diff --git a/README.md b/README.md index be1665ba..18f07e8b 100644 --- a/README.md +++ b/README.md @@ -165,6 +165,14 @@ to indicate the copyright and license terms: ## Alternatives +- [b-data](https://github.com/b-data)'s JupyterLab docker stacks - For + [R](https://github.com/b-data/jupyterlab-r-docker-stack), + [Python](https://github.com/b-data/jupyterlab-python-docker-stack), + [MAX/Mojo](https://github.com/b-data/jupyterlab-mojo-docker-stack) and + [Julia](https://github.com/b-data/jupyterlab-julia-docker-stack). + With [code-server](https://github.com/coder/code-server) next to JupyterLab. + Just Python – no [Conda](https://github.com/conda/conda) / + [Mamba](https://github.com/mamba-org/mamba). - [rocker/binder](https://rocker-project.org/images/versioned/binder.html) - From the R focused [rocker-project](https://rocker-project.org), lets you run both RStudio and Jupyter either standalone or in a JupyterHub diff --git a/docs/using/selecting.md b/docs/using/selecting.md index fcb77909..0d325521 100644 --- a/docs/using/selecting.md +++ b/docs/using/selecting.md @@ -338,7 +338,7 @@ See the [contributing guide](../contributing/stacks.md) for information about ho | [GPU-Jupyter][gpu] | Power of your NVIDIA GPU and GPU calculations using Tensorflow and Pytorch in collaborative notebooks. This is done by generating a Dockerfile that consists of the **nvidia/cuda** base image, the well-maintained **docker-stacks** that is integrated as a submodule, and GPU-able libraries like **Tensorflow**, **Keras** and **PyTorch** on top of it. | | [myLab TH Lübeck Images][gpu_thl] | Images based on the **jupyter/docker-stacks**, built and maintained at the [myLab TH Lübeck][gpu_mylab] using build scripts similar to iot-salzburg. Several images include GPU libraries. | | [PRP-GPU][prp_gpu] | PRP (Pacific Research Platform) maintained [registry][prp_reg] for jupyter stack based on NVIDIA CUDA-enabled image. Added the PRP image with Pytorch and some other Python packages and GUI Desktop notebook based on . | -| [b-data][b-data] | GPU accelerated, multi-arch (`linux/amd64`, `linux/arm64/v8`) docker images for [R][r_cuda], [Python][python_cuda] and [Julia][julia_cuda]. Derived from nvidia/cuda `devel`-flavored images, including TensortRT and TensorRT plugin libraries. With [code-server][code-server] next to JupyterLab. Just Python – no [Conda][conda]/[Mamba][mamba]. | +| [b-data][b-data] | GPU accelerated, multi-arch (`linux/amd64`, `linux/arm64/v8`) Docker images for [R][r_cuda], [Python][python_cuda] , [MAX][max_cuda] and [Julia][julia_cuda]. Derived from nvidia/cuda `devel`-flavored images. With [code-server][code-server] next to JupyterLab. Just Python – no [Conda][conda] / [Mamba][mamba]. | [gpu]: https://github.com/iot-salzburg/gpu-jupyter [gpu_thl]: https://hub.docker.com/r/hanseware/jlab-images @@ -348,6 +348,7 @@ See the [contributing guide](../contributing/stacks.md) for information about ho [b-data]: https://github.com/b-data [r_cuda]: https://github.com/b-data/jupyterlab-r-docker-stack/blob/main/CUDA.md [python_cuda]: https://github.com/b-data/jupyterlab-python-docker-stack/blob/main/CUDA.md +[max_cuda]: https://github.com/b-data/jupyterlab-mojo-docker-stack/blob/main/CUDA.md [julia_cuda]: https://github.com/b-data/jupyterlab-julia-docker-stack/blob/main/CUDA.md [code-server]: https://github.com/coder/code-server [conda]: https://github.com/conda/conda