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 hands-on workshop provides an overview of neural networks with a focus on GPUs. Example codes will be provided in both Tensorflow and Pytorch and how to use them on Rivanna.

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.

This tutorial introduces the basics of GPU computing and demonstrates how to run AlphaFold on the HPC cluster to predict protein structures.

Accelerate your data science pipeline with RAPIDS on NVIDIA GPUs

This tutorial is an introduction to utilizing GPU computing resources on UVA's HPC systems.

Learn how to benchmark your program for parallel SLURM jobs.

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