:original_name: cce_10_0345.html

.. _cce_10_0345:

GPU Scheduling
==============

You can use GPUs in CCE containers.

Prerequisites
-------------

-  A GPU node has been created. For details, see :ref:`Creating a Node <cce_10_0363>`.

-  The gpu-beta add-on has been installed. During the installation, select the GPU driver on the node. For details, see :ref:`gpu-beta <cce_10_0141>`.

-  gpu-beta mounts the driver directory to **/usr/local/nvidia/lib64**. To use GPU resources in a container, you need to add **/usr/local/nvidia/lib64** to the **LD_LIBRARY_PATH** environment variable.

   Generally, you can use any of the following methods to add a file:

   #. Configure the **LD_LIBRARY_PATH** environment variable in the Dockerfile used for creating an image. (Recommended)

      .. code-block::

         ENV LD_LIBRARY_PATH /usr/local/nvidia/lib64:$LD_LIBRARY_PATH

   #. Configure the **LD_LIBRARY_PATH** environment variable in the image startup command.

      .. code-block::

         /bin/bash -c "export LD_LIBRARY_PATH=/usr/local/nvidia/lib64:$LD_LIBRARY_PATH && ..."

   #. Define the **LD_LIBRARY_PATH** environment variable when creating a workload. (Ensure that this variable is not configured in the container. Otherwise, it will be overwritten.)

      .. code-block::

                   env:
                     - name: LD_LIBRARY_PATH
                       value: /usr/local/nvidia/lib64

Using GPUs
----------

Create a workload and request GPUs. You can specify the number of GPUs as follows:

.. code-block::

   apiVersion: apps/v1
   kind: Deployment
   metadata:
     name: gpu-test
     namespace: default
   spec:
     replicas: 1
     selector:
       matchLabels:
         app: gpu-test
     template:
       metadata:
         labels:
           app: gpu-test
       spec:
         containers:
         - image: nginx:perl
           name: container-0
           resources:
             requests:
               cpu: 250m
               memory: 512Mi
               nvidia.com/gpu: 1   # Number of requested GPUs
             limits:
               cpu: 250m
               memory: 512Mi
               nvidia.com/gpu: 1   # Maximum number of GPUs that can be used
         imagePullSecrets:
         - name: default-secret

**nvidia.com/gpu** specifies the number of GPUs to be requested. The value can be smaller than **1**. For example, **nvidia.com/gpu: 0.5** indicates that multiple pods share a GPU. In this case, all the requested GPU resources come from the same GPU card.

After **nvidia.com/gpu** is specified, workloads will not be scheduled to nodes without GPUs. If the node is GPU-starved, Kubernetes events similar to the following are reported:

-  0/2 nodes are available: 2 Insufficient nvidia.com/gpu.
-  0/4 nodes are available: 1 InsufficientResourceOnSingleGPU, 3 Insufficient nvidia.com/gpu.

To use GPUs on the CCE console, select the GPU quota and specify the percentage of GPUs reserved for the container when creating a workload.


.. figure:: /_static/images/en-us_image_0000001569022929.png
   :alt: **Figure 1** Using GPUs

   **Figure 1** Using GPUs

GPU Node Labels
---------------

CCE will label GPU-enabled nodes after they are created. Different types of GPU-enabled nodes have different labels.

.. code-block::

   $ kubectl get node -L accelerator
   NAME           STATUS   ROLES    AGE     VERSION                                    ACCELERATOR
   10.100.2.179   Ready    <none>   8m43s   v1.19.10-r0-CCE21.11.1.B006-21.11.1.B006   nvidia-t4

When using GPUs, you can enable the affinity between pods and nodes based on labels so that the pods can be scheduled to the correct nodes.

.. code-block::

   apiVersion: apps/v1
   kind: Deployment
   metadata:
     name: gpu-test
     namespace: default
   spec:
     replicas: 1
     selector:
       matchLabels:
         app: gpu-test
     template:
       metadata:
         labels:
           app: gpu-test
       spec:
         nodeSelector:
           accelerator: nvidia-t4
         containers:
         - image: nginx:perl
           name: container-0
           resources:
             requests:
               cpu: 250m
               memory: 512Mi
               nvidia.com/gpu: 1   # Number of requested GPUs
             limits:
               cpu: 250m
               memory: 512Mi
               nvidia.com/gpu: 1   # Maximum number of GPUs that can be used
         imagePullSecrets:
         - name: default-secret