The Slurm Cookbook

Posted on 10 June 2018 in tutorials

The Slurm Cookbook is meant to provide you with a brief overview of Slurm and a few examples of how you can interact with it and obtain information about jobs and resources.

Of course, all of the information presented here can be found by in the Slurm documentation, but if you are just getting started with Slurm it may not be obvious where to look for things.

Note: The Cookbook does not really cover batch scripts, because there are many other guides online which provide plenty of examples.

A three course meal

First of all, what does Slurm actually do? Slurm is a cluster management and job scheduling system for Linux clusters (an ensemble of connected computers running Linux). As such, Slurm is mainly concerned with three things:

  1. Allocating resources to users so that they can perform work (by resources, we mean the computers (or nodes) which form the cluster).

  2. Managing a queue of pending jobs. As long as there are free resources on the cluster, Slurm can simply give users the resources they need. But at some point, the requests of the various users may be incompatible. It is Slurm's job to decide what to execute when, and trying to do that in a smart way so as to use the resources efficiently.

  3. Handling the launch, executing, and monitoring of jobs submitted by users.

The main ingredients

Let's first get an overview of the main user commands that Slurm provides, before looking at some examples of how we can use them.

  • squeue allows you to view information about jobs. In particular, you will see which jobs are pending, which are running, which are completing, and which are completed. These are the states that a job will encounter throughout its lifetime assuming everything goes according to plan (but a job may also fail or be cancelled for several reasons).
  • salloc provides a Slurm job allocation, i.e. a set of resources. It then runs a command specified by the user, and when command is complete, frees up the job allocation.
  • sbatch: submit batch script to run jobs non-interactively on the compute nodes.
  • srun Runs parallel jobs on allocated resources (but can also request resources directly).
  • sacct displays accounting data (i.e. data on past jobs which are not on the queue anymore).
  • sancel can be used to cancel jobs on the queue, or more generally to send them signals.
  • sinfo gives you information about the nodes and partitions which compose the cluster, such as the number of nodes and their state.
  • scontrol allows you to view and modify Slurm configurations (but it's mostly for system administrators).

A handy summary of these commands together with some options can also be found here.

A note on sbatch, salloc, and srun

It may be confusing at first to distinguish between these three commands. In practice, you can think of it as follows: what salloc and sbatch do is allocate resources for jobs (i.e. they tell the system: "I need these many CPUs with this much memory "), whereas srun uses those resources to launch parallel jobs. The difference between sbatch and salloc is that sbatch is used to submit batch scripts which run non-interactively on the compute nodes, whereas salloc can get you the resources and allow you to run interactive commands on the nodes.

srun is generally launched within a job allocation, meaning that either salloc or sbatch have allocated the resources, and srun inherits these resources and the relevant options (which you could also overwrite). But srun can also fight for itself: if is called outside a job allocation, it can claim the necessary resources directly.

Some good recipes

This part contains a few examples of how you can use some of the main user command.

Inspecting the queue with squeue

Let's start simple: let's look at the current queue using squeue. Sometimes there may be a lot of jobs on the queue belonging to other users, which can make it difficult to check on your own jobs. You can filter the jobs that squeue displays by passing the --user parameter.

squeue --user=

Generally squeue cuts the name of the job to a few characters, which can be annoying. It would be nicer to have it display the full job name. The --format parameter comes to the rescue

squeue --format="%.8i %.9P %18j %10u %.8T %.12M %9N"

By default Slurm only allocates 8 characters to the job name, so in the example above, for the field j which corresponds to job name, we can change %.8j to %18j to make sure the full name gets displayed. Removing the dot aligns the text to the left. In the documentation for squeue you can find all the fields which you can pass to --format and format them to your liking.

Of course, we don't want to have to type this every time. What we can do instead is creating an alias. Let's copy the following into the .bashrc file (which is in your home directory):

alias squeue='squeue --format="%.8i %.9P %18j %10u %.8T %.12M %9N"'

Now, we can have our nicely formatted output by simply typing squeue.

NOTE: The .bashrc script is executed every time you start an interactive shell on the cluster (i.e. when you log in), and it can be used to initialize a bunch of useful stuff. Changes you make it will not have any effect unless you log out and log back in or directly source it by running source ~/.bashrc.

Note that squeue also supports a --Format parameter. Generally, --Format is more readable (for job name you would pass name instead of j) and has more fields (in --format, since it only uses single letters, at some point the letters run out), but --format is more flexible for formatting the output (you can't specify the number of characters using --Format as far as I know).

Here is an example using --Format:

squeue --user=<myusername> --Format=jobid,username,account,statecompact,starttime,timelimit,numcpus

Viewing system properties and state with sinfo

Let's not forget to take a careful look at our cluster, as this may influence how we decide to design or run our applications. By simply running sinfo, we can take a look at the partitions: their availability, their state, how many nodes they have, etc.

We can also take a look at the individual nodes, using the -N option. To include some more information in the output (for example the memory of each node) we can pass the -l flag (compactly, sinfo -Nl).

A very useful additional field is the number of cores on each node, by using --format and the C field.

sinfo -N --format "%.10n %.9P %.15C %.10m %.10O %.8t"

On the cluster of the lab, the output looks as follows:

  csn-cpu1      cpu\*        4/8/0/12      31996      10.44      mix
  csn-cpu2      cpu\*       2/10/0/12      31996       2.02      mix
  csn-cpu3      cpu\*       0/12/0/12      31996       0.01     idle
  csn-cpu4      cpu\*       1/11/0/12      31996       1.01      mix
  csn-cpu5      cpu\*       0/12/0/12      31996       0.01     idle
  csn-cpu6      cpu\*       0/40/0/40     128736       0.01     idle
  csn-cpu7      cpu\*       0/40/0/40     128735       0.01     idle
  csn-cpu8      cpu\*       0/40/0/40     128736       0.01     idle
  csn-cpu9      cpu\*      12/28/0/40     128736       8.50      mix
  csn-gpu1       gpu       4/36/0/40     257675       0.19      mix

Here, memory is expressed in megabytes. Note that CPUS on each node are presented in the A/I/O/T format, which stands for allocated/idle/other (offline/down)/total. You can see that the state is idle when no cpu cores are allocated, and mix when some but not all the cores are being used. The CPU_LOAD on the other hand is an indication of how much work we are giving to our nodes.

We can obtain a similar result with the --Format parameter

sinfo -N --Format=nodehost,cpusstate,cpusload,memory,statecompact

Lastly, I may want to view information only of the nodes that I am currently using. We can achieve this by first using squeue to find out where my jobs are running, create a variable called mynodes by parsing the output of squeue, and then use it in the call to sinfo:

mynodes=$(squeue --user=pmarche1 -o "%N" | grep csn | tr "\\n" ",")
sinfo -N --nodes "$mynodes"  --Format=nodehost,cpusstate,cpusload,memory,statecompact

Reviewing past jobs with sacct

If we want to find out information about jobs which are not on the queue anymore (so they don't show up with squeue) we can resort to sacct.

For instance, we may be interested in finding out on which compute nodes our jobs ended up. We can specify a list of job IDs, as well as a list of fields for the --format option.

sacct --jobs=7058,7057 --format=User,JobID,account,AllocNodes,NodeList,Timelimit,elapsed,ReqMem,MaxRss,ExitCode

Here, the NodeList field will tell us on which nodes our jobs landed. --format supports many more fields, which you can list by sacct --helpformat.

Note that sacct by default (and if you do not specify the job IDs with --jobs) only shows you jobs from the current day (since midnight). To show older jobs, you can pass the --starttime option:

sacct --starttime=<mm.dd.yy>

sacct may also not display the full job name by default. To make sure that we see the full name, we can format it by adding % and a number of characters after each field, for instance

sacct --user pmarche1 --format=User,JobID,JobName%20,AllocNodes,NodeList

This allocates 20 characters to the field JobName. Again, you can use aliases to avoid having to remember the full command.

Running interactive jobs

In some occasions we may want to run interactive jobs on one or more nodes. To do so, you can call salloc and then start an interactive session using srun.

salloc --partition <partition> srun -N1 --pty /bin/bash

In the example, we specify the partition we want to work on and the number of nodes (but we could specify other requirements for the allocation). Importantly, we have to pass the --pty option which tells Slurm to drop us in a ssh session on the node we receive. Lastly, we need to give srun the actual command to run: since we want an interactive session, we want to run some kind of shell, for instance /bin/bash.

Earlier on, I mentioned that srun can also be called without the help of sbatch or salloc, in which case it will go and fetch resources directly. As an example, we can in fact do:

srun --partition cpu --pty /bin/bash

Killing jobs with scancel

Lastly, let's kill some jobs. The most basic way is to pass a job ID to scancel, for instance scancel 3425. But suppose you have many jobs on the queue which need to be cancelled: copy-pasting each job ID can take forever. Luckily, there are many ways in which you can constrain the scancel operation. For instance, you can kill all your jobs with

scancel --user=<myusername> 

Or only jobs with a certain name

scancel --jobname=<myjobID>

You can cancel only job which are in a particular state (state can be PENDING, RUNNING, SUSPENDED).

scancel --state=<state>

And of course combine all these options however you want.