Tips N Tricks #6: How to train multiple deep neural networks on TPUs simultaneously | Summary and Q&A

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April 17, 2020
by
Abhishek Thakur
YouTube video player
Tips N Tricks #6: How to train multiple deep neural networks on TPUs simultaneously

TL;DR

Learn how to train eight different models simultaneously on Google Cloud GPUs for faster training compared to home GPUs.

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Key Insights

  • 💨 Google Cloud GPUs offer faster training times compared to regular home GPUs.
  • 👻 A new live show series on YouTube allows guests to present their machine learning or AI projects.
  • 🚄 Training multiple models simultaneously on Google Cloud GPUs can significantly speed up the training process.
  • 😒 Modifying code to use XLA and specifying the device index are necessary for training on Google Cloud GPUs.
  • ☠️ The recommended batch size and learning rate may need adjustment when training on multiple GPU cores.
  • 😒 Torch XLA, although experimental, has strong developer support and is relatively easy to use.
  • 👤 The video emphasizes the importance of user feedback and suggestions for improvement.

Transcript

okay so hello everyone and welcome to my tips and tricks video and in this video I'm going to show you something really cool that I recently came across maybe uh it's known to a lot of people but to me it was entirely new and I think it's it's a pretty cool thing that you can try so what I'm going to talk about today is how to train eight different... Read More

Questions & Answers

Q: What is the advantage of using Google Cloud GPUs for training machine learning models?

Google Cloud GPUs are faster than regular home GPUs, providing quicker training times and improved performance.

Q: How can I participate in the live show series mentioned in the video?

To be a guest on the live show, fill out the form provided in the video's description box and share your non-commercial projects or startup company related to machine learning or AI.

Q: Is it necessary to modify existing GPU training code to train on Google Cloud GPUs?

Yes, slight modifications to the code are needed, such as changing the device to XLA and specifying the device index for each core used.

Q: Can I train multiple models simultaneously on Google Cloud GPUs?

Yes, you can train multiple models on different cores of Google Cloud GPUs simultaneously, improving training speed.

Summary & Key Takeaways

  • Google Cloud GPUs are faster than regular home GPUs, making them popular for training machine learning models.

  • The video introduces a new live show series on YouTube where guests present their machine learning or AI projects.

  • The video demonstrates how to train multiple models on Google Cloud GPUs simultaneously, improving training speed.

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