bash - RONIN BLOG

Parallelizing Workloads With Slurm (Brute Force Edition)

One of the reasons researchers turn to clusters and Slurm is to run many independent jobs. Recently, we posted about how to use Slurm job arrays to do this. Here we describe some additional intuitive ways of getting the job(s) done.

slurm

Parallelizing Workloads with Slurm Job Arrays

Do you have a script that needs to be run across many samples? Or maybe you need to parameter test a script with a variety of values? This blog post covers how to achieve this simply and efficiently with Slurm job arrays.

storage

Everything You Never Needed to Know About Drives, File Systems and Storage

When you build a computer, it needs storage. When you build a computer on the cloud, you try to get by with the smallest disk drives (or volumes) you can to fit the software and data that you have, so that you can avoid paying for disk space you don't need.

Administrator

Your RONIN Superpower: The sudo Command

Everyone who creates a machine or a cluster in RONIN has a superpower: the ability to become somebody else. Another user on that computer, that is, including the supreme superuser who has permissions to do anything, whose name is "root".

linux

An Introduction to Linux Directories and the PATH Variable

To effectively manage your compute environment in the cloud, you need to understand the Linux directory structure, as well as key environment variables such as the PATH variable. This blog post is here to teach you the basics.

linux

10 Simple Linux Commands Every Researcher Should Know

Being able to work with and manipulate files directly via the command line is one of the most useful skills to develop when working in the cloud. This blog post will introduce you to 10 common Linux commands that are crucial for your analysis artillery.

parallel

Parallelising Jobs with GNU Parallel

In the cloud, you can easily scale the size of your computing resources to fit your needs, meaning you have the ability to run many commands or scripts in parallel. This is where GNU parallel comes in handy!

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