# Quick Start User Guide

## Overview

The Simple Linux Utility for Resource Management (SLURM) is an open source, fault-tolerant, and highly scalable cluster management and job scheduling system for large and small Linux clusters. SLURM requires no kernel modifications for its operation and is relatively self-contained. As a cluster resource manager, SLURM has three key functions. First, it allocates exclusive and/or non-exclusive access to resources (compute nodes) to users for some duration of time so they can perform work. Second, it provides a framework for starting, executing, and monitoring work (normally a parallel job) on the set of allocated nodes. Finally, it arbitrates conflicting requests for resources by managing a queue of pending work.

## Architecture

As depicted in Figure 1, SLURM consists of a slurmd daemon running on each compute node, a central slurmctld daemon running on a management node (with optional fail-over twin), and six utility programs: srun, scancel, sinfo, srun, smap, squeue, and scontrol. All of the commands can run anywhere in the cluster.

Figure 1. SLURM components

The entities managed by these SLURM daemons, shown in Figure 2, include nodes, the compute resource in SLURM, partitions, which group nodes into logical sets, jobs, or allocations of resources assigned to a user for a specified amount of time, and job steps, which are sets of (possibly parallel) tasks within a job. The partitions can be considered job queues, each of which has an assortment of constraints such as job size limit, job time limit, users permitted to use it, etc. Priority-ordered jobs are allocated nodes within a partition until the resources (nodes, processors, memory, etc.) within that partition are exhausted. Once a job is assigned a set of nodes, the user is able to initiate parallel work in the form of job steps in any configuration within the allocation. For instance, a single job step may be started that utilizes all nodes allocated to the job, or several job steps may independently use a portion of the allocation.

Figure 2. SLURM entities

## Commands

Man pages exist for all SLURM daemons, commands, and API functions. The command option --help also provides a brief summary of options. Note that the command options are all case insensitive.

srun is used to submit a job for execution, allocate resources, attach to an existing allocation, or initiate job steps. Jobs can be submitted for immediate or later execution (e.g., batch). srun has a wide variety of options to specify resource requirements, including: minimum and maximum node count, processor count, specific nodes to use or not use, and specific node characteristics (so much memory, disk space, certain required features, etc.). Besides securing a resource allocation, srun is used to initiate job steps. These job steps can execute sequentially or in parallel on independent or shared nodes within the job's node allocation.

scancel is used to cancel a pending or running job or job step. It can also be used to send an arbitrary signal to all processes associated with a running job or job step.

scontrol is the administrative tool used to view and/or modify SLURM state. Note that many scontrol commands can only be executed as user root.

sinfo reports the state of partitions and nodes managed by SLURM. It has a wide variety of filtering, sorting, and formatting options.

squeue reports the state of jobs or job steps. It has a wide variety of filtering, sorting, and formatting options. By default, it reports the running jobs in priority order and then the pending jobs in priority order.

smap reports state information for jobs, partitions, and nodes managed by SLURM, but graphically displays the information to reflect network topology.

## Examples

Execute /bin/hostname on four nodes (-N4). Include task numbers on the output (-l). The default partition will be used. One task per node will be used by default.

    adev0: srun -N4 -l /bin/hostname
    0: adev9
    1: adev10
    2: adev11
    3: adev12

Execute /bin/hostname in four tasks (-n4). Include task numbers on the output (-l). The default partition will be used. One processor per task will be used by default (note that we don't specify a node count).

    adev0: srun -n4 -l /bin/hostname
    0: adev9
    1: adev9
    2: adev10
    3: adev10

Submit the script my.script for later execution (-b). Explicitly use the nodes adev9 and adev10 (-w "adev[9-10]"; note the use of a node range expression). One processor per task will be used by default. The output will appear in the file my.stdout (-o my.stdout). By default, one task will be initiated per processor on the nodes. Note that my.script contains the command /bin/hostname that executed on the first node in the allocation (where the script runs) plus two job steps initiated using the srun command and executed sequentially.

    adev0: cat my.script
    #!/bin/sh
    /bin/hostname
    srun -l /bin/hostname
    srun -l /bin/pwd

    adev0: srun -w "adev[9-10]" -o my.stdout -b my.script
    srun: jobid 469 submitted

    adev0: cat my.stdout
    adev9
    0: adev9
    1: adev9
    2: adev10
    3: adev10
    0: /home/jette
    1: /home/jette
    2: /home/jette
    3: /home/jette

Submit a job, get its status, and cancel it.

    adev0: srun -b my.sleeper
    srun: jobid 473 submitted

    adev0: squeue
      JobId Partition Name     User     St TimeLimit Prio Nodes
        473 batch     my.sleep jette    R  UNLIMITED 0.99 adev9

    adev0: scancel 473

    adev0: squeue
      JobId Partition Name     User     St TimeLimit Prio Nodes

Get the SLURM partition and node status.

    adev0: sinfo
    PARTITION  NODES STATE     CPUS    MEMORY    TMP_DISK NODES
    --------------------------------------------------------------------------------
    debug          8 IDLE         2      3448       82306 adev[0-7]
    batch          1 DOWN         2      3448       82306 adev8
                   7 IDLE         2 3448-3458       82306 adev[9-15]

## MPI

MPI use depends upon the type of MPI being used. Instructions for using several varieties of MPI with SLURM are provided below.

Quadrics MPI relies upon SLURM to allocate resources for the job and srun to initiate the tasks. One would build the MPI program in the normal manner then initiate it using a command line of this sort:

srun [OPTIONS] <program> [program args]

LAM/MPI relies upon the SLURM srun command to allocate resources using either the --allocate or the --batch option. In either case, specify the maximum number of tasks required for the job. Then execute the lamboot command to start lamd daemons. lamboot utilizes SLURM's srun command to launch these daemons. Do not directly execute the srun command to launch LAM/MPI tasks. For example:

    $ srun -n16 -A     # allocates resources and spawns shell for job
    $ lamboot
    $ mpirun -np 16 foo args
    1234 foo running on adev0 (o)
    2345 foo running on adev1
    etc.
    $ lamclean
    $ lamhalt
    $ exit             # exits shell spawned by initial srun command

HP-MPI uses the mpirun command with the -srun option to launch jobs. For example:

    $MPI_ROOT/bin/mpirun -TCP -srun -N8 ./a.out

MPICH2 jobs are launched using the srun command. Just link your program with SLURM's implementation of the PMI library so that tasks can communication host and port information at startup. For example:

    $ mpicc -lXlinker "-lpmi" ...
    $ srun -n20 a.out

NOTES:

- Some MPICH2 functions are not currently supported by the PMI libary integrated with SLURM
- Set the environment variable PMI_DEBUG to a numeric value of 1 or higher for the PMI libary to print debugging information

BlueGene MPI relies upon SLURM to create the resource allocation and then uses the native mpirun command to launch tasks. Build a job script containing one or more invocations of the mpirun command. Then submit the script to SLURM using srun command with the --batch option. For example:

    srun -N2 --batch my.script

Note that the node count specified with the -N option indicates the base partition count. See BlueGene User and Administrator Guide for more information.

Last modified 6 December 2005