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Node Selectors

Node Selectors allow you to assign Pods to specific nodes within a cluster. This is especially useful in environments where different workloads require different hardware configurations, such as CPU-intensive or GPU-intensive tasks. By using node selectors, you can optimize resource utilization and ensure that your applications run on the most suitable hardware.

Documentation

You can learn more about Node Selectors in the Kubernetes documentation.

Managing Node Selectors​

To select a particular GPU type use the selector gpu.nvidia.com/class: <gpu-selector> in your resource spec.

SelectorTypeUse
H100SXM-80H100 SXM 80GBTrain complex deep learning models and high performance inference tasks
H100-80H100 PCIE 80GBHigh performance inference/training
L40SL40S PCIE 48GBHigh performance graphics/inference/training GPU
L4L4 PCIE 24GBLower cost graphics/inference/training GPU

Adding Node Selectors​

To add a node selector to your pod configuration, you need to include the nodeSelector field in your pod’s specification. Here's how you can specify node selectors for both GPU and CPU nodes:

Deploying to GPU-Enabled Nodes

To deploy a pod that requires a GPU, add a node selector to your pod's specification to ensure it runs on a node equipped with a GPU.

apiVersion: v1
kind: Pod
metadata:
  name: gpu-pod
spec:
  containers:
  - name: cuda-container
    image: nvidia/cuda:10.2-base
    resources:
      limits:
        nvidia.com/gpu: 1 # Requesting 1 NVIDIA GPU
  nodeSelector:
    gpu.nvidia.com/class: H100-80 # New selector for specific GPU class

In this example, the pod gpu-pod is configured to run on nodes labeled with gpu.nvidia.com/class: H100-80. The container cuda-container will utilize an NVIDIA CUDA image, specifically requiring a GPU to operate.

Deploying to CPU-Only Nodes

If you need to deploy a pod that does not require a GPU, you can simply omit the GPU resources.

apiVersion: v1
kind: Pod
metadata:
  name: cpu-pod
spec:
  containers:
  - name: web-server
    image: nginx

This configuration ensures that the cpu-pod, which runs a simple NGINX web server, will be placed on any node that has the capacity to run this workload.

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