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GPU Optimization with Run:ai Atlas
Introduction Overview of Run:ai Atlas platform Reference Architecture of Run:ai Atlas on Dell infrastructure Use case validation for Run:ai Atlas Deployment Considerations
Overview
Installing Symcloud Platform
Installing GPU operator
Installing Run:ai Atlas platform
Why Dell Technologies? Dell Technologies services and support The Dell Technologies Customer Solutions Center Conclusion References

Installing GPU operator

Installing GPU operator

  • We manually installed GPU driver on each worker node. To install the GPU operator:

    1. Before installing the NVIDIA GPU driver, install the kernel headers and gcc complier:

    $ dnf group install "Development Tools"

    $ dnf install kernel-devel-$(uname -r) kernel-headers-$(uname -r)

    1. Download and install NVIDIA driver version 525 by running the NVIDIA-Linux-x86_64-525.65.run file and following the prompts.
    2. Verify the driver installation by running the nvdia-smi command.
    3. Ensure that MIG is turned off.
    4. Reboot the server if required
    5. Install the GPU operator by using the following helm commands:

    $ helm repo add nvidia https://helm.ngc.nvidia.com/nvidia

    $ helm repo update

    $ helm install --wait --generate-name -n robinio nvidia/gpu-operator --set driver.enabled=false,toolkit.version=v1.11.0-ubi8 --version v22.9.2

    1. Verify the GPU installation by using the kubectl get pods -n robinio | grep nvidia command: