Use slurm_map to compute function over a list in parallel, spread across multiple nodes of a Slurm cluster, with similar syntax to lapply.

  jobname = NA,
  nodes = 2,
  cpus_per_node = 2,
  processes_per_node = cpus_per_node,
  preschedule_cores = TRUE,
  job_array_task_limit = NULL,
  global_objects = NULL,
  pkgs = rev(.packages()),
  libPaths = NULL,
  rscript_path = NULL,
  r_template = NULL,
  sh_template = NULL,
  slurm_options = list(),
  submit = TRUE



A list to apply f to. Each element of x corresponds to a separate function call.


A function that accepts one element of x as its first argument, and may return any type of R object.


Additional arguments to f. These arguments do not vary with each call to f.


The name of the Slurm job; if NA, it is assigned a random name of the form "slr####".


The (maximum) number of cluster nodes to spread the calculation over. slurm_map automatically divides x in chunks of approximately equal size to send to each node. Less nodes are allocated if the parameter set is too small to use all CPUs on the requested nodes.


The number of CPUs requested per node. This argument is mapped to the Slurm parameter cpus-per-task.


The number of logical CPUs to utilize per node, i.e. how many processes to run in parallel per node. This can exceed cpus_per_node for nodes which support hyperthreading. Defaults to processes_per_node = cpus_per_node.


Corresponds to the mc.preschedule argument of parallel::mclapply. Defaults to TRUE. If TRUE, the elements of x are assigned to cores before computation. If FALSE, each element of x is executed by the next available core. Setting FALSE may be faster if different elements of x result in very variable completion time for jobs.


The maximum number of job array tasks to run at the same time. Defaults to NULL (no limit).


A character vector containing the name of R objects to be saved in a .RData file and loaded on each cluster node prior to calling f.


A character vector containing the names of packages that must be loaded on each cluster node. By default, it includes all packages loaded by the user when slurm_map is called.


A character vector describing the location of additional R library trees to search through, or NULL. The default value of NULL corresponds to libraries returned by .libPaths() on a cluster node. Non-existent library trees are silently ignored.


The location of the Rscript command. If not specified, defaults to the location of Rscript within the R installation being run.


The path to the template file for the R script run on each node. If NULL, uses the default template "rslurm/templates/slurm_run_R.txt".


The path to the template file for the sbatch submission script. If NULL, uses the default template "rslurm/templates/submit_sh.txt".


A named list of options recognized by sbatch; see Details below for more information.


Whether or not to submit the job to the cluster with sbatch; see Details below for more information.


A slurm_job object containing the jobname and the number of nodes effectively used.


This function creates a temporary folder ("_rslurm_[jobname]") in the current directory, holding .RData and .RDS data files, the R script to run and the Bash submission script generated for the Slurm job.

The set of input parameters is divided in equal chunks sent to each node, and f is evaluated in parallel within each node using functions from the parallel R package. The names of any other R objects (besides x) that f needs to access should be included in global_objects or passed as additional arguments through ....

Use slurm_options to set any option recognized by sbatch, e.g. slurm_options = list(time = "1:00:00", share = TRUE). See for details on possible options. Note that full names must be used (e.g. "time" rather than "t") and that flags (such as "share") must be specified as TRUE. The "array", "job-name", "nodes", "cpus-per-task" and "output" options are already determined by slurm_map and should not be manually set.

When processing the computation job, the Slurm cluster will output two types of files in the temporary folder: those containing the return values of the function for each subset of parameters ("results_[node_id].RDS") and those containing any console or error output produced by R on each node ("slurm_[node_id].out").

If submit = TRUE, the job is sent to the cluster and a confirmation message (or error) is output to the console. If submit = FALSE, a message indicates the location of the saved data and script files; the job can be submitted manually by running the shell command sbatch from that directory.

After sending the job to the Slurm cluster, slurm_map returns a slurm_job object which can be used to cancel the job, get the job status or output, and delete the temporary files associated with it. See the description of the related functions for more details.

See also

slurm_call to evaluate a single function call.

slurm_apply to evaluate a function row-wise over a data frame of parameters.

cancel_slurm, cleanup_files, get_slurm_out and get_job_status which use the output of this function.


if (FALSE) {
sjob <- slurm_map(func, list)
get_job_status(sjob) # Prints console/error output once job is completed.
func_result <- get_slurm_out(sjob, "table") # Loads output data into R.