This tutorial provides an introduction to deep learning using high performance computing. This workshop will cover accessing deep learning containers, resource allocation and helpful tools, how to choose a GPU, and deep learning slurm scripts.

This tutorial provides a practical introduction to building artificial neural networks using PyTorch, a powerful and flexible deep learning framework. The course covers the fundamentals of PyTorch, including tensors, automatic differentiation, and model building.

This tutorial is an introduction to multi-GPU strategies for large language model (LLM) inference using tools like Accelerate, DeepSpeed, and vLLM.

An introduction to parallel programming using shared memory, including some GPU.