This lesson is being piloted (Beta version)
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Setup
Episodes
Introduction to SMU SuperPOD
Working with Conda Environment
Using NGC Container in SuperPOD
Using Jupyter Lab in SuperPOD
Using Batch script in SuperPOD
Job queueing and control in SuperPOD
Data Science workflow with GPUs using RAPIDS
Sample Application of NEMO for Sentiment Analysis
Sample Applications of MultiGPUs for Computer Vision using Horovod
Using YOLOv5 for object detection
Using Transfer Learning with ResNet50
Using Stable Diffusion with SuperPOD
Using Pre-trained model from HuggingFace
All in one page (Beta)
Extras
Reference
About
Discussion
Figures
Instructor Notes
License
SMU SuperPOD 101
: You need to have a SuperPOD account created and also MobaXTerm on Windows OS or Terminal on Macs OS