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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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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