Tips and Tricks on O2
| Audience | Computational skills required | Duration |
|---|---|---|
| Biologists | Beginner bash | 2-3 hour workshop (~2-3 hours of trainer-led time) |
Description
This repository has teaching materials for a 3 hour, hands-on Intermediate bash workshop led at a relaxed pace. Many tools for the analysis of big data require the use of a high performance compute cluster and a knowledge of the command line. In this workshop we invite users of the HMS Research Computing Cluster O2 and members of the Harvard community who are interested in using a compute cluster to join us as we demonstrate some very helpful tips and best practices. We will introduce participants to various commands and approaches to help effectively navigate use the cluster and complete tasks in an efficient manner.
This workshop is being held in collaboration with HMS Research Computing, and is an advanced workshop requiring knowledge of the command-line and/or the basic shell skills learned in The Foundation - Basic Shell.
Learning Objectives
In this workshop, we will:
- Establish a
scratchspace on the O2 computing cluster and check our storage quotas - Modify our
.bashrcprofile with commonly used aliases - Download external data to O2 from a website
- Locally download and upload data to and from O2
- Manage job submissions to O2
These materials are developed for a trainer-led workshop, but are also amenable to self-guided learning.
Contents
| Lessons | Estimated Duration | Instructor |
|---|---|---|
| Introduction | 10 min | Meeta |
| Setting up, .bashrc and checking quotas | 45 min | Will |
| Data utilies with O2 | 45 min | Meeta |
| Job Management on O2 | 45 min | Will |
| Wrap-up | 5 min | Meeta |
Installation Requirements
Windows users: GitBash
These materials have been developed by members of the teaching team at the Harvard Chan Bioinformatics Core (HBC). These are open access materials distributed under the terms of the Creative Commons Attribution license (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
- Some materials used in these lessons were derived from work that is Copyright © Data Carpentry (http://datacarpentry.org/). All Data Carpentry instructional material is made available under the Creative Commons Attribution license (CC BY 4.0).