Fake GPU Operator

🎮 Simulate NVIDIA GPUs in Kubernetes without actual hardware

Note: Container images and Helm charts are now available at ghcr.io/run-ai/fake-gpu-operator.

🚀 Overview

The Fake GPU Operator is a lightweight tool that simulates NVIDIA GPUs in Kubernetes clusters without requiring physical hardware. It provides basic functionality for developers and testers:

• Simulates virtual GPUs on CPU-only nodes
• Supports basic feature discovery and NVIDIA MIG support
• Generates Prometheus metrics for GPU monitoring
• Reduces hardware costs for testing environments

Use cases include:

• Testing GPU-dependent applications
• CI/CD pipeline testing
• Development environments
• Learning and experimentation

✨ Features

• Basic GPU topology simulation
• Prometheus metrics generation
• NVIDIA MIG simulation support
• Configurable GPU types and memory
• Basic nvidia-smi simulation

🏃 Quick Start

Prerequisites

• Kubernetes cluster without NVIDIA GPU Operator
• Helm 3.x
• kubectl CLI tool

1. Label Your Nodes

kubectl label node <node-name> run.ai/simulated-gpu-node-pool=default

2. Install the Operator

helm upgrade -i gpu-operator oci://ghcr.io/run-ai/fake-gpu-operator/fake-gpu-operator --namespace gpu-operator --create-namespace --version <VERSION>

3. Deploy a Test Workload

apiVersion: v1
kind: Pod
metadata:
  name: gpu-pod
spec:
  containers:
  - name: gpu-container
    image: nvidia/cuda-vector-add:v0.1
    resources:
      limits:
        nvidia.com/gpu: 1
    env:
      - name: NODE_NAME
        valueFrom:
          fieldRef:
            fieldPath: spec.nodeName

🛠️ Configuration

GPU Topology

Customize GPU configurations in your values.yaml:

topology:
  nodePools:
    default:
      gpus:
        - type: "Tesla K80"
          memory: "12GB"
          count: 2

GPU Utilization

Control GPU utilization metrics with pod annotations:

metadata:
  annotations:
    run.ai/simulated-gpu-utilization: "10-30"  # Simulate 10-30% GPU usage

🔍 Troubleshooting

Pod Security Admission

To ensure proper functionality, configure Pod Security Admission for the gpu-operator namespace:

kubectl label ns gpu-operator pod-security.kubernetes.io/enforce=privileged

nvidia-smi Support

The operator injects a simulated nvidia-smi tool into GPU pods. Ensure your pods include the required environment variable:

env:
  - name: NODE_NAME
    valueFrom:
      fieldRef:
        fieldPath: spec.nodeName

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

📝 License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.

🙋 Support

• 🐛 Issue Tracker

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Created with ❤️ by Run:ai