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Cloud TPU VMs are generally available

cloud.google.com

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Re: Cloud TPU VMs are generally available

#32
post #31

Do these TPU VMs have preemptible/spot pricing? I'm just a hobbyist, but it always seemed annoying before that one would have to orchestrate VMs to spin up/down alongside spot instances of TPUs manually.

Yes, there are a couple of ways to use Cloud TPUs at lower priority and lower cost. If you are a hobbyist, I highly recommend trying out Cloud TPUs for free via the TPU Research Cloud: https://sites.research.google/trc/

If you are flexible, you (or your scripts) can access a lot of compute power at odd hours!

Re: Cloud TPU VMs are generally available

#34
post #5

Earlier quoted context omitted.

Thanks for the very kind feedback! We've wanted to provide TPU VMs since the beginning of the Cloud TPU program, and I'm delighted that you're enjoying them. Many people across Google contributed to this launch. We're definitely working on GKE integration, and we intend to provide more support for orchestration over time since individual Cloud TPU workloads are getting bigger and bigger. We'd love to hear any more de…

Curious what is the difficulty with GKE integration? From afar, it seems like the flavor of VM shouldn’t impact ability to run K8s.

The GKE team probably has other priorities.

Re: Cloud TPU VMs are generally available

#38
post #17

For those like me who had no idea what this means: > Tensor Processing Units (TPUs) are Google's custom-developed application-specific integrated circuits (ASICs) used to accelerate machine learning workloads.

Is this[1] the best resource for understanding TPU (or TPU-like) architectures in general?

I would love to see a TPU implementation in the style of the Nand2Tetris[2] CPU, reduced to its bare essentials for learning purposes.

Are systolic array processors the best place to start for this kind of info? Thanks in advance if anyone answers. :)

[1]: https://drive.google.com/file/d/0Bx4hafXDDq2EMzRNcy1vSUxtcEk...

[2]: https://www.nand2tetris.org/course

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