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Old 2019-12-11, 08:41   #683
preda
 
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"Mihai Preda"
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Quote:
Originally Posted by kriesel View Post
And I've been having a hard time getting a K80 on the sessions I'm using to benchmark gpuowl P-1 run time scaling and limit. When I started, K80 was all I was getting; now it's the exception.
It would be great for that if Google made it possible to specify what gpu model was required or preferred, instead of just none, gpu, or tpu.
Maybe they are taking feature requests on some forum or issue tracker?
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Old 2019-12-11, 14:22   #684
kriesel
 
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Default gpu model in colab question

Quote:
Originally Posted by preda View Post
Maybe they are taking feature requests on some forum or issue tracker?
After a bit of searching it appears they are using stackoverflow. So:

https://stackoverflow.com/questions/...-or-to-require

5 views in first half hour but no replies yet.

Last fiddled with by kriesel on 2019-12-11 at 14:27
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Old 2019-12-11, 15:22   #685
kracker
 
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Quote:
Originally Posted by kriesel View Post
After a bit of searching it appears they are using stackoverflow. So:

https://stackoverflow.com/questions/...-or-to-require

5 views in first half hour but no replies yet.
If they do implement that, probably no one will use the K80 or P4 - and the P100 and T4's general availability might be significantly less due to everyone wanting those.
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Old 2019-12-11, 18:40   #686
kriesel
 
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Quote:
Originally Posted by kracker View Post
If they do implement that, probably no one will use the K80 or P4 - and the P100 and T4's general availability might be significantly less due to everyone wanting those.
Imagine the following choices, instead of the generic None, GPU, TPU:

None

GPU: P100 preferred (falls back to other gpu if no P100 available)
GPU: P100 required (backend availability fails if no P100 available)
GPU: T4 preferred (falls back to other gpu if no T4 available)
GPU: T4 required (backend availability fails if no T4 available)
GPU: K80 preferred (falls back to other gpu if no K80 available)
GPU: K80 required (backend availability fails if no K80 available)
GPU: P4 preferred (falls back to other gpu if no P4 available)
GPU: P4 required (backend availability fails if no P4 available)
etc. as new GPU models are added
maybe even P100 wait (waits until a P100 is available) etc or
GPU: Any required
GPU: Any optional (run the gpu task if one is available, run the cpu task in any event)
GPU: P100 optional (etc for other models too)

TPU
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Old 2019-12-12, 09:20   #687
bayanne
 
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"Tony Gott"
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This is a new message to me:

Code:
Beginning GPU Trial Factoring Environment Bootstrapping...
Please see https://www.gpu72.com/ for additional details.

20191212_091736: GPU72 TF V0.33 Bootstrap starting...
20191212_091736: Working as "...................."...

20191212_091736: 
20191212_091736: *** FATAL ERROR ***
20191212_091736: GPU not found.  Make sure GPU is enabled (Runtime menu -> Change runtime type).
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Old 2019-12-12, 14:18   #688
chalsall
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"Chris Halsall"
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Quote:
Originally Posted by bayanne View Post
This is a new message to me:
OK. I just restarted one of my running instances to make sure this wasn't something new. It isn't. (Was given a P100 instead of K80 during the exercise.)

What this message means is you tried running the TF Notebook in an instance without a GPU. This can happen if you accidentally hit "Connect" when prompted with the "No GPU Backend available, connect anyway?" message.

Last fiddled with by chalsall on 2019-12-12 at 14:25 Reason: s/Not GPU/No GPU/;
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Old 2019-12-12, 16:02   #689
petrw1
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"Wayne"
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Quote:
Originally Posted by chalsall View Post
What this message means is you tried running the TF Notebook in an instance without a GPU. This can happen if you accidentally hit "Connect" when prompted with the "No GPU Backend available, connect anyway?" message.
It also happened to me when Kaggle for some reason turned off my GPU selection and I had to reenable it.
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Old 2019-12-12, 16:55   #690
Dylan14
 
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"Dylan"
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Quote:
Originally Posted by kriesel View Post
Imagine the following choices, instead of the generic None, GPU, TPU:

It would also be nice if we could specify how many CPU cores we would like to deploy in our instances, depending on available resources.
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Old 2019-12-13, 23:53   #691
lycorn
 
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Sep 2002
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Quote:
Originally Posted by bayanne View Post
Sessions on Colab seem to have reduced from 12 hours to 10 hours now
But only for gpus, as far as I can see. I am currently getting 10 hours on gpus and 12 on cpus.
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Old 2019-12-14, 00:07   #692
matzetoni
 
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Anyone else seeing a blank page instead of your Kaggle kernels results? I can see my kernels list and I can edit / commit them, but I can't see the results of a commited run, it's just a blank page. It was working for me a few hours ago...
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Old 2019-12-14, 01:49   #693
PhilF
 
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Same here. Blank page.

UPDATE: Working again now.

Last fiddled with by PhilF on 2019-12-14 at 02:17
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