tacc-deep-learning-tutorials

This repository contains hands-on tutorials and materials that accompany the Deep Learning section of the Life Sciences Machine Learning Institute at the Texas Advanced Computing Center (TACC).

1. Accessing Frontera

Log into Frontera using SSH:

ssh username@frontera.tacc.utexas.edu
(username@frontera.tacc.utexas.edu) Password: 
(username@frontera.tacc.utexas.edu) TACC Token Code:

# ------------------------------------------------------------------------------
# Welcome to the Frontera Supercomputer
# Texas Advanced Computing Center, The University of Texas at Austin
# ------------------------------------------------------------------------------

2. Getting the Tutorial Materials

Navigate to your scratch directory and clone this tutorial repository:

cds # shortcut for cd #SCRATCH
git clone https://github.com/kbeavers/tacc-deep-learning-tutorials.git

3. Environment Setup

a. Start an Interactive Session

cds
idev -m 20

b. Set up the Container Environment

# Load the Apptainer module
module load tacc-apptainer

# Pull the Docker container image created for this tutorial
apptainer pull docker://kbeavers/tf-213:frontera

# Run the kernel setup script
cd tacc-deep-learning-tutorials
bash ./scripts/install_kernel.sh

4. Dataset Preparation

Extract the provided coral species image dataset

bash ./scripts/download_dataset.sh

5. Launching the Tutorial

a. Copy the tutorial notebooks to your home directory

cp ./tutorials/Mushroom-ANN-tutorial.ipynb $HOME/
cp ./tutorials/Coral-CNN-tutorial.ipynb $HOME/

These notebooks are provided as blank templates for you to fill in as you work through the exercises. To complete this tutorial:

1. Follow the step-by-step instructions on our ReadTheDocs.
2. Write the code from the ReadTheDocs page into the corresponding empty cells in your notebook.
3. Execute each cell to build your ANN/CNN and see the results.

If you get stuck, a completed solution is available within the tutorials directory of this repository.

b. Access the TACC Analysis Portal and configure your session as follows:

• System: Frontera
• Application: Jupyter Notebook
• Project:
• Queue: rtx
• Job Name: DL-Training
• Time Limit: 2:0:0
• Reservation: (or leave blank if no reservation)

c. Final Steps:

• Click 'Submit' and wait for the job to start
• Click 'Connect' when the a node becomes available
• Open Mushroom-ANN-tutorial.ipynb or Coral-CNN-tutorial.ipynb in your $HOME directory
• Change your kernel to Day3-tf-213
• Trust the kernel

Note: The kernel may take a few moments to initialize on first use.