Cloud GPUs Tutorial (comparing & using)
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Wednesday, July 28, 2021
Do not bother with Linode. They do not even have any GPUs available. Such a waste of time. Here's an email I received from their support.
"At this time, we do not have any GPUs available. Additionally, we typically need to see at least three months of billing history before granting GPU access."
I tried requesting access to GPUs on Google Cloud and was denied about 2 minutes after submitting my request, despite having my google account for ~18 years. AWS it is I guess….
Did anyone try a game streaming provider, which provides a full desktop environment, to train NNs?
Eg shadow offers a GTX 1080 comparable card for only 13€/15€/month
The card isnt the fastest, but compared to the cloud gpu providers they seem (for me) to be very cheap. For longer training sessions i could use a raspberry pi to keep the session open.
Also i could obviously use that provider to play some games 😀
Did i miss something or why is nobody doing this?
This is the best videos on this topic available! Thank you so much! I just tried this out. Not sure it was like this a year ago but now you can just "upgrade" & "downgrade" by clicking on a button.
Maybe the transfer rate you are used to is 100 mega bits / sec, and this is just 12 mega BYTES per second. I believe a megabit is 1/8 the size of a megabyte, so 12*8 ~= 100 mega bits / sec.
Again, could be wrong, but I think the standard is Mb is megabit, and MB is megabyte.
Here you can see all the services for different places: https://www.linode.com/global-infrastructure/
If I see correct, only Newark has GPUs at the moment.
Update: I just had contact with their support, Mumbai also has GPUs
How do you delete the server at the end so you don't have to keep paying?
I’m completely new to training models on a gpu. So is the purpose of this to come up with your model architecture on your local machine… over like a Jupiter notebook. Then when you are ready to pre process data and train your model…you move your info to the GPU and do those actions on the GPU? Then once your model is trained you shutdown the GPU and can use the trained model elsewhere?
You are master.
Fantastic tutorial, thanks!!! Just one question: when you tested on modelfit.py, you mentioned that we may want to do those np.array data preprocessing on another server. Could you provide a tutorial on this topic? The reason I am asking is because data preprocessing is a big part of deep learning exercises. And a lot of times I am using paperspace GPU servers to handle it (I don't know other efficient approaches)
Is there a way to directly download huge public datasets onto the GPU server or Cloud storage?
training on vast.ai with non-sensitive datasets is another cheaper option
Hey Sentdex how come you suspect the guys offering the RTX6000 would be running at a loss?
so this is James McAvoy teaching me how to set up a cloud GPU, fantastic
Not so fast at all.
In GTX 980: "3s 173us/sample".
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cudaGetDevice() failed. Status: cudaGetErrorString symbol not found
Can you help me with my error? I'm trying to follow your tutorial with the cats-and-dogs dataset and i get this error when i try to run the CNN. I have a 1050 GTX
rsync with compression is faster than scp.
Also, your transfer speeds seem to be limited by the read speed of the spinning rusts.
For reinforcement learning do you recommend a virtual desktop instead?
Why have you created a data-server and a rtx6000gpu, you couldn`t just uploaded your data to the rtx6000gpu ??
got 3 seconds per epoch
~150μs/sample on a single local GTX1080
24s on a Titan RTX looks strangely sloooow?
isn't paperspace better ?… and doesnt require these setups
For the scp you were using the public ip of the server so the traffic had to go through more hops than if you were using internal ips, which I guess that you could have created as the servers are in the same lan.
What are some good VPS's for discord bots or sites or whatever?
Google cloud has $300 credit for one year, which is something to consider.
Great video!! Thank you for wonderful content as always.
Try rsync -a instead of scp
Sentdex, can you teach bitcoin mining using cpu python coding
😀 I am using google colab, it is pain to use but is free and you can even mount google drive on it + it comes with pre installed machine learning libraries and stuff. And tesla gpus
scp -C for compression
Why not use GCP TPU ?
Do you know how to match two list that is a two 2d list?
As a beginner to deep learning this was a big help. Thanks Sentdex!
Which OS you are using?
Linode has internal IP’s. Under the network tab in dash. For me at least It works way way faster when I do scp.
I'd like to see that 4xv100 with 4xrtx6000 comparison
Sentdex is OP … Mad underrated!
MegaBytes/sec 🙂
What about spell.run? You can just code locally, but when you want to run your code on the cloud, you just add "spell run" before your "python script.py" and it will only charge you for the run.