I follow the development of
in order to maintain GHC musl – Unofficial binary distributions of GHC on Alpine Linux.
ℹ️ The multi-arch (linux/amd64
, linux/arm64/v8
) docker image used to build the
statically linked Linux amd64 and arm64 binary releases of
Images available at
- Quay:
quay.io/benz0li/ghc-musl
- Docker Hub:
docker.io/benz0li/ghc-musl
- GitLab (b-data GmbH):
glcr.b-data.ch/ghc/ghc-musl
@b-data, I devote about 20% of my time to open-source software maintaining dev containers, docker images and deployment templates for Data Scientists.
- Multi-arch Mojo Dev Container1
- Multi-arch docker images1
- (GPU accelerated) Multi-arch Data Science Dev Containers1
- (GPU accelerated) Multi-arch docker images1:
- (CUDA-enabled) JupyterLab QGIS docker stack
- (CUDA-enabled) JupyterLab Python docker stack
- (CUDA-enabled) JupyterLab Julia docker stack
- (CUDA-enabled) JupyterLab R docker stack
All JupyterLab images include- code-server
→ VS Code in the browser - Git
- Git LFS
- Pandoc
- Zsh
GPU accelerated images include - CUDA runtime,
CUDA math libraries,
NCCL and
cuDNN
- including development libraries and headers
- TensortRT and TensorRT plugin libraries
- including development libraries and headers
- code-server
- (CUDA-enabled) Python docker stack
- (CUDA-enabled) Julia docker stack
- (CUDA-enabled) R docker stack
Siblings2 of the JupyterLab images without- code-server
- IRKernel/IPython/IJulia
- JupyterHub/JupyterLab
- Jupyter Notebook
- LSP Servers
- Oh My Zsh
- Widgets
GPU accelerated images include - CUDA runtime,
CUDA math libraries,
NCCL and
cuDNN
- without development libraries and headers
- TensortRT and TensorRT plugin libraries
- without development libraries and headers
- Customised Docker Hub images1:
- Containerised source installations1:
- Containerised installations1:
- Docker deployment templates: