One click dev environments for MLIR with CUDA support.

To use GitHub Codespaces, just click the button below.

The following image permutations are available:

• Ubuntu 24.04
• Ubuntu 22.04
• With CUDA 12.8
• No CUDA
• MLIR 20
• MLIR 19

# With CUDA
docker pull ghcr.io/sdiehl/docker-mlir-cuda:mlir20-cuda-ubuntu24.04
docker pull ghcr.io/sdiehl/docker-mlir-cuda:mlir19-cuda-ubuntu24.04

# Without CUDA
docker pull ghcr.io/sdiehl/docker-mlir-cuda:mlir20-ubuntu24.04
docker pull ghcr.io/sdiehl/docker-mlir-cuda:mlir19-ubuntu24.04

# With CUDA
docker pull ghcr.io/sdiehl/docker-mlir-cuda:mlir20-cuda-ubuntu22.04
docker pull ghcr.io/sdiehl/docker-mlir-cuda:mlir19-cuda-ubuntu22.04

# Without CUDA
docker pull ghcr.io/sdiehl/docker-mlir-cuda:mlir20-ubuntu22.04
docker pull ghcr.io/sdiehl/docker-mlir-cuda:mlir19-ubuntu22.04

To run any of these images:

docker run -it ghcr.io/sdiehl/docker-mlir-cuda:<tag> bash

Or in your Dockerfile:

FROM ghcr.io/sdiehl/docker-mlir-cuda:<tag>

This repository includes a devcontainer.json file in the .devcontainer directory. This allows you to use Visual Studio Code's Remote - Containers extension to develop inside a container.

1. Install Visual Studio Code.
2. Install the Remote - Containers extension.
3. Clone this repository.
4. Open the repository in Visual Studio Code.
5. When prompted, reopen the repository in a container.

This will build and start a development container using the settings specified in the devcontainer.json file.

You can use this development environment directly in GitHub Codespaces:

1. Navigate to the repository on GitHub
2. Click the "Code" button
3. Select the "Codespaces" tab
4. Click "Create codespace on main"
5. In the options dialog, select "MLIR CUDA Dev Container" as the base image
6. Wait for the codespace to build and start

CUDA binaries are installed to /usr/local/cuda/bin/ and the CUDA libraries are installed to /usr/local/cuda/lib64/.

To append to your paths add the following to ~/.bashrc:

export PATH=/usr/local/cuda/bin:$PATH
export LD_LIBRARY_PATH=/usr/local/cuda/lib64:$LD_LIBRARY_PATH