submit a job to queue (see standard options below)
srun
Within a running job script/environment: Run code using the allocated resources (see options below)
srun
On frontend: submit to queue, wait until done, show output. (see options below)
sinteractive
Submit job, wait, provide shell on node for interactive playing (X forwarding works, default partition interactive). Exit shell when done. (see options below)
srun--ptybash
(advanced) Another way to run interactive jobs, no X forwarding but simpler. Exit shell when done.
scancel<jobid>
Cancel a job in queue
salloc
(advanced) Allocate resources from frontend node. Use srun to run using those resources, exit to close shell when done. Read the description! (see options below)
scontrol
View/modify job and slurm configuration
Command
Option
Description
sbatch/srun/etc
-t, --time=hh:mm:ss
time limit
-t,--time=dd-hh
time limit, days-hours
-p,--partition=partition
job partition. Usually leave off and things are auto-detected.
--mem-per-cpu=n
request n MB of memory per core
--mem=n
request n MB memory per node
-c, --cpus-per-task=n
Allocate *n* CPU’s for each task. For multithreaded jobs. (compare ``–ntasks``: ``-c`` means the number of cores for each process started.)
-N, --nodes=n-m
allocate minimum of n, maximum of m nodes.
-n, --ntasks=n
allocate resources for and start n tasks (one task=one process started, it is up to you to make them communicate. However the main script runs only on first node, the sub-processes run with “srun” are run this many times.)
-J, --job-name=name
short job name
-ooutput
print output into file output
-eerror
print errors into file error
--exclusive
allocate exclusive access to nodes. For large parallel jobs.
--constraint=feature
request feature (see slurmfeatures for the current list of configured features, or Arch under the hardware list). Multiple with --constraint="hsw|skl".
--array=0-5,7,10-15
Run job multiple times, use variable $SLURM_ARRAY_TASK_ID to adjust parameters.
--gres=gpu
request a GPU, or --gres=gpu:n for multiple
--gres=spindle
request nodes that have disks, spindle:n, for a certain number of RAID0 disks
--mail-type=type
notify of events: BEGIN, END, FAIL, ALL, REQUEUE (not on triton) or ALL. MUST BE used with --mail-user= only
--mail-user=your@email
whome to send the email
srun
-N<N_nodes> hostname
Print allocated nodes (from within script)
Command
Description
slurmq ; slurmqq
Status of your queued jobs (long/short)
slurmpartitions
Overview of partitions (A/I/O/T=active,idle,other,total)
slurmcpus<partition>
list free CPUs in a partition
slurmhistory[1day,2hour,…]
Show status of recent jobs
seff<jobid>
Show percent of mem/CPU used in job
slurmj<jobid>
Job details (only while running)
slurms ; slurmss<partition>
Show status of all jobs
sacct
Full history information (advanced, needs args)
Full slurm command help:
$ slurm
Show or watch job queue:
slurm [watch] queue show own jobs
slurm [watch] q show user's jobs
slurm [watch] quick show quick overview of own jobs
slurm [watch] shorter sort and compact entire queue by job size
slurm [watch] short sort and compact entire queue by priority
slurm [watch] full show everything
slurm [w] [q|qq|ss|s|f] shorthands for above!
slurm qos show job service classes
slurm top [queue|all] show summary of active users
Show detailed information about jobs:
slurm prio [all|short] show priority components
slurm j|job show everything else
slurm steps show memory usage of running srun job steps
Show usage and fair-share values from accounting database:
slurm h|history show jobs finished since, e.g. "1day" (default)
slurm shares
Show nodes and resources in the cluster:
slurm p|partitions all partitions
slurm n|nodes all cluster nodes
slurm c|cpus total cpu cores in use
slurm cpus cores available to partition, allocated and free
slurm cpus jobs cores/memory reserved by running jobs
slurm cpus queue cores/memory required by pending jobs
slurm features List features and GRES
Examples:
slurm q
slurm watch shorter
slurm cpus batch
slurm history 3hours
Other advanced commands (many require lots of parameters to be
useful):