Defines the underlying parallelization mode for parallelMap
.
Also allows to set a “level” of parallelization.
Only calls to parallelMap
with a matching level are parallelized.
The defaults of all settings are taken from your options, which you can
also define in your R profile.
For an introductory tutorial and information on the options configuration, please
go to the project's github page at https://github.com/berndbischl/parallelMap.
parallelStart(mode, cpus, socket.hosts, bj.resources = list(),
bt.resources = list(), logging, storagedir, level,
load.balancing = FALSE, show.info, suppress.local.errors = FALSE,
...)parallelStartLocal(show.info, suppress.local.errors = FALSE, ...)
parallelStartMulticore(cpus, logging, storagedir, level,
load.balancing = FALSE, show.info, ...)
parallelStartSocket(cpus, socket.hosts, logging, storagedir, level,
load.balancing = FALSE, show.info, ...)
parallelStartMPI(cpus, logging, storagedir, level,
load.balancing = FALSE, show.info, ...)
parallelStartBatchJobs(bj.resources = list(), logging, storagedir, level,
show.info, ...)
parallelStartBatchtools(bt.resources = list(), logging, storagedir,
level, show.info, ...)
[character(1)
]
Which parallel mode should be used:
“local”, “multicore”, “socket”, “mpi”, “BatchJobs”.
Default is the option parallelMap.default.mode
or, if not set,
“local” without parallel execution.
[integer(1)
]
Number of used cpus.
For local and BatchJobs mode this argument is ignored.
For socket mode, this is the number of processes spawned on localhost, if
you want processes on multiple machines use socket.hosts
.
Default is the option parallelMap.default.cpus
or, if not set,
detectCores
for multicore mode,
max(1, mpi.universe.size - 1)
for mpi mode
and 1 for socket mode.
[character
]
Only used in socket mode, otherwise ignored.
Names of hosts where parallel processes are spawned.
Default is the option parallelMap.default.socket.hosts
, if this option exists.
[list
]
Resources like walltime for submitting jobs on HPC clusters via BatchJobs.
See submitJobs
.
Defaults are taken from your BatchJobs config file.
[list
]
Analog to bj.resources
.
See submitJobs
.
[logical(1)
]
Should slave output be logged to files via sink
under the storagedir
?
Files are named "<iteration_number>.log" and put into unique
subdirectories named “parallelMap_log_<nr>” for each subsequent
parallelMap
operation.
Previous logging directories are removed on parallelStart
if logging
is enabled.
Logging is not supported for local mode, because you will see all
output on the master and can also run stuff like
traceback
in case of errors.
Default is the option parallelMap.default.logging
or, if not set,
FALSE
.
[character(1)
]
Existing directory where log files and intermediate objects for BatchJobs
mode are stored.
Note that all nodes must have write access to exactly this path.
Default is the current working directory.
[character(1)
]
You can set this so only calls to parallelMap
that have exactly the same level are parallelized.
Default is the option parallelMap.default.level
or, if not set,
NA
which means all calls to parallelMap
are are potentially parallelized.
[logical(1)
]
Enables load balancing for multicore, socket and mpi.
Set this to TRUE
if you have heterogeneous runtimes.
Default is FALSE
[logical(1)
]
Verbose output on console for all further package calls?
Default is the option parallelMap.default.show.info
or, if not set,
TRUE
.
[logical(1)
]
Should reporting of error messages during function evaluations in local mode be suppressed?
Default ist FALSE, i.e. every error message is shown.
[any]
Optional parameters, for socket mode passed to makePSOCKcluster
,
for mpi mode passed to makeCluster
and for multicore
passed to mcmapply
(mc.preschedule
(overwriting load.balancing
),
mc.set.seed
,
mc.silent
and mc.cleanup
are supported for multicore).
Nothing.
Currently the following modes are supported, which internally dispatch the mapping operation to functions from different parallelization packages:
No parallelization with mapply
.
Multicore execution on a single machine with mclapply
.
Snow MPI cluster on one or multiple machines with makeCluster
and clusterMap
.
Parallelization on batch queuing HPC clusters, e.g., Torque, SLURM, etc., with batchMap
.
For BatchJobs mode you need to define a storage directory through the argument storagedir
or
the option parallelMap.default.storagedir
.