runongpu 1.0.1

A CLI tool that runs GitHub projects on free cloud GPUs

RunOnGPU

RunOnGPU is a CLI tool that helps you run GitHub projects on a GPU with minimal setup.

It is useful if you want to test CUDA, PyTorch, or other GPU code but do not have a local NVIDIA GPU.

Requirements

• Windows
• Python 3.12.13+
• Git
• Google Chrome
• Google account for Colab

Install

1. Install anaconda with Python >= 3.12.13 for smooth performance
2. Run following commands in your conda enviroment
3. Make sure you do not touch chrome or move around your cursor as the program runs the code.

pip install runongpu

Check setup:
runongpu doctor

Quick Start

Go to the project you want to run and initialize RunOnGPU:

runongpu init

Enter your GitHub repo URL when asked.

This creates a runongpu.txt file. Edit this file to tell RunOnGPU how to set up, build, test, and run your project.

Then run:

runongpu run

RunOnGPU will open Colab, copy the starter notebook, clone your repo, set the runtime to a T4 GPU, and run your commands. If for some reason, it doesn't work on the first try, press enter in your command line interface to restart the program.

runongpu.txt

You need this to run neccesary commands. You must edit this file to ensure your program runs smoothly.

runongpu.txt controls what happens inside Colab.

It has four sections:

[setup]
# install dependencies here

[build]
# compile or build the project here

[test]
# run tests here

[run]
# run the final program here

Add one command per line.

Example: CUDA

If your repo has this structure:

my-cuda-project/
├── main.cu
└── runongpu.txt

Use:

[setup]

[build]
nvcc main.cu -o vector_add

[test]

[run]
./vector_add

Example: CUDA in a Subfolder

If your repo has this structure:

runongpu-examples/
├── cuda/
│   └── vector-add/
│       └── main.cu
└── runongpu.txt

Use:

[setup]

[build]
cd cuda/vector-add && nvcc main.cu -o vector_add

[test]

[run]
cd cuda/vector-add && ./vector_add

Example: Python

[setup]
pip install -r requirements.txt

[build]

[test]
pytest

[run]
python main.py

Example: CMake

[setup]

[build]
cmake -S . -B build
cmake --build build

[test]
ctest --test-dir build --output-on-failure

[run]
./build/my_program

Notes

On the first run, you may need to sign into Google Colab. RunOnGPU saves the copied notebook URL and reuses it on future runs.

Do not interact with the Colab window while RunOnGPU is setting it up.

Run Tests

python -m pytest