Learning Materials
Tutorials, workshop materials, and example repositories for learning how to run your research computing work at scale. Filter by topic using the tags (a guide must have every selected tag), or search for a keyword.
Showing 8 of 8 guides
AlphaFold3 (AF3) predicts atomic-resolution biomolecular structures for proteins, nucleic acids, and complexes.
A step-by-step example of transitioning from running R calculations on your computer using RStudio, to running many such calculations on a HTC system.
This tutorial covers the basics of how to use containers to deploy software. While this example is bioinformatics-flavored, the concepts can be applied to any software stack.
A genome assembly workflow for Oxford Nanopore long reads using hifiasm on CHTC’s High Throughput Computing infrastructure.
Learn how to use the computing power of CHTC with the data you keep in ResearchDrive.
Learn how to run PyTorch training and inference workflows with this cat-dog image classifier. Contains example container recipes that you can use as a starting point for your own ML workflows.
How to run a set of jobs using different input files, with bioinformatics as the example domain. This process can be applied to any other workflow that processes individual data files.
HTCondor’s Directed Acyclic Graph Manager (DAGMan) utility enables you to automate the submission of your HTCondor jobs. This tutorial guides you through how to use DAGMan to submit two HTCondor jobs.
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