Popper is a workflow execution engine based on Github Actions (GHA) that allows you to execute GHA workflows locally on your machine. Popper workflows are defined in HCL syntax and behave like GHA workflows. The main difference with respect to GHA workflows is that, through some extensions to the GHA syntax, a Popper workflow can execute actions in other runtimes in addition to Docker.
- How can we deal with large datasets? For example I have to work on large data of hundreds GB, how would this be integrated into Popper?
- How can Popper capture more complex workflows? For example, automatically restarting failed tasks?
- Can I follow Popper in computational science research, as opposed to computer science?
- How to apply the Popper protocol for applications that take large quantities of computer time?