From 23cff5f299642a62b05499e25a2c0a5194bca5ad Mon Sep 17 00:00:00 2001
From: Ravi Tripathi <ravi89@uab.edu>
Date: Tue, 30 Apr 2019 11:23:13 -0500
Subject: [PATCH] Adding initial notebook to run singularity container
---
singularity_container.ipynb | 79 +++++++++++++++++++++++++++++++++++++
1 file changed, 79 insertions(+)
create mode 100644 singularity_container.ipynb
diff --git a/singularity_container.ipynb b/singularity_container.ipynb
new file mode 100644
index 0000000..e57b4aa
--- /dev/null
+++ b/singularity_container.ipynb
@@ -0,0 +1,79 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# SIngularity Containers"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## What is a container?"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "A container is a standard unit of software that packages up code and all its dependencies so the application runs quickly and reliably from one computing environment to another. A container image is a lightweight, standalone, executable package of software that includes everything needed to run an application: code, runtime, system tools, system libraries and settings.\n",
+ "\n",
+ "Containers use the host system's kernel, and can access its hardware more directly. When you run a process in a container it runs on the host system, directly visible as a process on that system. Unlike a Virtual Machine, container is a virtualization at the software level, whereas VMs are virtualization at hardware level. If you are interested in finding out more differences between VM and a container, go to this [link](https://www.electronicdesign.com/dev-tools/what-s-difference-between-containers-and-virtual-machines)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Why use a container?\n",
+ "\n",
+ "Containers package together a program and all of its dependencies, so that if you have the container you can use it on any Linux system with the container system software installed. It doesn't matter whether the system runs Ubuntu, RedHat or CentOS Linux - if the container system is available then the program runs identically on each, inside its container. This is great for distributing complex software with a lot of dependencies, and ensuring you can reproduce experiments exactly. If you still have the container you know you can reproduce your work. Also since the container runs as a process on the host machine, it can be run very easily in a [SLURM job](https://docs.uabgrid.uab.edu/wiki/Slurm)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Docker vs Singularity?\n",
+ "\n",
+ "[Docker](https://www.docker.com/) is the most popular and widely used container system in the industry. But [Singularity](https://www.sylabs.io/singularity/) was built keeping HPC in mind, i.e a shared environment. Singularity is designed so that you can use it within SLURM jobs and it does not violate security constraints on the cluster. Though, since Docker is very popular and a lot of people were already using the Docker for their softwares, Singularity maintained a compatibility for Docker images. We'll be seeing this compatibility later in the notebook.\n",
+ "\n",
+ "Singularity is already available on Cheaha. To check the available modules for Cheaha, run the cell below:\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "scrolled": true
+ },
+ "outputs": [],
+ "source": [
+ "!module avail Singularity\n"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.7.2"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
--
GitLab