diff --git a/workshop-instructions/imgs/duo_01.png b/workshop-instructions/imgs/duo_01.png index 6ec5cef..2c1d5cc 100644 Binary files a/workshop-instructions/imgs/duo_01.png and b/workshop-instructions/imgs/duo_01.png differ diff --git a/workshop-instructions/imgs/duo_02.png b/workshop-instructions/imgs/duo_02.png index 4b14a46..c4fe325 100644 Binary files a/workshop-instructions/imgs/duo_02.png and b/workshop-instructions/imgs/duo_02.png differ diff --git a/workshop-instructions/imgs/duo_03.png b/workshop-instructions/imgs/duo_03.png deleted file mode 100644 index 9efa6bd..0000000 Binary files a/workshop-instructions/imgs/duo_03.png and /dev/null differ diff --git a/workshop-instructions/instructions.html b/workshop-instructions/instructions.html index 5b88d35..386a9b3 100644 --- a/workshop-instructions/instructions.html +++ b/workshop-instructions/instructions.html @@ -128,28 +128,27 @@

Logging in to OOD

  • Enter your selected username into ‘Username’ field of the login page

  • Enter the password: HNNws2024*

    • -
    +

    1. From the DUO authentication screen, select “Other options” and then choose “Bypass code”
    -

    +
    -
    -
      +
      1. Enter the bypass code associated with the username you selected in Step 2
      -

      +

    Launching the Desktop App on Oscar

    1. Choose the “Desktop (Advanced)” application. Note that this is different form the regular “Desktop” app.
      2. @@ -193,24 +192,26 @@

      Installing 
      pip install --pre hnn-core[gui]

      For zsh

      pip install --pre hnn-core'[gui]'
      +

      Once installed, you can launch the GUI with the following command.

      +
      hnn-gui

      Note that you will not be able to utilize the MPI backend to run simulation in parallel without also installing MPI on your machine. We recommend using the Conda install method below if you would like to utilize MPI, as it significantly streamlines the MPI setup process.

      For our workshops, we will be running simulations with only a few trials at most, and so MPI is not strictly necessary to keep up with the materials.

      Installing HNN-Core GUI on Your Local Machine via Conda

      Creating a Conda Env and Installing Dependencies

      Note: We recommend using use Windows Subsystem for Linux (WSL) to run HNN on Windows machines. Installation instructions can be found here

      Start by creating a new conda environment. We recommend creating an environment with the fewest number of dependencies to speed up the installation process.

      -
      conda create --name hnn_core_gui python=3.11 --no-default-packages
-conda activate hnn_core_gui
-pip install --pre hnn-core[gui]
      +
      conda create --name hnn_core_gui python=3.11 --no-default-packages
+conda activate hnn_core_gui
+pip install --pre hnn-core[gui]

      Installing MPI for Parallel Simulations

      To run simulations in parallel across multiple cores, which dramatically speeds up siuations, you’ll need to set up the MPI backend.

      -
      conda activate hnn_core_gui # activate the environment if needed
-conda install -y openmpi mpi4py
-pip install psutil
      +
      conda activate hnn_core_gui # activate the environment if needed
+conda install -y openmpi mpi4py
+pip install psutil

      Additionally, for MacOS, run the following command.

      -
      export DYLD_FALLBACK_LIBRARY_PATH=${CONDA_PREFIX}/lib
      +
      export DYLD_FALLBACK_LIBRARY_PATH=${CONDA_PREFIX}/lib

      More detailedd instructions are available on our parallel backends page.

      Launch the GUI

      You can now launch the GUI from within your conda environemnt.

      -
      conda activate hnn_core_gui # activate the environment if needed
-hnn-gui
      +
      conda activate hnn_core_gui # activate the environment if needed
+hnn-gui
      diff --git a/workshop-instructions/instructions.md b/workshop-instructions/instructions.md index b296661..94163ab 100644 --- a/workshop-instructions/instructions.md +++ b/workshop-instructions/instructions.md @@ -52,7 +52,7 @@ We have created a Google CoLab notebook that allows you to run the HNN-Core GUI 4. Enter the password: HNNws2024* -
      +
      ![](imgs/oscar_login.png) @@ -61,14 +61,14 @@ We have created a Google CoLab notebook that allows you to run the HNN-Core GUI 5. From the DUO authentication screen, select "Other options" and then choose "Bypass code" - +
      -| ![](imgs/duo_01.png) | ![](imgs/duo_02.png) | ![](imgs/duo_03.png) | -|-----------------------------|-----------------------------|-----------------------------| +| ![](imgs/duo_01.png) | ![](imgs/duo_02.png) | +|-----------------------------|-----------------------------| -6. Enter the bypass code associated with the username you selected in Step 2 +1. Enter the bypass code associated with the username you selected in Step 2 - +
      ### Launching the Desktop App on Oscar 1. Choose the "Desktop (Advanced)" application. Note that this is different form the regular "Desktop" app. @@ -131,10 +131,18 @@ pip install --pre hnn-core[gui] pip install --pre hnn-core'[gui]' ``` +Once installed, you can launch the GUI with the following command. + +```bash +hnn-gui +``` + Note that you will not be able to utilize the MPI backend to run simulation in parallel without also installing MPI on your machine. We recommend using the Conda install method below if you would like to utilize MPI, as it significantly streamlines the MPI setup process. For our workshops, we will be running simulations with only a few trials at most, and so MPI is not strictly necessary to keep up with the materials. + + ## Installing HNN-Core GUI on Your Local Machine via Conda ### Creating a Conda Env and Installing Dependencies