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(Simple Linux Utility for Resource Management) is a software package for submitting, scheduling, and monitoring jobs on large compute clusters. This page details how to use SLURM for submitting and monitoring jobs on ACCRE’s Vampire cluster. These differences are highlighted in. A summary of SLURM commands is shown in. (A great reference for SLURM commands can also be found by. For example, the example below is a simple Python job requesting 6 node, 6 CPU core, 555 MB of RAM, and 7 hours of wall time. In general, #SBATCH options tend to be more self-explanatory. Note that specifying the node ( #SBATCH --nodes=6 ) and CPU core ( #SBATCH --ntasks=6 ) count must be broken off into two lines in SLURM, and that SLURM has no equivalent to #PBS -j oe (SLURM combines standard output and error into a single file by default).

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/bin/bash directive on the first line. The subsequent lines begin with the SLURM directive #SBATCH followed by a resource request or other pertinent job information. Below the #SBATCH directives are the Linux commands needed to run your program or analysis. For reference, the following table lists common Torque options (Torque is the previous job scheduler used at ACCRE, and many Torque/PBS variants are still in use at high-performance computing centers like ACCRE)along side the equivalent option in SLURM. For examples of how to include the appropriate SLURM options for parallel jobs, please refer to. Note that the --constrain option allows a user to target certain processor families or nodes with a specific CPU core count. All non-GPU groups on the cluster have access to the production and debug partitions. The purpose of the debug partition is to allow users to quickly test a representative job before submitting a larger number of jobs to the production partition (which is the default partition on our cluster). Wall time limits and other policies for each of our partitions are shown below. Just like Torque, SLURM offers a number of helpful commands for tasks ranging from job submission and monitoring to modifying resource requests for jobs that have already been submitted to the queue. Below is a list of SLURM commands, as well as the Torque equivalent in the far left column. The sbatch command is used for submitting jobs to the cluster. Slurm ) is shown below: This job (called just_a_test ) requests 6 compute node, 6 task (by default, SLURM will assign 6 CPU core per task), 6 GB of RAM per CPU core, and 65 minutes of wall time (the time required for the job to complete). Optionally, any #SBATCH line may be replaced with an equivalent command-line option. For instance, the #SBATCH --ntasks=6 line could be removed and a user could specify this option from the command line using: The commands needed to execute a program must be included beneath all #SBATCH commands. Lines beginning with the # symbol (without /bin/bash or SBATCH) are comment lines that are not executed by the shell. The example above simply prints the version of Python loaded in a user’s path. A real job would likely do something more complex than the example above, such as read in a Python file for processing by the Python interpreter. For more information about sbatch see: http: //slurm.

Schedmd. Com/sbatch. Htmlsqueue is used for viewing the status of jobs. By default, squeue will output the following information about currently running jobs and jobs waiting in the queue: Job ID, Partition, Job Name, User Name, Job Status, Run Time, Node Count, and Node List. There are a large number of command-line options available for customizing the information provided by squeue. Below are a list of examples: For more information about squeue see: http: //slurm. Com/squeue. HtmlThis command is used for viewing information for completed jobs. This can be useful for monitoring job progress or diagnosing problems that occurred during job execution. By default, sacct will report Job ID, Job Name, Partition, Account, Allocated CPU Cores, Job State, and Exit Code for all of the current user’s jobs that completed since midnight of the current day. Many options are available for modifying the information output by sacct: The --format option is particularly useful, as it allows a user to customize output of job usage statistics. We would suggest create an alias for running a customized version of sacct. For instance, the elapsed and Timelimit arguments allow for a comparison of allocated vs. Actual wall time. MaxRSS and MaxVMSize shows maximum RAM and virtual memory usage information for a job, respectively, while ReqMem reports the amount of RAM requested. For more information about sacct see: http: //slurm.

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Com/sacct. Htmlscontrol is used for monitoring and modifying queued jobs. One of its most powerful options is the scontrol show job option, which is analogous to Torque’s checkjob command. Scontrol is also used for holding and releasing jobs. Below is a list of useful scontrol commands: Please note that the time limit or memory of a job can only be adjust for pending jobs, not for running jobs. For more information about scontrol see: http: //slurm. Com/scontrol. HtmlThe function of salloc is to launch an interactive job on compute nodes. This can be useful for troubleshooting/debugging a program or if a program requires user input. To launch an interactive job requesting 6 node, 7 CPU cores, and 6 hour of wall time, a user would type: This command will execute and then wait for the allocation to be obtained. At this point, a user can execute normal commands and launch his/her application like normal. Note that many of the sbatch options are also applicable for salloc, so a user can insert other typical resource requests, such as memory. Another useful feature in salloc is that it enforces resource requests to prevent users or applications from using more resources than were requested. For example: In this example, srun -n 9 failed because only 7 tasks were allocated for this interactive job (for details on srun see below). Also note that typing exit during the interactive session will kill the interactive job, even if the allotted wall time has not been reached. For more information about salloc see: http: //slurm.

Com/salloc. HtmlSimilarly to salloc, this command provides an interactive shell on a compute node but with the possibility of running programs with a graphical user interface (GUI) directly on the compute node. To correctly visualize the GUI on your monitor, you first need to connect to the cluster’s gateway with the X66 forwarding abilitated as follows: Then from the gateway request the interactive job with X66 forwarding as in the following example: At this point when launching a GUI based software, the interface should appear on your monitor. Sinfo allows users to view information about SLURM nodes and partitions. A partition is a set of nodes (usually a cluster) defined by the cluster administrator. Below are a few example uses of sinfo: For more information about sinfo see: http: //slurm. Com/sinfo. Htmlsreport is used for generating reports of job usage and cluster utilization. It queries the SLURM database to obtain this information. By default information will be shown for jobs run since midnight of the current day. Some examples: For more information about sreport see: http: //slurm. Com/sreport. HtmlThis command is used to launch a parallel job step. More details about running MPI jobs within SLURM are provided. Invoking srun on a non-MPI command or executable will result in this program being independently run X times on each of the CPU cores in the allocation.

Alternatively, srun can be run directly from the command line on a gateway, in which case srun will first create a resource allocation for running the parallel job. The -n [CPU_CORES] option is passed to specify the number of CPU cores for launching the parallel job step. For example, running the following command from the command line will obtain an allocation consisting of 66 CPU cores and then run the command hostname across these cores: For more information about srun see: http: //www. Com/slurmdocs/srun. HtmlIn addition to commands provided by SLURM, ACCRE staff have also written a number of useful commands that are available for use on the ACCRE cluster. Rtracejob is used to compare resource requests to resource usage for an individual job. It takes a job id as its single argument. For example: rtracejob is useful for troubleshooting when something goes wrong with your job. For example, a user might want to check how much memory a job used compared to how much was requested, or how long it took a job to execute relative to how much wall time was requested. In this example, note the Requested Memory reported is 6555Mc, meaning 6555 megabytes per core (the “c” stands for “core”). This is the default for jobs that specify no memory requirement. Q8 is a useful command for getting a breakdown of currently running or recently run jobs and their states, organized by user, group, and account. The command takes no arguments and after a few seconds will produce output with a format similar to the following: In this example, two users (jack and jill) are running jobs on the cluster. Both of these users are in a group called science, which is under an account called science_account. Accounts are important because resource limits are generally enforced on the account level, so q8 makes it easy to compare an account’s usage to its limits and to see which users are running jobs under an account. The three types of limits are Max Cores, Max Mem, and Max CPU Time, each of which limit the resources available to all jobs running under an account. For reference, if a job is pending due to a resource limitation, this will be indicated in the far right column from the output of squeue. AssocGrpCpuLimit, AssocGrpMemLimit, and AssocGrpRunMinsLimit are the reasons that will be shown by squeue based on limits on CPU cores, memory, or CPU time, respectively.

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