18674

Deep Learning by Doing: The NVIDIA Deep Learning Institute and University Ambassador Program

Xi Chen, Gregory S. Gutmann, Joe Bungo
University of Kentucky, Lexington, Kentucky
arXiv:1812.08671 [cs.CY], 20 Dec 2018

@article{chen2018deep,

   title={Deep Learning by Doing: The NVIDIA Deep Learning Institute and University Ambassador Program},

   author={Chen, Xi and Gutmann, Gregory S. and Bungo, Joe},

   year={2018},

   month={dec},

   archivePrefix={"arXiv"},

   primaryClass={cs.CY}

}

Download Download (PDF)   View View   Source Source   

1914

views

Over the past two decades, High-Performance Computing (HPC) communities have developed many models for delivering education aiming to help students understand and harness the power of parallel and distributed computing. Most of these courses either lack a hands-on component or heavily focus on theoretical characterization behind complex algorithms. To bridge the gap between application and scientific theory, NVIDIA Deep Learning Institute (DLI) has designed an on-line education and training platform that helps students, developers, and engineers solve real-world problems in a wide range of domains using deep learning and accelerated computing. DLI’s accelerated computing course content starts with the fundamentals of accelerating applications with CUDA and OpenACC in addition to other courses in training and deploying neural networks for deep learning. Advanced and domain-specific courses in deep learning are also available. The online platform enables students to use the latest AI frameworks, SDKs, and GPU-accelerated technologies on fully-configured GPU servers in the cloud so the focus is more on learning and less on environment setup. Students are offered project-based assessment and certification at the end of some courses. To support academics and university researchers teaching accelerated computing and deep learning, the DLI University Ambassador Program enables educators to teach free DLI courses to university students, faculty, and researchers.
No votes yet.
Please wait...

* * *

* * *

HGPU group © 2010-2024 hgpu.org

All rights belong to the respective authors

Contact us: