Description
Nextflow is widely adopted across the life sciences because it can run across various research computing platforms including local machines, high performance computing (HPC) and cloud platforms. Teaching researchers how to configure and run workflows effectively on HPC remains a challenge due to differences in schedulers, storage systems, container runtimes, and institutional policies. As such, training materials often become site-specific and difficult to use.
This project will develop a reusable Nextflow for HPC Training resources bundle that builds on existing workshop materials. The bundle will support delivery across multiple HPC environments and institutional contexts. Materials will include instructor guides, learner exercises, infrastructure configuration examples, and troubleshooting scenarios.
Goals
- Refactor and modularise existing Nextflow for HPC workshop materials into reusable components
- Develop infrastructure-agnostic training content that can be adapted to different schedulers
- Create templated configuration examples demonstrating best practices for running Nextflow pipelines on HPC
- Develop hands-on exercises covering resource tuning, profiling, debugging, and scaling workflows
- Produce instructor notes and delivery guides to enable others to run the workshop independently
- Improve documentation structure for long-term maintenance and community contributions
