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Installation

You can install RAPIDS using Docker (the fastest), or native instructions for MacOS and Linux (Ubuntu). Windows is supported through Docker or WSL.

  1. Install Docker

  2. Pull our RAPIDS container

    docker pull moshiresearch/rapids:latest
    

  3. Run RAPIDS' container (after this step is done you should see a prompt in the main RAPIDS folder with its python environment active)

    docker run -it moshiresearch/rapids:latest
    
  4. Pull the latest version of RAPIDS

    git pull
    
  5. Make RAPIDS script executable

    chmod +x rapids
    

  6. Check that RAPIDS is working

    ./rapids -j1
    

  7. Optional. You can edit RAPIDS files with vim but we recommend using Visual Studio Code and its Remote Containers extension

    How to configure Remote Containers extension
    • Make sure RAPIDS container is running
      • Install the Remote - Containers extension
      • Go to the Remote Explorer panel on the left hand sidebar
      • On the top right dropdown menu choose Containers
      • Double click on the moshiresearch/rapids container in theCONTAINERS tree
      • A new VS Code session should open on RAPIDS main folder inside the container.

Warning

If you installed RAPIDS using Docker for Windows on Windows 10, the container will have limits on the amount of RAM it can use. If you find that RAPIDS crashes due to running out of memory, increase this limit.

We tested these instructions in Catalina

  1. Install brew

  2. Install MySQL

    brew install mysql
    brew services start mysql
    
  3. Install R 4.0, pandoc and rmarkdown. If you have other instances of R, we recommend uninstalling them

    brew install r
    brew install pandoc
    Rscript --vanilla -e 'install.packages("rmarkdown", repos="http://cran.us.r-project.org")'
    
  4. Install miniconda (restart your terminal afterwards)

    brew cask install miniconda
    conda init zsh # (or conda init bash)
    
  5. Clone our repo

    git clone https://github.com/carissalow/rapids
    
  6. Create a python virtual environment

    cd rapids
    conda env create -f environment.yml -n rapids
    conda activate rapids
    
  7. Install R packages and virtual environment:

    snakemake -j1 renv_install
    snakemake -j1 renv_restore
    

    Note

    This step could take several minutes to complete, especially if you have less than 3Gb of RAM or packages need to be compiled from source. Please be patient and let it run until completion.

  8. Make RAPIDS script executable

    chmod +x rapids
    

  9. Check that RAPIDS is working

    ./rapids -j1
    

We tested RAPIDS on Ubuntu 18.04 & 20.04. Note that the necessary Python and R packages are available in other Linux distributions, so if you decide to give it a try, let us know and we can update these docs.

  1. Install dependencies

    sudo apt install libcurl4-openssl-dev
    sudo apt install libssl-dev
    sudo apt install libxml2-dev
    sudo apt install libglpk40
    
  2. Install MySQL

    sudo apt install libmysqlclient-dev
    sudo apt install mysql-server
    
  3. Add key for R’s repository.

    sudo apt-key adv --keyserver keyserver.ubuntu.com --recv-keys E298A3A825C0D65DFD57CBB651716619E084DAB9
    
  4. Add R’s repository

    sudo add-apt-repository 'deb https://cloud.r-project.org/bin/linux/ubuntu bionic-cran40/'
    
    sudo add-apt-repository 'deb https://cloud.r-project.org/bin/linux/ubuntu focal-cran40/'
    
  5. Install R 4.0. If you have other instances of R, we recommend uninstalling them

    sudo apt update
    sudo apt install r-base
    
  6. Install Pandoc and rmarkdown

    sudo apt install pandoc
    Rscript --vanilla -e 'install.packages("rmarkdown", repos="http://cran.us.r-project.org")'
    
  7. Install git

    sudo apt install git
    
  8. Install miniconda

  9. Restart your current shell

  10. Clone our repo:

    git clone https://github.com/carissalow/rapids
    
  11. Create a python virtual environment:

    cd rapids
    conda env create -f environment.yml -n MY_ENV_NAME
    conda activate MY_ENV_NAME
    
  12. Install the R virtual environment management package (renv)

    snakemake -j1 renv_install
    
  13. Restore the R virtual environment

    Run the following command to restore the R virtual environment using RSPM binaries

    R -e 'renv::restore(repos = c(CRAN = "https://packagemanager.rstudio.com/all/__linux__/bionic/latest"))'
    

    Run the following command to restore the R virtual environment using RSPM binaries

    R -e 'renv::restore(repos = c(CRAN = "https://packagemanager.rstudio.com/all/__linux__/focal/latest"))'
    

    If the fast installation command failed for some reason, you can restore the R virtual environment from source:

    R -e 'renv::restore()'
    

    Note

    This step could take several minutes to complete, especially if you have less than 3Gb of RAM or packages need to be compiled from source. Please be patient and let it run until completion.

  14. Make RAPIDS script executable

    chmod +x rapids
    

  15. Check that RAPIDS is working

    ./rapids -j1
    

There are several options varying in complexity:

  • You can use our Docker instructions (tested)
  • You can use our Ubuntu 20.04 instructions on WSL2 (not tested but it will likely work)
  • Native installation (experimental). If you would like to contribute to RAPIDS you could try to install MySQL, miniconda, Python, and R 4.0+ in Windows and restore the Python and R virtual environments using steps 6 and 7 of the instructions for Mac. You can get in touch if you would like to discuss this with the team.