K
Q

Kubernetes and GPU node cluster implementation practices

6/22/2018

I am trying to understand the K8s gpu practices better, and implementing a small K8s GPU cluster which is suppose to work like below.

This going to be little long explanation, but I hope it will help to have many questions at once place to understand GPU practices better in Kubernetes.

Application Requirement

  • I want to create a K8s autoscale cluster.
  • Pods are running the models say a tensorflow based deep learning program.
  • Pods are waiting for a message in pub sub queue to appear and it can proceed its execution once it recieves a message.
  • Now a message is queued in a PUB/SUB queue.
  • As message is available, pods reads it and execute deep learning program.

Cluster requirement

If no message is present in queue and none of the GPU based pods are executing program( i mean not using gpu), then gpu node pool should scale down to 0.

Design 1

Create a gpu node pool. Each node contains N GPU, where N >= 1. Assign model trainer pod to each gpu. That is 1:1 mapping of pods and GPU. When I tried assigning 2 pods to 2 GPU machine where each pod is suppose to run a mnist program.

What I noticed is

1 pod got allocated and executes the program and later it went into crash loop. May be I am doing some mistake as my docker image is suppose to run program once only as I was just doing feasibility test of running 2 pods simultaneously on 2 gpu of same node.Below is the error

Message Reason First Seen Last Seen Count Back-off restarting failed container BackOff Jun 21, 2018, 3:18:15 PM Jun 21, 2018, 4:16:42 PM 143 pulling image "nkumar15/mnist" Pulling Jun 21, 2018, 3:11:33 PM Jun 21, 2018, 3:24:52 PM 5 Successfully pulled image "nkumar15/mnist" Pulled Jun 21, 2018, 3:12:46 PM Jun 21, 2018, 3:24:52 PM 5 Created container Created Jun 21, 2018, 3:12:46 PM Jun 21, 2018, 3:24:52 PM 5 Started container Started Jun 21, 2018, 3:12:46 PM Jun 21, 2018, 3:24:52 PM 5

The other pod didn't get assigned at all to GPU. Below is the message from pod events

0/3 nodes are available: 3 Insufficient nvidia.com/gpu.

Design 2

Have multiple GPU machines in gpu node pool with each node having only 1 GPU.
K8s, will assign each pod to each available GPU in node and hopefully there won't be any issue. I am yet to try this.

Questions

  1. Is there any suggested practice to design above type of system in kubernetes as of version 1.10?
  2. Is Design 1 approach not feasible as of 1.10 release? For eg, I have 2 GPU node with 24 GB GPU memory, is it possible such that K8s assign 1 pod to each GPU and each pods execute its own workload with 12GB memory limit each?
  3. How do I scale down gpu node pool to 0 size through autoscaler?
  4. In Design 2, say what if I run out of GPU memory? as curently in GCP 1 GPU node doesn't have more than 16 GB memory.

Again apologies for such a long question, but I hope it will help other also.

Updates

For question 2 I created a new cluster to reproduce same issue which I faced multiple times before, I am not sure what changed this time but 2nd pod is successfully allocated a GPU. I think with this result I can confirm that 1gpu-1pod mapping is allowed in a multi gpu single node However restricting memory per gpu process is not feasible as of 1.10.

-- Neeraj
google-kubernetes-engine
kubernetes
tensorflow

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1 Answer

6/24/2018

Both designs are supported in 1.10. I view design 2 as a special case of 1. You don't necessarily need to have 1 GPU per node. In case your pod needs more GPUs and memory, you have to have multiple GPUs per node, as you mentioned in question (4). I'd go with 1 unless there's a reason not to.

I think the best practice would be create a new cluster with no GPUs (a cluster has a default node pool), and then create a GPU node pool and attach it to the cluster. Your non-GPU workload can run in the default pool, and the GPU workload can run in the GPU pool. To support scaling-down to 0 GPUs, you need to set --num-nodes and --min-nodes to be 0 when creating the GPU node pool.

Docs:

Create a cluster with no GPUs: https://cloud.google.com/kubernetes-engine/docs/how-to/creating-a-cluster#creating_a_cluster

Create a GPU node pool for an existing cluster: https://cloud.google.com/kubernetes-engine/docs/concepts/gpus#gpu_pool

-- user571470
Source: StackOverflow