hpc

This tutorial is an introduction to using the Rivanna high-performance computing (HPC) system.

This tutorial is an introduction to using several popular bioinformatics tools on Rivanna.

The industry standard of restricting containers to just the application and its dependencies often results in better security and smaller size. See how the use of multi-stage builds and scratch/distroless base images can reduce the image size by as much as 99% in real applications. This is a continuation of the Building Containers for Rivanna workshop.

Learn how to write Dockerfiles, build Docker images, run them on Rivanna using Singularity, and even create your own Jupyter kernel on our JupyterLab.

Accelerate your data science pipeline with RAPIDS on NVIDIA GPUs

The basics of parallel programming with MPI.

An introduction to creating, and utilizing Singularity containers on an HPC system.

In this hands-on workshop, you will be introduced to the Julia programming language and its use on the Rivanna HPC cluster.

This workshop introduces applied optimization in the MATLAB environment, focusing on using the Optimization Toolbox™ and the Global Optimization Toolbox™.

In this hands-on workshop, you will be introduced to parallel and distributed computing in MATLAB™ for speeding up your application and offloading work.