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add chart to public repo #4

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joaocc opened this issue Mar 14, 2020 · 7 comments
Open

add chart to public repo #4

joaocc opened this issue Mar 14, 2020 · 7 comments

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@joaocc
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joaocc commented Mar 14, 2020

Hi,
Thx for publishing this.
Have you thought on making this available in the helm chart public repo?
Thx

@wind0r
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wind0r commented Mar 15, 2020

Hi,

Yes, that is an idea for the future.
I first wanted to get this chart to the public and more mature before creating a PR to the public repo :)

Last time a did a change to the public repo it took some months to get merged, so I created this repo first.

Let´s hope that we do not need this charts in some months.

@joaocc
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joaocc commented Mar 15, 2020

We deployed this in a couple of clusters, and it seems to work, but not with GPU.
If you have settings to switch between GPUs (nVidia/ATI/Intel) it would be great, as the chart could be even more plug-and-play.
As for submitting chart, the merge can be quicker. In addition, we can add it to public chart repos, as with Helm3 things are a bit more distributed now.

@joaocc
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joaocc commented Mar 15, 2020

https://chartmuseum.com/ has link to create free chart-registry account in codefresh (https://codefresh.io/codefresh-signup/)

@wind0r
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wind0r commented Mar 15, 2020

Wow! That's really cool to hear!

#1 describes the changed needed to do to make it work at least with nVidia GPUs. I was able to successful test it with my Workstation but I do not have a GPU Cluster to validate the chart. Also, I still wanted to read about the License Agreements. :/

I will check how I can publish the helm chart :)

@joaocc
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joaocc commented Mar 15, 2020

I think both things could be separate.
There are already some docker images that seem to support GPU (https://hub.docker.com/r/coreweave/fah-gpu).
Using this image should allow the chart to avoid licensing issues, and keep the focus on enabling the GPUs to be accessible on the pods, and aligned with the image.

@fmannhardt
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Got this (the Docker image here: https://hub.docker.com/r/coreweave/fah-gpu ) running on a p3 machine on AWS. However, this requires some set-up on the machine:
https://medium.com/@houdinisparks/deploying-gpu-containers-on-aws-ec2-with-docker-machine-c79c9062d90
And the use of --runtime=nvidia instead of the GPUs argument:

sudo docker run --runtime=nvidia --name fah -p 7396:7396 -v $(pwd)/fah-data:/root -d coreweave/fah-gpu:7.5.1

There is some information on how to get this setup in AWS here:
https://aws.amazon.com/blogs/compute/running-gpu-accelerated-kubernetes-workloads-on-p3-and-p2-ec2-instances-with-amazon-eks/

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