This is a patch release to initiate automatic generation of DOIs by Zenodo with each future release.
job_array_task_limit included in
slurm_*() functions to allow the user to set
get_job_status() now checks whether
slurm_*.out files exist before attempting to open them, avoiding an error (#72).
slurm_map() with similar syntax to
Better handling of additional arguments to
slurm_apply(), and of how R objects are made available to the Slurm jobs (#48).
Slurm jobID added to
slurm_job objects (#55).
processes_per_node argument added to support hyperthreading (#57).
get_slurm_out()) is now compatible with partitions that cannot accept interactive jobs and with newer releases of Slurm, though there is a potential incompatibility with versions of Slurm older than 16.05.0, which was released on May 2016 (#65).
Improved status with
get_slurm_out to gather results (#30).
Allow user to provide custom .R and .sh templates (#47).
Allow user to specify path to
Rscript (#45) and number of CPUS per task (#36).
Allow user to disable core prescheduling if tasks have high variance in completion time (816b40e).
Pass (serialized) functions to Slurm nodes without stringifying.
add_objects objects from correct environment.
Package tests evaluate on a cluster when available.
Include reverse dependency check in release process.
README now separate from package documentation.
Vignette can be built on CRAN tests again (no slurm submissions).
parallel::mcmapply, without SIMPLIFY, to prevent
mc.cores error when checking on Windows.
wait argument adds option to
slurm_call to block the calling script until the submitted job completes. This option can be used to allow immediate processing of a submitted job’s output (#2).
Use “.RDS” file extension, rather than “.RData”, for serialized objects (#4).
Minor bug fixes (#4).
First version on CRAN
submit argument to
submit = FALSE, the submission scripts are created but not run. This is useful if the files need to be transferred from a local machine to the cluster and run at a later time.
Added new optional arguments to
slurm_call, allowing users to give informative names to SLURM jobs (
jobname) and set any options understood by
data_file argument to
slurm_call is replaced with
add_objects, which accepts a vector of R object names from the active workspace and automatically saves them in a .RData file to be loaded on each node.
slurm_call now generate R and Bash scripts through whisker templates. Advanced users may want to edit those templates in the
templates folder of the installed R package (e.g. to set default SBATCH options in
Files generated by the package (scripts, data files and output) are now saved in a subfolder named
_rslurm_[jobname] in the current working directory.
Minor updates, including reformatting the output of
print_job_status and removing this package’s dependency on
slurm_apply function to use
parallel::mcMap instead of
mcmapply, which fixes a bug where list outputs (i.e. each function call returns a list) would be collapsed in a single list (rather than returned as a list of lists).
Changed the interface so that the output type (table or raw) is now an argument of
get_slurm_out rather than of
slurm_apply, and defaults to
cpus_per_node argument to
slurm_apply, indicating the number of parallel processes to be run on each node.
Added the optional argument
slurm_apply, which can take the value
table (each function evaluation returns a row, output is a data frame) or
raw (each function evaluation returns an arbitrary R object, output is a list).
Fixed a bug in the chunk size calculation for