/tag/singularity

  • Rivanna HPC Software

    Overview Research Computing at UVA offers a variety of standard software packages for all Rivanna users. We also install requested software based on the needs of the high-performance computing (HPC) community as a whole. Software used by a single group should be installed by that group’s members, ideally on leased storage controlled by the group. Departments with a set of widely-used software packages may install them to the lsp_apps space. The Research Computing group also provides limited assistance for individual installations. For help installing research software on your PC, please contact Research Software Support at res-consult@virginia.edu. Software Modules and Containers Software on Rivanna is accessed via environment modules or containers.
  • Software Containers

    Overview Containers bundle an application, the libraries and other executables it may need, and even the data used with the application into portable, self-contained files called images. Containers simplify installation and management of software with complex dependencies and can also be used to package workflows. Singularity is a container application targeted to multi-user, high-performance computing systems. It interoperates well with SLURM and with the Lmod modules system. Singularity can be used to create and run its own containers, or it can import Docker containers. Creating Singularity Containers To create your own image from scratch, you must have root privileges on some computer running Linux (any version).
  • Custom Jupyter Kernels

    You can create custom kernels from an Anaconda environment or a Singularity container. In both cases you’ll need to install the ipykernel package. Jupyter kernel based on Anaconda environment To create a custom kernel of the Anaconda environment myenv that uses Python 3.7: module load anaconda/2019.10-py3.7 conda create -n myenv python=3.7 ipykernel <other_packages> source activate myenv python -m ipykernel install –user –name myenv –display-name "My Env" Note: You can customize the display name for your kernel. It is shown when you hover over a tile in JupyterLab. If you do not specify a display name, the default Python [conda env:<ENV_NAME>] will be shown.
  • Keras on Rivanna

    Description Keras is a high-level neural networks application programming interface (API), written in Python and capable of running on top of TensorFlow, CNTK, or Theano. On Rivanna, we provide TensorFlow containers that include the Keras API. Since version 1.12.0, TensorFlow contains its own Keras API implementation as described on the TensorFlow website. Using Keras with TensorFlow containers Like TensorFlow itself, Python code that utlizes the Keras package can be run interactively as Jupyter Notebooks, in interactive shell jobs, or non-interctively as SLURM batch jobs. Rivanna provides several nodes with graphics processing units (GPUs) that should be used when running Keras code.
  • Rivanna HPC Software

    Overview Research Computing at UVA offers a variety of standard software packages for all Rivanna users. We also install requested software based on the needs of the HPC community as a whole. Software used by a single group should be installed by that group’s members, ideally on leased storage controlled by the group. Departments with a set of widely-used software packages may install them to the lsp_apps space. The Research Computing group also provides limited assistance for individual installations. For help installing research software on your PC, please contact Research Software Support at res-consult@virginia.edu. Software Modules and Containers Software on Rivanna is provided via environment modules or as containers.