Resources can be accessed for batched computations through the Slurm queue manager (version 22.05). Plus, a custom Slurm plugin allows users to book scheduled access to resources through an external calendar, the Booked Scheduler. 

The system offers 4 jobs queues:

• epito-compile (Time limit: 1h; Max resources: 2 cores, 1 node);
• epito-1h (Time limit: 1h; Exclusive node access);
• epito-12h (Time limit: 12h; Exclusive node access);
• epito-booked (No time limit; Exclusive node access; reservation through the Booked Scheduler) .

Resource usage is accounted using credits, the Booked Scheduler currency. Initial credits count allow computation for a 5000 core-hours total, but more can be requested following this procedure.

To book resources on the system, first log into the web calendar. You can then select one or more epito nodes from the resource list to create a reservation. From the creation page, you can choose the starting and ending date and time, the resources needed and a mandatory title and description, as showed in the image below.

Once the reservation is correctly created, the system will prompt you with a confirmation message:

Now head to the system and login your user via ssh. You can check the corresponding Slurm reservation has been created with the command “scontrol show res”.

The output should look like the following:

You can now submit your batch script. Remember to specify the correct partition “epito-booked” and to use the reservation you created in the step before, or the job may not have the guaranteed resources or may be terminated after the default time limit. Here is a simple example of a script:

#!/bin/sh
#SBATCH –partition=epito-booked
#SBATCH –reservation=test_computing
#SBATCH –nodes=2
srun sleep 120

Using Slurm directives, the partition name, reservation and minimum number of nodes requested for the job are specified in the corresponding line. With “srun” you can specify the command to run on each node. You can find more information in the sbatch official documentation page.

Once the script is ready, you can submit the job with the “sbatch” command with the file and name as argument, and check its status by using the command “squeue” to list the job queue, showing the job id, partition, running time and the current status:

The script result and/or error logs will be created in your submitting working directory while the job runs in file named slurm-{jobid}.