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Set of conda environments for KAUST linux machines and clusters

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CondaEnvs KAUST

Set of conda environments for KAUST linux machines and clusters at KAUST.

First of all install Miniconda following instructions at: https://github.com/kaust-rccl/ibex-miniconda-install

For each environment, an environment_$ENVNAME.yml file is provided alongside with a shell installation script install_$ENVNAME.sh.

Simply run:

./install_$ENVNAME.sh $PATH_TO_DEV_LIB

where $PATH_TO_DEV_LIB contains the path of the library to install in developer mode (if empty, the library will be installed in user mode using pip or conda installers).

Environments

  • Scientific: CPU installation of basic scientific stack (customize this to your needs)

  • Azure_CLI: CPU installation of azure-cli (to be able to programmatically download Volve data)

  • MPI4PY: CPU installation of basic scientific stack with MPI4Py

  • PyLops: CPU installation of PyLops and its dependencies

  • PyLops_36: CPU installation of PyLops and its dependencies

  • PyLops_37: CPU installation of PyLops and its dependencies

  • PyLops_cupy: GPU-enabled installation of PyLops with Cupy (cuda11.1.0)

  • PyLops_cupy_cusignal: GPU-enabled installation of PyLops with Cupy + CuSignal (cuda10.2.89)

  • PyLops_cupy_cusignal_3090: GPU-enabled installation of PyLops with Cupy + CuSignal (cuda11.0 to be used with GeForce RTX 3090)

  • PyLops_cupy_mpi4py_3090: GPU-enabled installation of PyLops with Cupy + PyLops (cuda11.8 to be used with GeForce RTX 3090)

  • PyLops_gpu: GPU-enabled installation of PyLops-gpu with PyTorch + Cupy (cuda10.2.89)

  • PyLops_gpu_3090: GPU-enabled installation of PyLops-gpu with PyTorch + Cupy (cuda11.0 to be used with GeForce RTX 3090)

  • PyLops_diffusers_3090: GPU-enabled installation of PyLops-gpu with PyTorch + Cupy + Diffusers (cuda11.8 to be used with GeForce RTX 3090)

  • PyLops_dist: CPU installation of PyLops-distributed and its dependencies

  • Devito: CPU installation of Devito

  • EGS: Stanford GPU-enabled FD propagators and PDE-constrained inversion

Adds on:

  • Jupyter Extensions: install Jupyter extensions (e.g., TOC)
  • Curvelops: install FFWT, Curvelab and Curvelops (works only with PyLops_36 and PyLops_37)

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