fake-gpu

Project Overview

The fake-gpu project is designed to simulate GPU information, making it easier to test scenarios where a GPU is not available. This can be particularly useful for development and testing purposes in environments that lack physical GPU hardware.

Features

• Simulate GPU information through configuration files
• Unable to Perform Genuine CUDA Computation
• Test GPU-related functions without GPU hardware
• Non-intrusive, no need to modify application code
• Supports CUDA Driver, CUDA Runtime, NVML API
• Supports nvidia-smi
• Supports DCGM-Exporter

Requirements

• containerd >= 1.7.0

Usage

To use the fake GPU, follow these steps:

You should have a Kubernetes cluster running with containerd as the container runtime. You should have already deployed nvidia-device-plugin or HAMi.

Option 1: Deploy the nvidia-device-plugin

 kubectl create -f https://raw.githubusercontent.com/NVIDIA/k8s-device-plugin/v0.17.0/deployments/static/nvidia-device-plugin.yml

Option 2: Deploy the HAMi

helm repo add hami-charts https://project-hami.github.io/HAMi/
helm install hami hami-charts/hami  -n kube-system

Deploy the fake GPU

1. Download the latest release of the fake GPU.

wget https://github.com/chaunceyjiang/fake-gpu/releases/download/v0.3.0/fake-gpu-helm-chart-v0.3.0.tgz

2. Deploy the fake GPU to your Kubernetes cluster.

helm install fake-gpu fake-gpu-helm-chart-v0.3.0.tgz

3. Configure your application to use the GPU.

cat <<EOF | kubectl apply -f -
apiVersion: v1
kind: Pod
metadata:
  name: fake-gpu
spec:
  containers:
  - name: fake-gpu
    image: nginx
    resources:
      limits:
        nvidia.com/gpu: 1
EOF

4. Run your application as you would with a real GPU.

kubectl exec -it fake-gpu -- nvidia-smi
+---------------------------------------------------------------------------------------+
| NVIDIA-SMI 470.129.06           Driver Version: 440.33.01          CUDA Version: 12.2 |
+-----------------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M          | Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap          |         Memory-Usage | GPU-Util  Compute M. |
|                                         |                      |               MIG M. |
+-----------------------------------------+----------------------+----------------------+
|   1  NVIDIA Tesla P4                Off |                  Off |                  Off |
| N/A   33C    P8    11W /  70W           |      0MiB / 15411MiB |       0%     Default |
|                                         |                      |                  N/A |
+-----------------------------------------+----------------------+----------------------+

+---------------------------------------------------------------------------------------+
| Processes:                                                                            |
|  GPU   GI   CI        PID   Type   Process name                            GPU Memory |
|        ID   ID                                                             Usage      |
+---------------------------------------------------------------------------------------+
|    1   N/A  N/A       19       G   /usr/local/nginx                           3200MiB |
+---------------------------------------------------------------------------------------+

Compilation

To compile the project, follow these steps:

make docker-build IMAGE_VERSION=v0.2.0
helm template charts/fake-gpu --set imag.repository=chaunceyjiang/fake-gpu  --set image.tag=v0.2.0 --set nri.runtime.patchConfig=false > install.yaml
kubectl apply -f install.yaml

Contributing

We welcome contributions to the fake-gpu project. To contribute, follow these guidelines:

1. Fork the repository.
2. Create a new branch for your feature or bugfix.
3. Make your changes and commit them with descriptive commit messages.
4. Push your changes to your forked repository.
5. Create a pull request to the main repository.

Please ensure your code follows the project's coding standards and includes appropriate tests.