slurm_apply to compute function over multiple sets of
parameters in parallel, spread across multiple nodes of a Slurm cluster,
with similar syntax to
slurm_apply( f, params, ..., jobname = NA, nodes = 2, cpus_per_node = 2, processes_per_node = cpus_per_node, preschedule_cores = TRUE, global_objects = NULL, add_objects = NULL, pkgs = rev(.packages()), libPaths = NULL, rscript_path = NULL, r_template = NULL, sh_template = NULL, slurm_options = list(), submit = TRUE )
A function that accepts one or many single values as parameters and may return any type of R object.
A data frame of parameter values to apply
Additional arguments to
The name of the Slurm job; if
The (maximum) number of cluster nodes to spread the calculation
The number of CPUs requested per node. This argument is
mapped to the Slurm parameter
The number of logical CPUs to utilize per node,
i.e. how many processes to run in parallel per node. This can exceed
Corresponds to the
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
Older deprecated name of
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
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
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
Whether or not to submit the job to the cluster with
slurm_job object containing the
jobname and the
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
f needs to access should be included in
global_objects or passed as additional arguments through
slurm_options to set any option recognized by
slurm_options = list(time = "1:00:00", share = TRUE).
See http://slurm.schedmd.com/sbatch.html 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_apply 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").
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 submit.sh from that directory.
After sending the job to the Slurm cluster,
slurm_apply 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.
slurm_call to evaluate a single function call.
slurm_map to evaluate a function over a list.