Go to Great Lakes Overview To search this user guide, use the Command + F (Mac) or Ctrl + F (Win) keyboard shortcuts.
Slurm is a combined batch scheduler and resource manager that allows users to run their jobs on the University of Michigan’s high performance computing (HPC) clusters. This document describes the process for submitting and running jobs under the Slurm Workload Manager on theGreat Lakes cluster.
The Batch Scheduler and Resource Manager
The batch scheduler and resource manager work together to run jobs on an HPC cluster. The batch scheduler, sometimes called a workload manager, is responsible for finding and allocating the resources that fulfill the job’s request at the soonest available time. When a job is scheduled to run, the scheduler instructs the resource manager to launch the application(s) across the job’s allocated resources. This is also known as “running the job”.
The user can specify conditions for scheduling the job. One condition is the completion (successful or unsuccessful) of an earlier submitted job. Other conditions include the availability of a specific license or access to a specific hardware accelerator.
An HPC cluster is made up of a number of compute nodes, each with a complement of processors, memory and GPUs. The user submits jobs that specify the application(s) they want to run along with a description of the computing resources needed to run the application(s).
Users interact with an HPC cluster through login nodes. Login nodes are a place where users can login, edit files, view job results and submit new jobs. Login nodes are a shared resource and should not be used to run application workloads.
Jobs and Job Steps
A job is an allocation of resources assigned to an individual user for a specified amount of time. Job steps are sets of (possibly parallel) tasks within a job. When a job runs, the scheduler selects and allocates resources to the job. The invocation of the application happens within the batch script, or at the command line for interactive and jobs.
When an application is launched using srun, it runs within a “job step”. The srun command causes the simultaneous launching of multiple tasks of a single application. Arguments to srun specify the number of tasks to launch as well as the resources (nodes, CPUs, memory, and GPUs) on which to launch the tasks.
Multiple srun commands can be invoked sequentially, or in parallel by backgrounding them. Furthermore, the resources specified on any srun command can be less than the total resources that were allocated to the job, but the total resources of all concurrently executing srun commands cannot exceed that total.
Thesbatch command is used to submit a batch script to Slurm. It is designed to reject the job at submission time if there are requests or constraints that Slurm cannot fulfill as specified. This gives the user the opportunity to examine the job request and resubmit it with the necessary corrections. To submit a batch script simply run sbatch <scriptName>
$ sbatch myJob.sh
Submitting a Job in One Line
If you wish to submit a job without needing a separate script, you can use sbatch --wrap=<command string>. This will wrap the specified command in a simple “sh” shell script, which is then submitted to the Slurm controller.
Anatomy of a Batch Job
The batch job script is composed of three main components:
- The interpreter used to execute the script
- #SBATCH directives that convey submission options
- The application(s) to execute along with its input arguments and options
An Example Slurm job
#!/bin/bash# The interpreter used to execute the script#“#SBATCH” directives that convey submission options:#SBATCH --job-name=example_job#SBATCH --firstname.lastname@example.org#SBATCH --mail-type=BEGIN,END#SBATCH --cpus-per-task=1#SBATCH --nodes=1#SBATCH --ntasks-per-node=1#SBATCH --mem-per-cpu=1000m #SBATCH --time=10:00#SBATCH --account=test#SBATCH --partition=standard#SBATCH --output=/home/%u/%x-%j.log# The application(s) to execute along with its input arguments and options:/bin/hostnamesleep 60
Common Job Submission Options
|Option||Slurm Command(#SBATCH)||Great Lakes Usage|
Available partitions: standard(default), gpu (GPU jobs only), largemem (large memory jobs only), viz,debug, standard-oc(on-campus software only)
|Wall time limit||--time=<dd-hh:mm:ss>||--time=01-02:00:00|
|Process count per node||--ntasks-per-node=<count>||--ntasks-per-node=1|
|Core count (per process)||--cpus-per-task=<cores>||--cpus-per-task=1|
|Memory limit||--mem=<limit>(Memory per node in MB)||--mem=12000m|
If not set, the scheduler defaults will be applied
|Minimum memory per processor||--mem-per-cpu=<memory>||--mem-per-cpu=1000m|
If not set, the scheduler defaults will be applied
|Process count per GPU||--ntasks-per-gpu=<count>|
Must be used with --ntasks or --gres=gpu:
8 total tasks
|Job array||--array=<array indices>||--array=0-15|
|Standard output file||--output=<file path>(path must exist)||--output=/home/%u/%x-%j.log|
%u = username
%x = job name
%j = job ID
|Standard error file||--error=<file path>(path must exist)||--error=/home/%u/error-%x-%j.log|
|Combine stdout/stderr to stdout||--output=<combined out and err file path>||--output=/home/%u/%x-%j.log|
|Copy environment||--export=ALL (default)|
--export=NONE(to not export environment)
|Copy environment variable||--export=<variable=value,var2=val2>||--export=EDITOR=/bin/vim|
|Request software license(s)|
|Request event notification|
Note: multiple mail-type requests may be specified in a comma separated list:
Note: there are multiple mail-type options one can use:
NONE, BEGIN, END, FAIL, REQUEUE, ALL, INVALID_DEPEND, STAGE_OUT, TIME_LIMIT, TIME_LIMIT_90, TIME_LIMIT_80, TIME_LIMIT_50, ARRAY_TASKS
|Email address||--mail-user=<email address>||--email@example.com|
|Defer job until the specified time||--begin=<date/time>||--begin=2020-12-25T12:30:00|
Please note that if your job is set to utilize more than one node, make sure your code is MPI enabled in order to run across these nodes. You can use any ofsrun,mpirun or mpiexec commands to start your MPI job.
An interactive job is a job that returns a command line prompt (instead of running a script) when the job runs. Interactive jobs are useful when debugging or interacting with an application. Thesalloccommand is used to submit an interactive job to Slurm.When the job starts, a command line prompt will appear on one of the compute nodes assigned to the job. From here commands can be executed using the resources allocated on the local node.
[user@gl-login1 ~]$ salloc --account=testsalloc: Granted job allocation 23764789salloc: Waiting for resource configurationsalloc: Nodes gl3032 are ready for job[user@gl3032 ~ 3]$ hostnamegl3032.arc-ts.umich.edu[user@gl3032 ~]$
Jobs submitted with salloc will be assigned the cluster default values of 1 CPU and 768MB of memory. If the account is not specified, your default account will be used. If additional resources are required, they can be requested as options to the salloc command. The following example job is assigned 2 nodes with 4 CPUS and 4GB of memory each:
[user@gl-login1 ~ 1]$ salloc --account=test --nodes=2 --ntasks-per-node=4 --mem-per-cpu=1GB --cpus-per-task=1salloc: Granted job allocation 23765418salloc: Waiting for resource configurationsalloc: Nodes gl[3041-3042] are ready for job[user@gl3041 ~ 3]$ srun hostnamegl3041.arc-ts.umich.edugl3041.arc-ts.umich.edugl3041.arc-ts.umich.edugl3041.arc-ts.umich.edugl3042.arc-ts.umich.edugl3042.arc-ts.umich.edugl3042.arc-ts.umich.edugl3042.arc-ts.umich.edu
In the above example srun is used within the job from the first compute node to run a command once for every task in the job on the assigned resources. srun can be used to run on a subset of the resources assigned to the job. See the srun man page for more details.
GPU and Large Memory Jobs
Jobs can request GPUs with the job submission options --partition=gpu and a count option from the table below. All counts can be represented by gputype:number or just a number (default type will be used). Available GPU types can be found with the command sinfo -O gres -p <partition>. GPUs can be requested in both Batch and Interactive jobs.
|Description||Slurm directive (#SBATCH or srun option)||Example|
|GPUs per node||--gpus-per-node=<gputype:number>||--gpus-per-node=2 or --gpus-per-node=v100:2|
|GPUs per job||--gpus=<gputype:number>||--gpus=2 or --gpus=v100:2|
|GPUs per socket||--gpus-per-socket=<gputype:number>||--gpus-per-socket=2 or --gpus-per-socket=v100:2|
|GPUs per task||--gpus-per-task=<gputype:number>||--gpus-per-task=2 or --gpus-per-task=v100:2|
|CPUs required per GPU||--cpus-per-gpu=<number>||--cpus-per-gpu=4|
|Memory per GPU||--mem-per-gpu=<number>||--mem-per-gpu=1000m|
Jobs can request nodes with large amounts of RAM with --partition=largemem.
You may want to run a set of jobs sequentially, so that the second job runs only after the first one has completed. This can be accomplished using Slurm’s job dependencies options. For example, if you have two jobs, Job1.sh and Job2.sh, you can utilize job dependencies as in the example below.
[user@gl-login1]$ sbatch Job1.sh123213[user@gl-login1]$ sbatch --dependency=afterany:123213 Job2.sh123214
The flag --dependency=afterany:123213 tells the batch system to start the second job only after completion of the first job. afteranyindicates that Job2 will run regardless of the exit status of Job1, i.e. regardless of whether the batch system thinks Job1 completed successfully or unsuccessfully.
Once job 123213 completes, job 123214 will be released by the batch system and then will run as the appropriate nodes become available.
Exit status: The exit status of a job is the exit status of the last command that was run in the batch script. An exit status of ‘0’ means that the batch system thinks the job completed successfully. It does not necessarily mean that all commands in the batch script completed successfully.
There are several options for the –dependency flag that depend on the status of Job1:
|–dependency=afterany:Job1||Job2 will start after Job1 completes with any exit status|
|–dependency=after:Job1||Job2 will start any time after Job1 starts|
|–dependency=afterok:Job1||Job2 will run only if Job1 completed with an exit status of 0|
|–dependency=afternotok:Job1||Job2 will run only if Job1 completed with a non-zero exit status|
Making several jobs depend on the completion of a single jobis done in the example below:
[user@gl-login1]$ sbatch Job1.sh 13205 [user@gl-login1]$ sbatch --dependency=afterany:13205 Job2.sh 13206 [user@gl-login1]$ sbatch --dependency=afterany:13205 Job3.sh 13207 [user@gl-login1]$ squeue -u $USER -S S,i,M -o "%12i %15j %4t %30E" JOBID NAME ST DEPENDENCY 13205 Job1.bat R 13206 Job2.bat PD afterany:13205 13207 Job3.bat PD afterany:13205
Making a job depend on the completion of several other jobs: example below.
[user@gl-login1]$ sbatch Job1.sh13201[user@gl-login1]$ sbatch Job2.sh13202[user@gl-login1]$ sbatch --dependency=afterany:13201,13202 Job3.sh13203[user@gl-login1]$ squeue -u $USER -S S,i,M -o "%12i %15j %4t %30E"JOBID NAME ST DEPENDENCY 13201 Job1.sh R 13202 Job2.sh R 13203 Job3.sh PD afterany:13201,afterany:13202
Chaining jobs is most easily done by submitting the second dependent job from within the first job. Example batch script:
#!/bin/bashcd /data/mydirrun_some_commandsbatch --dependency=afterany:$SLURM_JOB_ID my_second_job
Job dependencies documentation adapted from https://hpc.nih.gov/docs/userguide.html#depend
Job arrays are multiple jobs to be executed with identical parameters.Job arrays are submitted with-a <indices> or --array=<indices>.The indices specification identifies what array index values should be used.Multiplevaluesmay be specified using a comma separated list and/or a range of values with a “-” separator: --array=0-15 or --array=0,6,16-32.
A step function can also be specified with a suffix containing a colon and number. For example,--array=0-15:4 is equivalent to --array=0,4,8,12.
A maximum number of simultaneously running tasks from the job array may be specified using a “%” separator.For example --array=0-15%4 will limit the number ofsimultaneously running tasks from this job array to 4. The minimum index value is 0.The maximum value is499999.
To receive mail alerts for each individual array task,--mail-type=ARRAY_TASKS should be added to the Slurm job script. Unless this option is specified, mail notifications on job BEGIN, END and FAIL apply to a job array as a whole rather than generating individual email messages for each task in the job array.
For each job type above, the user has the ability to define the execution environment. This includes environment variable definitions as well as shell limits (bashulimitor cshlimit).sbatchand salloc provide the--exportoption to convey specific environment variables to the execution environment.sbatchandsallocprovide the--propagateoption to convey specific shell limits to the execution environment.By default Slurm does not source the files~./bashrcor~/.profilewhen requesting resources viasbatch(although it does when runningsrun/salloc).So, if you have a standard environment that you have set in either of these files or your current shell then you can do one of the following:
- Add the command#SBATCH--get-user-envto your job script(i.e. the module environment is propagated).
- Source the configuration file in your job script:
<#SBATCH statements >source~/.bashrc
Note:You may want to remove the influence of any other current environment variables by adding#SBATCH --export=NONEto the script. This removes all set/exported variables and then acts as if#SBATCH--get-user-envhas been added (module environment is propagated).
Slurm recognizes and provides a number of environment variables.
The first category of environment variables are those that Slurm inserts into the job’s execution environment. These convey to the job script and application information such as job ID (SLURM_JOB_ID) and task ID (SLURM_PROCID).For the complete list, see the “OUTPUT ENVIRONMENT VARIABLES” section under thesbatch,salloc, andsrunman pages.
The next category of environment variables are those use user can set in their environment to convey default options for every job they submit. These include options such as the wall clock limit. For the complete list, see the “INPUT ENVIRONMENT VARIABLES” section under thesbatch,salloc, andsrunman pages.
Finally, Slurm allows the user to customize the behavior and output of some commands using environment variables. For example, one can specify certain fields for thesqueuecommand to display by setting theSQUEUE_FORMATvariable in the environment from which you invokesqueue.
Commonly Used Environment Variables
|Submit directory||$SLURM_SUBMIT_DIR||Slurm jobs starts from the submit directory by default.|
|Node list||$SLURM_JOB_NODELIST||The Slurm variable has a different format to the PBS one.|
To get a list of nodes use:
scontrol show hostnames $SLURM_JOB_NODELIST
|Job array index||$SLURM_ARRAY_TASK_ID|
|Number of nodes allocated||$SLURM_JOB_NUM_NODES|
|Number of processes||$SLURM_NTASKS|
|Number of processes per node||$SLURM_TASKS_PER_NODE|
|Requested tasks per node||$SLURM_NTASKS_PER_NODE|
|Requested CPUs per task||$SLURM_CPUS_PER_TASK|
|Hostname||$HOSTNAME == $SLURM_SUBMIT_HOST||Unless a shell is invoked on an allocated resource, the HOSTNAME variable is propagated (copied) from the submit machine environments will be the same on all allocated nodes.|
Slurm merges the job’s standard error and output by default and saves it to an output file with a name that includes the job ID (slurm-<job_ID>.out for normal jobs and"slurm-<job_ID_index.out for arrays"). You can specify your own output and error files to the sbatch command using the -o/file/to/output and -e/file/to/error options respectively. If both standard out and error should go to the same file, only specify -o /file/to/output Slurm will append the job’s output to the specified file(s). If you want the output to overwrite any existing files, add the --open-mode=truncate option.The files are written as soon as output is created. It does not spool on the compute node and then get copied to the final location after the job ends. If not specified in the job submission, standard output and error are combined and written into a file in the working directory from which the job was submitted.
For example if I submit job 93 from my home directory, the job output and error will be written to my home directory in a file called slurm-93.out. The file appears while the job is still running.
[user@gl-login1 ~]$ sbatch test.shSubmitted batch job 93 [user@gl-login1 ~]$ ll slurm-93.out-rw-r–r– 1 user hpcstaff 122 Jun 7 15:28 slurm-93.out [user@gl-login1 ~]$ squeue JOBID PARTITIONNAME USER STTIME NODES NODELIST(REASON) 93 standard example user R 0:04 1 gl3160
If you submit from a working directory which is not a shared filesystem, your output will only be available locally on the compute node and will need to be copied to another location after the job completes. /home, /scratch, and /nfs are all networked filesystems which are available on the login nodes and all compute nodes.
For example if I submit a job from /tmp on the login node, the output will be in /tmp on the compute node.
[user@gl-login1 tmp]$ pwd/tmp[user@gl-login1 tmp]$ sbatch /home/user/test.shSubmitted batch job 98[user@gl-login1 tmp]$ squeueJOBID PARTITION NAME USER ST TIME NODES NODELIST(REASON)98 standard example user R 0:03 1 gl3160[user@gl-login1 tmp]$ ssh gl3160[user@gl3160 ~]$ ll /tmp/slurm-98.out-rw-r–r– 1 user hpcstaff 78 Jun 7 15:46 /tmp/slurm-98.out
Serial vs. Parallel jobs
Parallel jobs launch applications that are comprised of many processes (aka tasks) that communicate with each other, typically over a high speed switch. Serial jobs launch one or more tasks that work independently on separate problems.
Parallel applications must be launched by the srun command. Serial applications can use srun to launch them, but it is not required in one node allocations.
A cluster is often highly utilized and may not be able to run a job when it is submitted. When this occurs, the job is placed in a partition. Specific compute node resources are defined for every job partition. The Slurmpartitionis synonymous with the termqueue.
Each partition can be configured with a set of limits which specify the requirements for every job that can run in that partition. These limits include job size, wall clock limits, and the users who are allowed to run in that partition.
The Great Lakes cluster has the “standard” (used for most production jobs, 14 day max walltime), “largemem” (used for jobs that require large amounts of RAM, 14 day max), “gpu” (used for GPU-intensive tasks, 14 day max), “debug” (only to verify/debug jobs, 1 day max) and “viz” (used for visualization jobs, 1 day max) partitions.
Commands related to partitions include:
|sinfo||Lists all partitions currently configured|
|scontrol show partition <name>||Provides details about each partition|
|squeue||Lists all jobs currently on the system, one line per job|
Most of a job’s specifications can be seen by invokingscontrol show job <jobID>. More details about the job can be written to a file by usingscontrol write batch_script <jobID> output.txt. If no output file is specified, the script will be written toslurm<jobID>.sh.
Slurm captures and reports the exit code of the job script (sbatchjobs) as well as the signal that caused the job’s termination when a signal caused a job’s termination.
A job’s record remains in Slurm’s memory for 30 minutes after it completes. scontrol show jobwill return “Invalid job id specified” for a job that completed more than 30 minutes ago. At that point, one must invoke thesacctcommand to retrieve the job’s record from the Slurm database.
Modifying a Batch Job
Many of the batch job specifications can be modified after a batch job is submitted and before it runs. Typical fields that can be modified include the job size (number of nodes), partition (queue), and wall clock limit. Job specifications cannot be modified by the user once the job enters theRunningstate.
Beside displaying a job’s specifications, thescontrolcommand is used to modify them. Examples:
|scontrol -dd show job <jobID>||Displays all of a job’s characteristics|
|scontrol write batch_script <jobID>||Retrieve the batch script for a given job|
|scontrol update JobId=<jobID> Account=science||Change the job’s account to the “science” account|
|scontrol update JobId=<jobID> Partition=priority||Changes the job’s partition to the priority partition|
Holding and Releasing a Batch Job
If a user’s job is in the pending state waiting to be scheduled, the user can prevent the job from being scheduled by invoking the scontrol hold <jobID> command to place the job into a Held state. Jobs in the held state do not accrue any job priority based on queue wait time. Once the user is ready for the job to become a candidate for scheduling once again, they can release the job using the scontrol release <jobID> command.
Signalling and Cancelling a Batch Job
Pending jobs can be cancelled (withdrawn from the queue) using the scancel command (scancel <jobID>). The scancel command can also be used to terminate a running job. The default behavior is to issue the job a SIGTERM, wait 30 seconds, and if processes from the job continue to run, issue a SIGKILL command.
The -s option of the scancel command (scancel -s <signal> <jobID>) allows the user to issue any signal to a running job.
Common Job Commands
|Submit a job||sbatch <job script>|
|Delete a job||scancel <job ID>|
|Job status (all)||squeue|
|Job status (by job)||squeue -j <job ID>|
|Job status (by user)||sq (equivalent of: squeue -u <your_uniqname>)|
sq <user> (equivalent of: squeue -u <user>)
|Job status (detailed)||scontrol show job -dd <job ID>|
|Show expected start time||squeue -j <job ID> --start|
|Queue list / info||scontrol show partition <name>|
|Node list||scontrol show nodes|
|Node details||scontrol show node <node>|
|Hold a job||scontrol hold <job ID>|
|Release a job||scontrol release <job ID>|
|Start an interactive job||salloc <args>|
|X forwarding||salloc <args> --x11|
|Read stdout messages at runtime||No equivalent command / not needed.Use the--outputoption instead.|
|Monitor or review a job’s resource usage||sacct -j <job_num> --format JobID,jobname,NTasks,nodelist,CPUTime,ReqMem,Elapsed|
(seesacctfor all format options)
|View job batch script||scontrol write batch_script <jobID> [filename]|
|View accounts you can submit to||sacctmgr show assoc user=$USER|
|View users with access to an account||sacctmgr show assoc account=<account>|
|View default submission account and wckey||sacctmgr show User <account>|
The basic job states are these:
- Pending – the job is in the queue, waiting to be scheduled
- Held – the job was submitted, but was put in the held state (ineligible to run)
- Running – the job has been granted an allocation. If it’s a batch job, the batch script has been run
- Complete – the job has completed successfully
- Timeout – the job was terminated for running longer than its wall clock limit
- Preempted – the running job was terminated to reassign its resources to a higher QoS job
- Failed – the job terminated with a non-zero status
- Node Fail – the job terminated after a compute node reported a problem
For the complete list, see the “JOB STATE CODES” section under the squeue man page.
A pending job can remain pending for a number of reasons:
- Dependency – the pending job is waiting for another job to complete
- Priority – the job is not high enough in the queue
- Resources – the job is high in the queue, but there are not enough resources to satisfy the job’s request
- Partition Down – the queue is currently closed to running any new jobs
For the complete list, see the “JOB REASON CODES” section under the squeue man page.
Displaying Computing Resources
As stated above, computing resources are nodes, CPUs, memory, and generic resources like GPUs. The resources of each compute node can be seen by running thescontrol show nodecommand. The characteristics of each partition can be seen by running thescontrol show partitioncommand. Finally, a load summary report for each partition can be seen by runningsinfo.
To show a summary of cluster resources on a per partition basis:
[user@gl-login1 ~]$ sinfoPARTITION AVAIL TIMELIMIT NODES STATE NODELISTstandard up 14-00:00:00 24 idle gl31[60-83]gpu up 14-00:00:00 2 idle gl10[18-19]largemem up 14-00:00:00 3 idle gl000[0-3]
[user@gl-login1 ~]$ sstate———————————————————————————————————————Node AllocCPU TotalCPU PercentUsedCPU CPULoad AllocMem TotalMem PercentUsedMem NodeState———————————————————————————————————————gl3160 0 36 0.00 0.03 0 192000 0.00 IDLEgl3160 0 36 0.00 0.04 0 192000 0.00 IDLE...
In this example the user “user” has access to submit workloads to the accounts support and hpcstaff on the Great Lakes cluster. To show associations for the current user:
[user@gl-login1 ~]$ sacctmgr show assoc user=$USERCluster Account User Partition ...———————————————————————————————————————greatlakes support user 1 greatlakes hpcstaff user 1
Job Statistics and Accounting
Thesreportcommand provides aggregated usage reports by user and account over a specified period. Examples:
By user:sreport -T billing cluster AccountUtilizationByUser Start=2017-01-01 End=2017-12-31
By account:sreport -T billing cluster UserUtilizationByAccount Start=2017-01-01 End=2017-12-31
For all of the sreport options see thesreport man page.
Time Remaining in an Application
If a running application overruns its wall clock limit, all its work could be lost. To prevent such an outcome, applications have two means for discovering the time remaining in the application.
The first means is to use the sbatch --signal=<sig_num>[@<sig_time>] option to request a signal (like USR1 or USR2) at sig_time number of seconds before the allocation expires. The application must register a signal handler for the requested signal in order to to receive it. The handler takes the necessary steps to write a checkpoint file and terminate gracefully.
The second means is for the application to issue a library call to retrieve its remaining time periodically. When the library call returns a remaining time below a certain threshold, the application can take the necessary steps to write a checkpoint file and terminate gracefully.
Slurm offers the slurm_get_rem_time() library call that returns the time remaining. On some systems, the yogrt library (man yogrt) is also available to provide the time remaining.
The Portable Batch System (PBS) and the Simple Linux Utility for Resource Management (Slurm) are two of the most popular job schedulers used for requesting resources allocations on a multi user cluster. Marquette University's previous HPC resource Pére used the PBS scheduler, while current HPC resource Raj uses Slurm.How does SRUN work? ›
srun immediately executes the script on the remote host, while sbatch copies the script in an internal storage and then uploads it on the compute node when the job starts. You can check this by modifying your submission script after it has been submitted; changes will not be taken into account (see this).What is Sbatch command? ›
sbatch submits a batch script to Slurm. The batch script may be given to sbatch through a file name on the command line, or if no file name is specified, sbatch will read in a script from standard input. The batch script may contain options preceded with "#SBATCH" before any executable commands in the script.What is Slurm and how does it work? ›
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 workload manager, Slurm has three key functions.Is Slurm a programming language? ›
Slurm is written in the C language and uses a GNU autoconf configuration engine. While initially written for Linux, other UNIX-like operating systems should be easy porting targets. Code should adhere to the Linux kernel coding style. (Some components of Slurm have been taken from various sources.What are Slurm commands? ›
The slurmd daemons provide fault-tolerant hierarchical communications. The user commands include: sacct, sacctmgr, salloc, sattach, sbatch, sbcast, scancel, scontrol, scrontab, sdiag, sh5util, sinfo, sprio, squeue, sreport, srun, sshare, sstat, strigger and sview. All of the commands can run anywhere in the cluster.What is the difference between Sbatch and Srun? ›
Answer. srun executes in interactive and blocking mode while sbatch executes in batch processing and non blocking mode. srun is mostly used to run immediate jobs but sbatch can be used for later execution of jobs. Note, that if your SSH session is interrupted for any reason, the srun will automatically be cancelled.What is the difference between Mpirun and Srun? ›
mpirun start proxy on each node, and then start the MPI tasks. On the other hand (e.g. the MPI tasks are not directly known by the resource manager). srun directly start the MPI tasks, but that requires some support ( PMI or PMIx ) from SLURM .How do you use SRUN in slurm? ›
After typing your srun command and options on the command line and pressing enter, Slurm will find and then allocate the resources you specified. Depending on what you specified, it can take a few minutes for Slurm to allocate those resources. You can view all of the srun options on the Slurm documentation website.How do I submit multiple jobs in Slurm? ›
The wrap feature of sbatch can be used to submit multiple jobs at once. Sbatch will wrap the specified command string in a simple "sh" shell script, and submit that script to the slurm controller.
Slurm - What Is It? Slurm is a job scheduler that manages cluster resources. It is what allows you to run a job on the cluster without worrying about finding a free node. It also tracks resource usage so nodes aren't overloaded by having too many jobs running on them at once.How do I specify memory in Slurm? ›
Memory Allocation in Slurm
You simply specify it using --memory=<size> in your srun and sbatch command. In the (rare) case that you provide more flexible number of threads (Slurm tasks) or GPUs, you could also look into --mem-per-cpu and --mem-per-gpu .
Slurm may be the most widely accepted framework for AI applications, both in enterprise and academic use, though other schedulers are available (such as LSF and Kubernetes kube-scheduler).Is Slurm an operating system? ›
The Slurm Workload Manager, formerly known as Simple Linux Utility for Resource Management (SLURM), or simply Slurm, is a free and open-source job scheduler for Linux and Unix-like kernels, used by many of the world's supercomputers and computer clusters.How do you check nodes in Slurm? ›
- sinfo. The sinfo command will show you the status of partitions in the cluster. ...
- scontrol. The scontrol command can be used to view the status/configuration of the nodes in the cluster. ...
AWS ParallelCluster is tested with Slurm configuration parameters, which are provided by default. Any changes that you make to these Slurm configuration parameters are done at your own risk. They are supported only on a best-effort basis.Is Slurm a framework? ›
Second, it provides a framework for starting, executing, and monitoring work (typically a parallel job) on a set of allocated nodes. Finally, it arbitrates contention for resources by managing a queue of pending work.What does Slurm stand for? ›
Simple Linux Utility for Resource Management. Slurm is a very popular soft drink, it is highly addictive.How do I know if my job is running in Slurm? ›
You can see all jobs running under the account by running squeue -A account_name and then find out more information on each job by scontrol show job <jobid> .How do I monitor jobs in Slurm? ›
Information on all running and pending batch jobs managed by SLURM can be obtained from the SLURM command squeue . Note that information on completed jobs is only retained for a limited period. Information on jobs that ran in the past is via. sacct An example of the output squeue is shown below.
There are two ways of submitting a job to SLURM: Submit via a SLURM job script - create a bash script that includes directives to the SLURM scheduler. Submit via command-line options - provide directives to SLURM via command-line arguments.How does slurm calculate priority? ›
The priority then depends on five elements:
- Job age: how long the job has been waiting in the queue ;
- User fairshare: a measure of past usage of the cluster by the user ;
- Job size: the number of CPUs a job requests ;
Alternatively, you can cancel a job submitted by srun or in an interactive shell, with salloc, by pressing Ctrl-C . In the example below, we have asked to start an interactive job, which we then cancel during waiting. Note Do not kill/skill srun to cancel a SLURM job! Doing so only terminates srun .What does CPUs per task mean? ›
A communication bus between a Socket/CPU and I/O controllers (disks, networking, graphics,...) in the server. Slurm complicates this, however, by using the terms core and cpu interchangeably depending on the context and Slurm command. --cpus-per-taks= for example is actually specifying the number of cores per task.Is OpenMPI same as MPI? ›
OpenMPI is an implementation of the Message Passing Interface (MPI), used in distributed memory architectures. Unlike shared memory described above, distributed memory uses a collection of independent core memory pairs that synchronize using a network, mostly found in supercomputers.How do I run an MPI program on multiple nodes? ›
- Log in to the head node onyx. Acquire nodes from the scheduler: pbsget -4.
- Start up the MPI daemons on all nodes using the command: mpdboot.
- Next run your mpi program with the mpiexec command. mpiexec -n 4 hello_world.
- Stop all MPI daemons. ...
- Exit and release all allocated nodes with the command: exit.
Slurm is supported by the mpirun command of the Intel® MPI Library through the Hydra Process Manager by default.Can you add time to Slurm job? ›
In order to increment or decrement the current time limit, the JobId specification must precede the TimeLimit specification. Only the Slurm administrator or root can increase job's TimeLimit. UserID=<UID or name> Used with the JobName option to identify jobs to be modified.How do I specify GPU in Slurm? ›
To use a GPU in a Slurm job, you need to explicitly specify this when running the job using the –gres or –gpus flag. The following flags are available: –gres specifies the number of generic resources required per node. –gpus specifies the number of GPUs required for an entire job.What is a daemon in Slurm? ›
slurmd is the compute node daemon of Slurm. It monitors all tasks running on the compute node , accepts work (tasks), launches tasks, and kills running tasks upon request.
Note: There is a maximum limit of 3000 jobs per user. See Annotated SLURM Script for a step-by-step explanation of all options.Can a job be binded to multiple nodes? ›
Step 1− If multi node selection was enabled, you get the chance to select multiple nodes to run the job on. The job will then be executed on each of the nodes, one after the other or concurrent - depending on the configuration.How do I cancel all pending jobs on Slurm? ›
Say you dispatch thousands of jobs with Slurm, but goofed something up and want to cancel some of those jobs. If you want to cancel all of your jobs then you can use scancel -u username , where username is your system username (i.e. jharri62 is my username).What ports does Slurm use? ›
The default port used by slurmctld to listen for incoming requests is 6817. This port can be changed with the SlurmctldPort slurm.What is a cluster in Slurm? ›
A cluster is comprised of all the nodes managed by a single slurmctld daemon. Slurm offers the ability to target commands to other clusters instead of, or in addition to, the local cluster on which the command is invoked.What is the latest version of Slurm? ›
Slurm can be upgraded from version 20.11 or 21.08 to version 22.05 without loss of jobs or other state information. Upgrading directly from an earlier version of Slurm will result in loss of state information.How do I check my Slurm memory limit? ›
If the memory limit is not requested, SLURM will assign the default 16 GB. The maximum allowed memory per node is 128 GB. To see how much RAM per node your job is using, you can run commands sacct or sstat to query MaxRSS for the job on the node - see examples below.How much RAM do I need for ZoneMinder? ›
ZoneMinder also shows average load on the top right corner of the Web Console for easy access. Around 700MB of memory. So if you have 2GB of memory, you should be all set.How do you find the amount of memory in node? ›
To find out how much memory there is per node on a given cluster, use the snodes command and look at the MEMORY column which lists values in units of MB. You can also use the shownodes command.Which platform is best for AI? ›
Google AI Platform, TensorFlow, Microsoft Azure, Rainbird, Infosys Nia, Wipro HOLMES, Dialogflow, Premonition, Ayasdi, MindMeld, Meya, KAI, Vital A.I, Wit, Receptiviti, Watson Studio, Lumiata, Infrrd are some of the top Artificial Intelligence Platforms .
In summary: Slurm works well for batch workloads and optimizing resource usage based on a queue of jobs. Kubernetes is meant for use in 'modern' cloud-native microservice architectures. It optimizes scheduling and scaling live services based on available resources. So, two quite different worlds.Can bot build without using AI? ›
Without Artificial Intelligence, we won't be able to create a bot. As a result, it is incorrect. To make the bot adapt to the information and examples, we'll require machine learning. The bot's ability to deduce specific probability on which can be decided must then be tested in the real world.How do you end a job in Slurm? ›
- $ scancel <jobid>
- $ squeue -u $USER.
- $ scancel 1234567.
It's a sweet, tart, refreshing drink with the striking flavour and spicy warmth of ginger. I coloured it with yellow and green food colouring to get the same bright green shade of the slurm drink in this sparking limeade, and I added some vodka for good measure too.How many cores does a node have? ›
Each regular compute node has 64 cores, 500 GB of available memory, GigE and EDR (100Gbit) Infiniband interconnects.How do I know how many cores a cluster has? ›
- Use sc. statusTracker. getExecutorInfos. length to get the total number of nodes. ...
- Use java. lang. Runtime. getRuntime. ...
- Multiply both results (subtracting 1 from the total number of nodes) to get the total number of cores available: Scala Copy. java.lang.
- The following command lists all nodes: $ oc get nodes. The following example is a cluster with healthy nodes: $ oc get nodes. ...
- The following command lists information about a single node: $ oc get node <node> $ oc get node node1.example.com.
PBS stands for Portable Bash Script. A PBS Script is used to submit jobs (computation user wants to be done) to the scheduler. These jobs can then be handled by the scheduler and require no further input from the user, who often simply logs out after succesful submission.What is PBS cluster? ›
Portable Batch System (or simply PBS) is the name of computer software that performs job scheduling. Its primary task is to allocate computational tasks, i.e., batch jobs, among the available computing resources. It is often used in conjunction with UNIX cluster environments.What is a Slurm job? ›
SLURM is a popular job scheduler that is used to allocate, manage and monitor jobs on your cluster. In this blog post we teach you the basics of submitting SLURM jobs on your very own auto scaling cluster in the cloud with RONIN.
You may only have up to three PBS items on PBS prescription; and only have one Authority Required item, including STREAMLINED authority items. A PBS prescription may only contain PBS items, and cannot contain non-PBS items. If you would like more information please visit the Information for PBS Prescribers section.How much does a PBS script cost? ›
The standard PBS Safety Net price is $6.80 and free for those with a Pension, Concession or Veteran's card. In 2022, the standard PBS Safety Net threshold is $1,457.10 and $244.80 for those with a Pension, Concession or Veteran's card.How long is a PBS script valid for? ›
a repeat authorisation attached to a patient/pharmacist PBS prescription not more than 12 months after the date of the original PBS prescription.How do I check my PBS queue? ›
- qsub. To submit a batch job to the specified queue using a script: %qsub -q queue_name job_script. ...
- qstat. To display queue information: %qstat -Q queue_name %qstat -q queue_name %qstat -fQ queue_name. ...
- qdel. To delete (cancel) a job: %qdel job_id.
- qhold. To hold a job: %qhold job_id.
- your name and practice address.
- your prescriber number.
- your patient's name and address.
- a tick in the relevant PBS or RPBS box.
- the name, strength and form of medicine.
- the dose and instructions for use.
- the quantity and number of repeats.
- your signature.
We released Altair PBS Professionalreg; under an open-source license, opening the core of the software to the community. PBS Professional®, continues to be available as a hardened, commercial version for commercial customers, but alongside that offering we are committing to being open and community oriented.