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Servers#

The web-based servers run on the cluster, and users can access them directly from their browsers. We offer several Jupyter Lab-based apps as well as RStudio.

Jupyter Lab#

This app launch the Jupyter Lab with specific Python version and libraries, based on these Anaconda versions:

  • Anaconda3 2024.06-1, python 3.12.4
  • Anaconda3 2024.02-1, python 3.11.7
  • Anaconda3 2023.07-2, python 3.11.4
  • Anaconda3 2023.03-1, python 3.10.9

You can also load other modules in your environment, for instance CUDA related modules.

jupyter

ML/AI#

Jupyter Lab + Tensorflow, PyTorch and some other common ML libraries:

  • Python/3.10.8-GCCcore-12.2.0
  • JupyterLab/4.0.3-GCCcore-12.2.0
  • CUDA/12.2.0
  • cuDNN/8.9.2.26-CUDA-12.2.0
  • genomap/1.3.6-TF2.15.0-Torch2.2
  • PyTorch/2.2.0-Py3.10.8
  • TensorFlow/2.15.0-torch2.2-Py310

PyTorch#

Jupyter Lab + different PyTorch versions:

  • PyTorch-2.2, CUDA-12.3, NGC Container, python 3.10.12
  • PyTorch-2.1, CUDA-11.7, Anaconda3 2023.03-1, python 3.10.9
  • PyTorch-1.12.1, CUDA-11.7, python 3.10.4

The NGC container is optimized for use with NVIDIA GPUs, and contains the following software for GPU acceleration:

torch

RStudio#

Rstudio server with specific R and R packages from the Rocker project. Currently we ship:

  • R 4.3.2 + Rstudio + Geospatial packages (rocker-4.3.2-geospatial)
  • R 4.3.2 + Rstudio (rocker-4.3.2-rstudio)
  • R 4.2.1 + Rstudio + Geospatial packages (rocker-4.2.1-geospatial)

rstudio

TensorFlow#

Jupyter Lab + TensorFlow. Available versions are:

The NVIDIA TensorFlow Container is optimized for use with NVIDIA GPUs, and contains the following software for GPU acceleration:

We have included additional packages and extensions to enhance the user experience. These include:

tensorflow