View source for Workflow Migration from Laptop to HPC

Moving your work from a laptop or workstation to Anunna is mostly a change of mindset: instead of running things interactively and waiting at your screen, you describe what you want, hand it to the scheduler, and let it run. This page is a high-level guide to making that transition.

== What changes ==

* '''You do not run work interactively.''' On your laptop you run a script and watch it. On the cluster you submit it as a job and the scheduler runs it when resources are free — see [[Batch Jobs]]. The [[Login Nodes|login nodes]] are only for editing, transferring data, and submitting jobs.
* '''You ask for resources explicitly.''' CPUs, memory, time, and GPUs are all requested up front — see [[Scheduler Overview (Slurm)]].
* '''Storage is tiered.''' Active data goes on the fast [[Compute Storage|Lustre]] filesystem, not your home directory, and you need to know what is backed up — see [[Storage Systems Overview]] and [[Backup Policy]].
* '''Software comes from modules.''' Instead of installing everything yourself, you load it with [[Environment Modules|modules]], or install into your own environment — see [[Installing Personal Software]].

== A typical first migration ==

# Get an account and log in — see [[Who Can Access?]] and [[SSH Access]].
# Move your data and code across — see [[Data Transfer Methods]].
# Find your software as modules, or set up your own environment — see [[Software Overview]].
# Test on something small in an [[Interactive Jobs|interactive job]] to check it runs on the cluster.
# Wrap the working commands in a batch script and submit it — see [[Batch Jobs]].
# Scale up: many inputs at once with [[Array Jobs|job arrays]], or more cores and nodes with [[Performance Optimization/Multiple CPUs|threads]] and [[Performance Optimization/Multiple nodes (MPI)|MPI]].
# For multi-step analyses, consider a [[Workflow Engines (Snakemake, Nextflow)|workflow engine]].

== Tips ==

* Start small. Get one step working as a job before scaling to your whole dataset.
* Request only the resources you need — over-requesting just means longer waits in the queue.
* Keep your work reproducible from the start — see [[Reproducibility Guidelines]].

== See also ==
* [[Batch Jobs]]
* [[Software Overview]]
* [[Storage Systems Overview]]
* [[Reproducibility Guidelines]]