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Cloud TPUs in Beta

cloudplatform.googleblog.com

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Re: Cloud TPUs in Beta

#31

Post by brd »

tejasmanohar wrote: post #9

This is exciting. There are lots of specific reasons to choose Google Cloud over AWS (and vice versa), but proprietary hardware is surely an advantage that is going to be hard to replicate / compete with. If TPUs hold up to the hype, GCloud may become the de facto for ML/AI startups.

Having had the chance to attend a fireside chat with leadership from Google and SAP, I get the sense that the hype is likely to hold up. There are a lot of big bets happening in the Enterprise space around this notion of efficient, easy to implement ML.

Re: Cloud TPUs in Beta

#33

Post by kyrra »

gcp wrote: post #30

Interestingly, GCP now appears to be available to individuals in Europe. It wasn't like that before, no idea when that policy got changed. Before, GCP wasn't even a consideration compared to AWS (which always handled that).

More details: https://cloud.google.com/billing/docs/resources/vat-overview

Re: Cloud TPUs in Beta

#34

Post by gcp »

kyrra wrote: post #33
gcp wrote: post #30

Interestingly, GCP now appears to be available to individuals in Europe. It wasn't like that before, no idea when that policy got changed. Before, GCP wasn't even a consideration compared to AWS (which always handled that).

More details: https://cloud.google.com/billing/docs/resources/vat-overview

"You can’t change the tax status of your Google Cloud Platform billing account."

I think this is what tripped me up before. I closed my business years ago but it was completely impossible to get Google to fix this. Now it fixed it "by itself".

Just a warning to everyone before signing up with your main Google account :-)

Re: Cloud TPUs in Beta

#37

Post by Cyph0n »

saguro wrote: post #29
Cyph0n wrote: post #23

Earlier quoted context omitted.

GPUs are much more complex (general-purpose) and therefore cannot be optimized beyond a certain point due to timing requirements and PVT (process, temperature, voltage) variations. In other words, the more stuff you have on an ASIC, the more careful you have to be ensure a margin of tolerance for variations.

So the only advantage of the TPU is it's a simpler and more specialized asic? Google didn't break any new ground in terms of training perf?

> So the only advantage of the TPU is it's a simpler and more specialized asic

And everything that entails: lower energy consumption, higher throughput, lower cost at volume, higher profits for GCP, etc.

> Google didn't break any new ground in terms of training perf?

Relative to GPUs, sure, but I can't say how well they stack up against other custom ASICs for DL applications.

Re: Cloud TPUs in Beta

#38

Post by borramakot »

minimaxir wrote: post #6

That $6.50/hr rate might be the big deal here. Amazon does offer instances with a V100 GPU ( https://aws.amazon.com/ec2/pricing/on-demand/ , the P3 instances), but if you're training something like ImageNet, you'll want the biggest image (p3.16xlarge) at $24.48/hr . Attaching a VM of similar power to a TPU on Google Compute Engine is much cheaper ( https://cloud.google.com/compute/pricing , n1-highmem-64, +$3.78/hr t…

Back of the envelope, a TPU costs a little more than 2x as much as a Volta on AWS P3, and delivers a little less than 2x the performance (180 TOPs for the TPU, 100 for Volta). On a raw performance/$ metric, I'm not sure the TPU is that interesting.

It might be worth it if I were willing to pay a huge amount to get back results from an experiment faster, by using lots of TPUs- distributed learning on GPUs doesn't seem easy yet.

Re: Cloud TPUs in Beta

#39

Post by otterley »

I'm puzzled by the phrase "differentiated performance per dollar."

Is it more performant, or less?

If it's less performant, why mention it at all?

If it's more performant, why not simply say "better performance per dollar"?

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