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NVIDIA Workshop: Fundamentals of Deep Learning for Multi-GPUs

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Sprecher: Dr Georgios Varisteas, University of Luxembourg
Veranstaltung: Montag, den 03. Februar 2020 09:00 - 18:00
Ort: Room E004
JFK Building
29 Avenue J.F. Kennedy
L-1855 Kirchberg

The computational requirements of deep neural networks used to enable AI applications like self-driving cars are enormous. A single training cycle can take weeks on a single GPU, or even years for the larger datasets like those used in self-driving car research. Using multiple GPUs for deep learning can significantly shorten the time required to train lots of data, making solving complex problems with deep learning feasible.

This course will teach you how to use multiple GPUs to training neural networks. You'll learn:

  • Approaches to multi-GPU training
  • Algorithmic and engineering challenges to large-scale training
  • Key techniques used to overcome the challenges mentioned above
  • Upon completion, you'll be able to effectively parallelize training of deep neural networks using TensorFlow.

This workshop is hands-on with multiple Python coding exercises, thus beginner's level Python experience will be beneficial. Upon successful completion of the assessment, participants will receive an NVIDIA DLI certificate to recognize their subject matter competency and support professional career growth.

This course is the premier course on deep learning deployment offered by the NVIDIA Deep Learning Institute. You can find more detailed information here.