)
Papers with Code(What is Papers with Code?)
ScienceCast(What is ScienceCast?)
Demos
Recommenders and Search Tools
Influence Flower(What are Influence Flowers?)
CORE Recommender(What is CORE?)
arXivLabs: experimental projects with community collaborators
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.
Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.
Have an idea for a project that will add value for arXiv's community?Learn more about arXivLabs.