-[Interactive access to the nodes](#interactive-access-to-the-nodes)
-[Basic slurm script with an MPI application](#basic-slurm-script-with-an-mpi-application)
-[Other use-cases for slurm:](#other-use-cases-for-slurm)
-[Run a program in the background](#run-a-program-in-the-background)
-[Nohup](#nohup)
-[Screen (recommended)](#screen-recommended)
-[Troobleshooting](#troobleshooting)
-[My code runs slower on a computing server than on my laptop. Whay is the problem ?](#my-code-runs-slower-on-a-computing-server-than-on-my-laptop-whay-is-the-problem)
-[CMake](#cmake)
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# Irma atlas cluster
## Description
### Node configuration
The configuration has a frontal node, named irma-atlas, and 4 compute nodes.
Frontal node: irma-atlas:
* 64 cores on 4 sockets (AMD Opteron 6386 SE 2.8 Ghz),
* 512 GB of RAM,
* 2.4 TB of storage on SSD, (directory: /ssd)
* 70 TB for data storage (10'000 rpm HDD), (directory: /data)
* NFS mount to access laboratory data, (such as /home)
* NFS mount to access frontal node data: /ssd and /data
* NFS mount to access laboratory data, (such as /home)
Since the 25th of novembre 2015, one of the node has been equipped with 2 NVIDIA K80 GPGPU cards.
Everything is interconnected with both 10Gb Ethernet cards and 40Gb Infiniband cards.
The workload manager is [slurm](https://computing.llnl.gov/linux/slurm/).
### Storage
On the frontal node irma-atlas, you have access to several storage:
* Your home directory: /home/<username>. This directory is meant only to store important files and have to be kept to a minimal size.
* The /data/<username> directory. If this directory does not exist, you must create one, so you don't mix your files with other users. This partition has a size of 50 TB, so you can store big data, like simulation results, compilation-related files and libraries ...
* The /ssd/<username> directory. If this directory does not exist, you must create one, so you don't mix your files with other users. This partition has a size of 2 TB and is put on SSDs for increased access speed. You can use it to store medium-sized data.
