Setting up the ATLAS Environment

Overview

Teaching: 30 min
Exercises: 30 min

Questions

• What is a “release”?

• How can I configure my laptop to use “ATLAS code”?

Objectives

• Setup your working environment with Docker

• Load the ATLAS release through an image

Setting up “ATLAS”

Your collaborators in ATLAS produce a lot of amazing and powerful code that allows you to perform complex tasks and carry out amazing analyses. This code is generally referred to as “athena”. You can browse this code by clicking on the previous link. However, to be able to use this code you have to “get access” to it. This is done by building a basic version of athena and producing a bunch of libraries and header files which are subsequently bundled into what is referred to as a release.

You will learn much more about the structure of this release when we learn about CMake on the second day of the workshop. However, for now, you can view this “release” as a pre-requisite to be able to write code to analyze ATLAS data (and Monte Carlo simulation!).

There are a few ways to get access to this pre-compiled codebase. For the majority of this workshop we will be using Docker to do this and working in an AnalysisBase release container. You will learn more about the details of Docker later in the week of the workshop and what is presented here is only the minimal setup which will allow you to work through the tutorial.

Installing Docker

General information about Docker and details of installation can be found here: Docker Installation Depending on the operating system you are using on the local machine, links to specific instructions on the Docker website can be found below.

If something doesn’t work

Docker is a standard industry tool. The directions above should “just work”. That said, if you spend one hour working by yourself and still find that you are having issues with the basic setup, ASK SOMEONE!!! We have created a Discord server (Link to Discord) where you can dynamically ask tutors and other participants questions. This pertains to setting up Docker as well as every other portion of the bootcamp.

And more broadly, this is a very good general rule of thumb to get into. If you are struggling with something, particularly if it is technical, don’t needlessly waste your time thinking that “this is a stupid question, so I’m not allowed to ask”. There will be something to help you and that is what collaboration is all about anyways. So do one of the following :

• Ask the person sitting next to you
• Ask that helpful person on your analysis team or working group
• Ask a Skype channel, Mattermost or Discord chat
• Ask a mailing list

When you are done, just be sure to say “thank you”. #teamworkmakesthedreamwork

Download an ATLAS AnalysisBase Release

Start by downloading the Docker image for the release you want using the docker pull. The Docker images get managed by Docker behind the scenes (Again, more details in the Docker session), so you don’t have to worry about that yourself:

docker pull atlas/analysisbase:21.2.125

The image should be around 4GB in size, so make sure you have the space available on your hard drive.

Latest Release

These instructions will use a numbered release, which should be your default to work with.

If you want to use the absolutely latest, bleeding edge version you can replace atlas/analysisbase:21.2.125 with atlas/analysisbase or atlas/analysisbase/latest. However, doing so is not recommended for this bootcamp. Though some times it can be fun to live on the edge, so go ahead, try to pull the very latest ATLAS AnalysisBase image.

Starting the Release

Let’s now test to see whether this worked. Now that you have pulled the release image, you can use it to setup the ATLAS environment release. This is done using the docker run command.

docker run --rm -it atlas/analysisbase:21.2.125 bash

This will change the look of command prompt and you should now see something similar to [bash][atlas]:workdir > or [bash][atlas]:~ > as your prompt depending on where you are within the container. If you list the files in the top directory of the container, you should see one file called release_setup.sh. Sourcing this file will load the release that is contained within the image. Try

source /release_setup.sh

If this worked properly and you have setup docker correctly, then you should see the following

[bash][atlas]:~ > source /release_setup.sh 
Configured GCC from: /opt/lcg/gcc/8.3.0-cebb0/x86_64-centos7/bin/gcc
Configured AnalysisBase from: /usr/AnalysisBase/21.2.125/InstallArea/x86_64-centos7-gcc8-opt
[bash][atlas AnalysisBase-21.2.125]:~ > 

The CVMFS Way

One other common way to setup the analysis release is to use the CernVM File System which is available on nearly all clusters within the collaboration. In this case, you use the setupATLAS alias command to initialize the asetup (“athena(a) setup”) command which is subsequently used to create the surrounding ATLAS coding environment by giving you access to the precompiled base release. This would typically look something like

-bash-4.2$ setupATLAS
lsetup               lsetup <tool1> [ <tool2> ...] (see lsetup -h):
 lsetup agis          ATLAS Grid Information System
 lsetup asetup        (or asetup) to setup an Athena release
 lsetup atlantis      Atlantis: event display
...
-bash-4.2$ asetup AnalysisBase,21.2.125,here
Using AnalysisBase/21.2.125 [cmake] with platform x86_64-slc6-gcc62-opt
  at /cvmfs/atlas.cern.ch/repo/sw/software/21.2
Test area: /afs/cern.ch/user/m/meehan/delme
-bash-4.2$

This is achieving precisely the same goal as what we are achieving with Docker in this bootcamp. The primary benefit is that using Docker allows you to comfortably use your laptop for all of your work. So, cluster down? (No Problem!), poor internet connection? (No Problem), … you can now work all the time!

Key Points

• A software release (e.g. AnalysisBase) is necessary to analyze ATLAS data.

• You will learn much more about the details of an ATLAS release on Tuesday!

• Docker will serve as the “portal” for all ATLAS work throughout this tutorial. It can be thought of a “virtual machine”.

• You will learn much more about Docker on Thursday!