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makeClusterPSOCK(nworkers) gained protection against setting up too many localhost workers relative to number of available CPU cores. If nworkers / availableCores() is greater than 1.0 (100%), then a warning is produced. If greater than 3.0 (300%), an error is produced. These limits can be configured by R option parallelly.maxWorkers.localhost. These checks are skipped if nworkers inherits from AsIs, e.g. makeClusterPSOCK(I(16)). The current 3.0 (300%) limit is likely to be decreased in a future release. A few packages fail R CMD check --as-cran with this validation enabled. For example, one package uses 8 parallel workers in its examples, while R CMD check --as-cran only allows for two. To give such packages time to be fixed, the CRAN-enforced limits are ignored for now.makeClusterPSOCK() could produce a confusing error Invalid port: NA if a non-available port was requested. Now the error message is more informative, e.g. Argument 'port' specifies non-available port(s): 80.isNodeAlive() and killNode() now support also worker processes that run on remote machines. They do this by connecting to the remote machine using the same method used to launch the worker, which is typically SSH, and do their R calls that way.
isNodeAlive() and killNode() gained argument timeout for controlling the maximum time, in seconds, before giving up and returning NA.
Add cloneNode(), which can be used to “restart” RichSOCKnode cluster nodes.
Argument worker for makeNodePSOCK() now takes the optional, logical attribute localhost to manually specify that the worker is a localhost worker.
Add print() for RichSOCKnode, which gives more details than print() for SOCKnode.
print() for RichSOCKnode and RichSOCKcluster report on nodes with broken connections.
Add as.cluster() for RichSOCKnode, which returns a RichSOCKcluster.
Introduce R option parallelly.supportsMulticore.disableOn to control where multicore processing is disabled by default.
Calling killNode() on RichSOCKnode node could theoretically kill a process on the current machine with the same process ID (PID), although the parallel worker (node) is running on another machine.
isNodeAlive() on RichSOCKnode node could theoretically return TRUE because there was a process with the same process ID (PID) on the current machine, although the parallel worker (node) is running on another machine.
isLocalHost() for SOCK0node was not declared an S3 method.
freePort() defaults to default = NA_integer_, so that NA_integer_ is returned when no free port could be found. However, in R (< 4.0.0), which does not support port querying, we use default = "random".help("makeClusterPSOCK") that rscript_sh = "cmd" is needed if the remote machines run MS Windows.makeClusterPSOCK(..., verbose = TRUE) would not show verbose output. One still had to set option parallelly.debug to TRUE.
availableWorkers() could produce false sanity-check warnings on mismatching ‘PE_HOSTFILE’ content and ‘NSLOTS’ for certain SGE-cluster configurations.
availableWorkers(constraints = "connections"), which limits the number of workers that can be be used to the current number of free R connections according to freeConnections(). This is the maximum number of PSOCK, SOCK, and MPI parallel cluster nodes we can open without running out of available R connections.availableCores() would produce a warning In is.na(constraints) : is.na() applied to non-(list or vector) of type 'NULL' when running with R (< 4.0.0).
availableWorkers() did not acknowledge the "cgroups2.cpu.max" and "Bioconductor" methods added to availableCores() in parallelly 1.33.0 (2022-12-13). It also did not acknowledge methods "cgroups.cpuset" and "cgroups.cpuquota" added in parallelly 1.31.0 (2022-04-07), and "nproc" added in parallelly 1.26.1 (2021-06-29).
When makeClusterPSOCK() failed to connect to all parallel workers within the connectTimeout time limit, could either produce Error in sprintf(ngettext(failed, "Cluster setup failed (connectTimeout=%.1f seconds). %d worker of %d failed to connect.", : invalid format '%d'; use format %f, %e, %g or %a for numeric objects instead of an informative error message, or an error message with the incorrect information.
Add killNode() to terminate cluster nodes via process signaling. Currently, this is only supported for parallel workers on the local machine, and only those created by makeClusterPSOCK().
makeClusterPSOCK() and likes now assert the running R session has enough permissions on the operating system to do system calls such as system2("Rscript --version"). If not, an informative error message is produced.
On Unix, availableCores() queries also control groups v2 (cgroups2) field cpu.max for a possible CPU quota allocation. If a CPU quota is set, then the number of CPUs is rounded to the nearest integer, unless its less that 0.5, in case it’s rounded up to a single CPU. An example, where cgroups CPU quotas can be set to limit the total CPU load, is with Linux containers, e.g. docker run --cpus=3.5 ....
Add support for availableCores(methods = "connections"), which returns the current number of free R connections per freeConnections(). This is the maximum number of PSOCK, SOCK, and MPI parallel cluster nodes we can open without running out of available R connections. A convenient way to use this and all other methods is availableCores(constraints = "connections").
Now availableCores() recognizes environment variable IS_BIOC_BUILD_MACHINE, which is set to true by the Bioconductor (>= 3.16) check servers. If true, then a maximum of four (4) cores is returned. This new environment variable replaces legacy variable BBS_HOME used in Bioconductor (<= 3.15).
availableCores() splits up method "BiocParallel" into two; "BiocParallel" and "Bioconductor". The former queries environment variable BIOCPARALLEL_WORKER_NUMBER and the latter IS_BIOC_BUILD_MACHINE. This means availableCores(which = "all") now reports on both.
isNodeAlive() will now produce a once-per-session informative warning when it detects that it is not possible to check whether another process is alive on the current machine.
Add section to help("makeClusterPSOCK", package = "parallelly") explaining why R CMD check may produce “checking for detritus in the temp directory … NOTE” and how to avoid them.
Add section ‘For package developers’ to help("makeClusterPSOCK", package = "parallelly") reminding us that we need to stop all clusters we created in package examples, tests, and vignettes.
isNodeAlive() failed to record which method works for testing if a process exists or not, which meant it would keep trying all methods each time. Similarly, if none works, it would still keep trying each time instead of returning NA immediately. On some systems, failing to check whether a process exists could result in one or more warnings, in which case those warnings would be produced for each call to isNodeAlive().host element of the SOCK0node or SOCKnode objects created by makeClusterPSOCK() lost attribute localhost for localhost workers. This made some error messages from the future package less informative.revtunnel of makeNodePSOCK(), and therefore also of makeClusterPSOCK(), is now NA, which means it’s agile to whether rshcmd[1] specifies an SSH client, or not. If SSH is used, then it will resolve to revtunnel = TRUE, otherwise to revtunnel = FALSE. This removed the need for setting revtunnel = FALSE, when non-SSH clients are used.availableCores() and availableWorkers() gained support for the ‘Fujitsu Technical Computing Suite’ job scheduler. Specifically, they acknowledges environment variables PJM_VNODE_CORE, PJM_PROC_BY_NODE, and PJM_O_NODEINF. See help("makeClusterPSOCK", package = "parallelly") for an example.makeClusterPSOCK() would fail with Error: node$session_info$process$pid == pid is not TRUE when running R in Simplified Chinese (LANGUAGE=zh_CN), Traditional Chinese (Taiwan) (LANGUAGE=zh_TW), or Korean (LANGUAGE=ko) locales.
Some warnings and errors showed the wrong call.
Changes to option parallelly.availableCores.system would be ignored if done after the first call to availableCores().
availableCores() with option parallelly.availableCores.system set to less that parallel::detectCores() would produce a warning, e.g. “[INTERNAL]: Will ignore the cgroups CPU set, because it contains one or more CPU indices that is out of range [0,0]: 0-7”.
freePort() to "random", which used to be "first". The main reason for this is to make sure the default behavior is to return a random port also on R (< 4.0.0) where we cannot test whether or not a port is available.On Unix, availableCores() now queries also control groups (cgroups) fields cpu.cfs_quota_us and cpu.cfs_period_us, for a possible CPU quota allocation. If a CPU quota is set, then the number of CPUs is rounded to the nearest integer, unless its less that 0.5, in case it’s rounded up to a single CPU. An example, where cgroups CPU quotas can be set to limit the total CPU load, is with Linux containers, e.g. docker run --cpus=3.5 ....
In addition to cgroups CPU quotas, availableCores() also queries cgroups for a possible CPU affinity, which is available in field cpuset.set. This should give the same result as what the already existing ‘nproc’ method gives. However, not all systems have the nproc tool installed, in which case this new approach should work. Some high-performance compute (HPC) environments set the CPU affinity so that jobs do not overuse the CPUs. It may also be set by Linux containers, e.g. docker run --cpuset-cpus=0-2,8 ....
The minimum value returned by availableCores() is one (1). This can be overridden by new option parallelly.availableCores.min. This can be used to test parallelization methods on single-core machines, e.g. options(parallelly.availableCores.min = 2L).
The ‘nproc’ result for availableCores() was ignored if nproc > 9.
availableCores() would return the ‘fallback’ value when only ‘system’ and ‘nproc’ information was available. However, in this case, we do want it to return ‘nproc’ when ‘nproc’ != ‘system’, because that is a strong indication that the number of CPU cores is limited by control groups (cgroups) on Linux. If ‘nproc’ == ‘system’, we cannot tell whether cgroups is enabled or not, which means we will fall back to the ‘fallback’ value if there is no other evidence that another number of cores are available to the current R process.
Technically, canPortBeUsed() could falsely return FALSE if the port check was interrupted by, say, a user interrupt.
freePort(ports, default = "random") would always use return ports[1] if the system does not allow testing if a port is available or not, or if none of the specified ports are available.
makeNodePSOCK(), and therefore also makeClusterPSOCK(), gained argument rscript_sh, which controls how Rscript arguments are shell quoted. The default is to make a best guess on what type of shell is used where each cluster node is launched. If launched locally, then it whatever platform the current R session is running, i.e. either a POSIX shell ("sh") or MS Windows ("cmd"). If remotely, then the assumption is that a POSIX shell ("sh") is used.
makeNodePSOCK(), and therefore also makeClusterPSOCK(), gained argument default_packages, which controls the default set of R packages to be attached on each cluster node at startup. Moreover, if argument rscript specifies an ‘Rscript’ executable, then argument default_packages is used to populate Rscript command-line option --default-packages=.... If rscript specifies something else, e.g. an ‘R’ or ‘Rterm’ executable, then environment variable R_DEFAULT_PACKAGES=... is set accordingly when launching each cluster node.
Argument rscript_args of makeClusterPSOCK() now supports "*" values. When used, the corresponding element will be replaced with the internally added Rscript command-line options. If not specified, such options are appended at the end.
makeClusterPSOCK() did not support backslashes (\) in rscript_libs, backslashes that may originate from, for example, Windows network drives. The result was that the worker would silently ignore any rscript_libs components with backslashes.
The package detects when R CMD check runs and adjust default settings via environment variables in order to play nicer with the machine where the checks are running. Some of these environment variables were in this case ignored since parallelly 1.26.0.
makeClusterPSOCK() launches parallel workers with option socketOptions set to "no-delay" by default. This decreases the communication latency between workers and the main R session, significantly so on Unix. This option requires R (>= 4.1.0) and has no effect in early versions of R.Added argument socketOptions to makeClusterPSOCK(), which sets the corresponding R option on each cluster node when they are launched.
Argument rscript_envs of makeClusterPSOCK() can also be used to unset environment variables cluster nodes. Any named element with value NA_character_ will be unset.
Argument rscript of makeClusterPSOCK() now supports "*" values. When used, the corresponding element will be replaced with the "Rscript", or if homogenous = TRUE, then absolute path to current ‘Rscript’.
makeClusterPSOCK() example on how to launch workers distributed across multiple CPU Groups on MS Windows 10.isForkedChild() would only return TRUE in a forked child process, if and only if, it had already been called in the parent R process.
Using argument rscript_startup would cause makeClusterPSOCK() to fail in R-devel (>= r80666).
example("isNodeAlive") now uses \donttest{} to avoid long (> 10
Add isNodeAlive() to check whether a cluster and cluster nodes are alive or not.
Add isForkedChild() to check whether or not the current R process is a forked child process.
Environment variable R_PARALLELLY_SUPPORTSMULTICORE_UNSTABLE was incorrectly parsed as a logical instead of a character string. If the variables was set to, say, "quiet", this would cause an error when the package was loaded.
makeClusterPSOCK() failed to fall back to setup_strategy = "sequential", when not supported by the current R version.
availableCores() and availableWorkers() now respects environment variable BIOCPARALLEL_WORKER_NUMBER introduced in BiocParallel (>= 1.27.2). They also respect BBS_HOME which is set on the Bioconductor check servers to limit the number of parallel workers while checking Bioconductor packages.makeClusterPSOCK() and parallel::makeCluster() failed with error “Cluster setup failed. setup_strategy = "parallel" and when the tcltk package is loaded when running R (>= 4.0.0 && <= 4.1.0) on macOS. Now parallelly forces setup_strategy = "sequential" when the tcltk package is loaded on these R versions.makeClusterPSOCK(..., setup_strategy = "parallel") would forget to close an socket connection used to set up the workers. This socket connection would be closed by the garbage collector eventually with a warning.
parallelly::makeClusterPSOCK() would fail with “Error in freePort(port) : Unknown value on argument ‘port’: ‘auto’” if environment variable R_PARALLEL_PORT was set to a port number.
parallelly::availableCores() would produce ‘Error in if (grepl(“^ [1-9]$”, res)) return(as.integer(res)) : argument is of length zero’ on Linux systems without nproc installed.
print() on RichSOCKcluster mentions when the cluster is registered to be automatically stopped by the garbage collector.setup_strategy = "parallel" when using makeClusterPSOCK() or parallel::makeCluster(). The symptom is that they, after a long wait, result in “Error in makeClusterPSOCK(workers, …) : Cluster setup failed. setup_strategy = "sequential for parallelly and parallel when running in the RStudio Console. If you wish to override this behavior, you can always set option parallelly.makeNodePSOCK.setup_strategy to "parallel", e.g. in your ~/.Rprofile file. Alternatively, you can set the environment variable R_PARALLELLY_MAKENODEPSOCK_SETUP_STRATEGY=parallel, e.g. in your ~/.Renviron file.nproc installed, availableCores() would be limited by environment variables OMP_NUM_THREADS and OMP_THREAD_LIMIT, if set. For example, on conservative systems that set OMP_NUM_THREADS=1 as the default, availableCores() would pick this up via nproc and return 1. This was not the intended behavior. Now those environment variables are temporarily unset before querying nproc.R_PARALLELLY_* (and R_FUTURE_*) environment variables are now only read when the parallelly package is loaded, where they set the corresponding parallelly.* option. Previously, some of these environment variables were queried by different functions as a fallback to when an option was not set. By only parsing them when the package is loaded, it decrease the overhead in functions, and it clarifies that options can be changed at runtime whereas environment variables should only be set at startup.makeClusterPSOCK() now support setting up cluster nodes in parallel similarly to how parallel::makePSOCKcluster() does it. This significantly reduces the setup turnaround time. This is only supported in R (>= 4.0.0). To revert to the sequential setup strategy, set R option parallelly.makeNodePSOCK.setup_strategy to "sequential".
Add freePort() to get a random TCP port that can be opened.
parallelly.availableCores.fallback and environment variable R_PARALLELLY_AVAILABLECORES_FALLBACK was ignored since parallelly 1.22.0, when support for ‘nproc’ was added to availableCores().ssh client. This means that regardless whether you are on Linux, macOS, or Windows 10, setting up parallel workers on external machines over SSH finally works out of the box without having to install PuTTY or other SSH clients. This was possible because a workaround was found for a Windows 10 bug preventing us from using reverse tunneling over SSH. It turns out the bug reveals itself when using hostname ‘localhost’ but not ‘127.0.0.1’, so we use the latter.availableCores() gained argument omit to make it easier to put aside zero or more cores from being used in parallel processing. For example, on a system with four cores, availableCores(omit = 1) returns 3. Importantly, since availableCores() is guaranteed to always return a positive integer, availableCores(omit = 4) == 1, even on systems with four or fewer cores. Using availableCores() - 4 on such systems would return a non-positive value, which would give an error downstream.makeClusterPSOCK(), or actually makeNodePSOCK(), did not accept all types of environment variable names when using rscript_envs, e.g. it would give an error if we tried to pass _R_CLASS_MATRIX_ARRAY_.
makeClusterPSOCK() had a “length > 1 in coercion to logical” bug that could affect especially MS Windows 10 users.
plink of the PuTTY software, (ii) ssh in the RStudio distribution, and (iii) ssh of Windows 10. Previously, the latter was considered first but that still has a bug preventing us from using reverse tunneling.makeClusterPSOCK(), or actually makeNodePSOCK(), gained argument quiet, which can be used to silence output produced by manual = TRUE.
c() for cluster objects now warns about duplicated cluster nodes.
Add isForkedNode() to test if a cluster node runs in a forked process.
Add isLocalhostNode() to test if a cluster node runs on the current machine.
Now availableCores() and availableWorkers() avoid recursive calls to the custom function given by options parallelly.availableCores.custom and parallelly.availableWorkers.custom, respectively.
availableWorkers() now recognizes the Slurm environment variable SLURM_JOB_NODELIST, e.g. "dev1,n[3-4,095-120]". It will use scontrol show hostnames "$SLURM_JOB_NODELIST" to expand it, if supported on the current machine, otherwise it will attempt to parse and expand the nodelist specification using R. If either of environment variable SLURM_JOB_CPUS_PER_NODE or SLURM_TASKS_PER_NODE is set, then each node in the nodelist will be represented that number of times. If in addition, environment variable SLURM_CPUS_PER_TASK (always a scalar), then that is also respected.
parallelly. prefix for options and the R_PARALLELLY_ prefix for environment variables. Settings that use the corresponding future. and R_FUTURE_ prefixes are still recognized.availableCores() did not respect environment variable SLURM_TASKS_PER_NODE when the job was allocated more than one node.
Above argument quiet was introduced in future 1.19.1 but was mistakenly dropped from parallelly 1.20.0 when that was released, and therefore also from future (>= 1.20.0).
availableCores(), availableWorkers(), and freeCores() gained argument logical, which is passed down to parallel::detectCores() as-is. The default is TRUE but it can be changed by setting the R option parallelly.availableCores.logical. This option can in turn be set via environment variable R_PARALLELLY_AVAILABLECORES_LOGICAL which is applied (only) when the package is loaded.
Now makeClusterPSOCK() asserts that there are enough free connections available before attempting to create the parallel workers. If too many workers are requested, an informative error message is produced.
Add availableConnections() and freeConnections() to infer the maximum number of connections that the current R installation can have open at any time and how many of those are currently free to be used. This limit is typically 128 but may be different in custom R installations that are built from source.
Now availableCores() queries also Unix command nproc, if available. This will make it respect the number of CPU/cores limited by ‘cgroups’ and Linux containers.
PSOCK cluster workers are now set up to communicate using little endian (useXDR = FALSE) instead of big endian (useXDR = TRUE). Since most modern systems use little endian, useXDR = FALSE speeds up the communication noticeably (10-15%) on those systems. The default value of this argument can be controlled by the R option parallelly.makeNodePSOCK.useXDR or the corresponding environment variable R_PARALLELLY_MAKENODEPSOCK_USEXDR.
Add cpuLoad() for querying the “average” system load on Unix-like systems.
Add freeCores() for estimating the average number of unused cores based on the average system load as given by cpuLoad().
R_FUTURE_AVAILABLECORES_FALLBACK and R_FUTURE_AVAILABLECORES_SYSTEM, none of the R_PARALLELLY_* and R_FUTURE_* ones where recognized.find_rshcmd() which was never meant to be exported.makeClusterPSOCK() gained argument validate to control whether or not the nodes should be tested after they’ve been created. The validation is done by querying each node for its session information, which is then saved as attribute session_info on the cluster node object. This information is also used in error messages, if available. This validation has been done since version 1.5.0 but now it can be disabled. The default of argument validate can be controlled via an R options and an environment variable.
Now makeNodePSOCK(..., rscript_envs = "UNKNOWN") produces an informative warning on non-existing environment variables that was skipped.
makeClusterPSOCK() would produce an error on ‘one node produced an error: could not find function “getOptionOrEnvVar”’ if parallelly is not available on the node.
makeClusterPSOCK() would attempt to load parallelly on the worker. If it’s not available on the worker, it would result in a silent warning on the worker. Now parallelly is not loaded.
makeClusterPSOCK(..., tries = n) would retry to setup a cluster node also on errors that were unrelated to node setup or node connection errors.
The error message on using an invalid rscript_envs argument for makeClusterPSOCK() reported on the value of rscript_libs (sic!).
makeNodePSOCK(..., rscript_envs = "UNKNOWN") would result in an error when trying to launch the cluster node.
find_rshcmd() which was never meant to be exported.availableCores(), and availableWorkers(), supportsMulticore(), as.cluster(), autoStopCluster(), makeClusterMPI(), makeClusterPSOCK(), and makeNodePSOCK() from the future package.isConnectionValid() and connectionId() adopted from internal code of the future package.Renamed environment variable R_FUTURE_MAKENODEPSOCK_tries used by makeClusterPSOCK() to R_FUTURE_MAKENODEPSOCK_TRIES.
connectionId() did not return -1L on Solaris for connections with internal ‘nil’ pointers because they were reported as ‘0’ - not ‘nil’ or ‘0x0’.
Now availableCores() better supports Slurm. Specifically, if environment variable SLURM_CPUS_PER_TASK is not set, which requires that option --slurm-cpus-per-task=n is specified and SLURM_JOB_NUM_NODES=1, then it falls back to using SLURM_CPUS_ON_NODE, e.g. when using --ntasks=n.
Now availableCores() and availableWorkers() supports LSF/OpenLava. Specifically, they acknowledge environment variable LSB_DJOB_NUMPROC and LSB_HOSTS, respectively.
makeClusterPSOCK() will now retry to create a cluster node up to tries (default: 3) times before giving up. If argument port species more than one port (e.g. port = "random") then it will also attempt find a valid random port up to tries times before giving up. The pre-validation of the random port is only supported in R (>= 4.0.0) and skipped otherwise.
makeClusterPSOCK() skips shell quoting of the elements in rscript if it inherits from AsIs.
makeClusterPSOCK(), or actually makeNodePSOCK(), gained argument quiet, which can be used to silence output produced by manual = TRUE.
plan(multisession), plan(cluster, workers = <number>), and makeClusterPSOCK() which they both use internally, sets up localhost workers twice as fast compared to versions since future 1.12.0, which brings it back to par with a bare-bone parallel::makeCluster(..., setup_strategy = "sequential") setup. The slowdown was introduced in future 1.12.0 (2019-03-07) when protection against leaving stray R processes behind from failed worker startup was implemented. This protection now makes use of memoization for speedup.print() on RichSOCKcluster gives information not only on the name of the host but also on the version of R and the platform of each node (“worker”), e.g. “Socket cluster with 3 nodes where 2 nodes are on host ‘localhost’ (R version 4.0.0 (2020-04-24), platform x86_64-w64-mingw32), 1 node is on host ‘n3’ (R version 3.6.3 (2020-02-29), platform x86_64-pc-linux-gnu)”.
It is now possible to set environment variables on workers before they are launched by makeClusterPSOCK() by specify them as as <name>=<value> as part of the rscript vector argument, e.g. rscript=c("ABC=123", "DEF='hello world'", "Rscript"). This works because elements in rscript that match regular expression "^ [[:alpha:]_][[:alnum:]_]*=.*" are no longer shell quoted.
makeClusterPSOCK() now returns a cluster that in addition to inheriting from SOCKcluster it will also inherit from RichSOCKcluster.
Made makeClusterPSOCK() and makeNodePSOCK() agile to the name change from parallel:::.slaveRSOCK() to parallel:::.workRSOCK() in R (>= 4.1.0).
makeClusterPSOCK(..., rscript) will not try to locate rscript[1] if argument homogeneous is FALSE (or inferred to be FALSE).
makeClusterPSOCK(..., rscript_envs) would result in a syntax error when starting the workers due to non-ASCII quotation marks if option useFancyQuotes was not set to FALSE.
makeClusterPSOCK() gained argument rscript_envs for setting environment variables in workers on startup, e.g. rscript_envs = c(FOO = "3.14", "BAR")._R_CHECK_LIMIT_CORES_ set. To better emulate CRAN submission checks, the future package will, when loaded, set this environment variable to TRUE if unset and if R CMD check is running. Note that future::availableCores() respects _R_CHECK_LIMIT_CORES_ and returns at most 2L (two cores) if detected.makeClusterPSOCK() draws a random port from (when argument port is not specified) can now be controlled by environment variable R_FUTURE_RANDOM_PORTS. The default range is still 11000:11999 as with the parallel package.?makeClusterPSOCK with instructions on how to troubleshoot when the setup of local and remote clusters fail.makeClusterPSOCK() could produce warnings like “cannot open file ‘/tmp/alice/Rtmpi69yYF/future.parent=2622.a3e32bc6af7.pid’: No such file”, e.g. when launching R workers running in Docker containers.
makeClusterMPI() did not work for MPI clusters with ‘comm’ other than ‘1’.
Now availableCores() also recognizes PBS environment variable NCPUS, because the PBSPro scheduler does not set PBS_NUM_PPN.
If, option future.availableCores.custom is set to a function, then availableCores() will call that function and interpret its value as number of cores. Analogously, option future.availableWorkers.custom can be used to specify a hostnames of a set of workers that availableWorkers() sees. These new options provide a mechanism for anyone to customize availableCores() and availableWorkers() in case they do not (yet) recognize, say, environment variables that are specific the user’s compute environment or HPC scheduler.
makeClusterPSOCK() gained support for argument rscript_startup for evaluating one or more R expressions in the background R worker prior to the worker event loop launching. This provides a more convenient approach than having to use, say, rscript_args = c("-e", sQuote(code)).
makeClusterPSOCK() gained support for argument rscript_libs to control the R package library search path on the workers. For example, to prepend the folder ~/R-libs on the workers, use rscript_libs = c("~/R-libs", "*"), where "*" will be resolved to the current .libPaths() on the workers.
makeClusterPSOCK() did not shell quote the Rscript executable when running its pre-tests checking whether localhost Rscript processes can be killed by their PIDs or not.makeClusterPSOCK() fails to create one of many nodes, then it will attempt to stop any nodes that were successfully created. This lowers the risk for leaving R worker processes behind.makeClusterPSOCK() in future (>= 1.11.1) produced warnings when argument rscript had length(rscript) > 1.makeClusterPSOCK() fails to connect to a worker, it produces an error with detailed information on what could have happened. In rare cases, another error could be produced when generating the information on what the workers PID is.makeClusterPSOCK() and makeNodePSOCK() can now be controlled via environment variables in addition to R options that was supported in the past. An advantage of using environment variables is that they will be inherited by child processes, also nested ones.R CMD check is running or not. If it is, then a few future-specific environment variables are adjusted such that the tests play nice with the testing environment. For instance, it sets the socket connection timeout for PSOCK cluster workers to 120 seconds (instead of the default 30 days!). This will lower the risk for more and more zombie worker processes cluttering up the test machine (e.g. CRAN servers) in case a worker process is left behind despite the main R processes is terminated. Note that these adjustments are applied automatically to the checks of any package that depends on, or imports, the future package.makeClusterPSOCK() would fail to connect to a worker, for instance due to a port clash, then it would leave the R worker process running - also after the main R process terminated. When the worker is running on the same machine, makeClusterPSOCK() will now attempt to kill such stray R processes. Note that parallel::makePSOCKcluster() still has this problem.makeClusterPSOCK() produces more informative error messages whenever the setup of R workers fails. Also, its verbose messages are now prefixed with “[local output]” to help distinguish the output produced by the current R session from that produced by background workers.
It is now possible to specify what type of SSH clients makeClusterPSOCK() automatically searches for and in what order, e.g. rshcmd = c("<rstudio-ssh>", "<putty-plink>").
Now makeClusterPSOCK() preserves the global RNG state (.Random.seed) also when it draws a random port number.
makeClusterPSOCK() gained argument rshlogfile.
makeClusterPSOCK(..., rscript = "my_r") would in some cases fail to find the intended my_r executable.Add makeClusterMPI(n) for creating MPI-based clusters of a similar kind as parallel::makeCluster(n, type = "MPI") but that also attempts to workaround issues where parallel::stopCluster() causes R to stall.
makeClusterPSOCK() and makeClusterMPI() gained argument autoStop for controlling whether the cluster should be automatically stopped when garbage collected or not.
makeClusterPSOCK() produced a warning when environment variable R_PARALLEL_PORT was set to random (e.g. as on CRAN).makeClusterPSOCK() now produces a more informative warning if environment variable R_PARALLEL_PORT specifies a non-numeric port.makeClusterPSOCK(), and therefore plan(multisession) and plan(multiprocess), will use the SSH client distributed with RStudio as a fallback if neither ssh nor plink is available on the system PATH.makeClusterPSOCK(..., renice = 19) would launch each PSOCK worker via nice +19 resulting in the error “nice: ‘+19’: No such file or directory”. This bug was inherited from parallel::makePSOCKcluster(). Now using nice --adjustment=19 instead.makeClusterPSOCK() now defaults to use the Windows PuTTY software’s SSH client plink -ssh, if ssh is not found.
Argument homogeneous of makeNodePSOCK(), a helper function of makeClusterPSOCK(), will default to FALSE also if the hostname is a fully qualified domain name (FQDN), that is, it “contains periods”. For instance, c('node1', 'node2.server.org') will use homogeneous = TRUE for the first worker and homogeneous = FALSE for the second.
makeClusterPSOCK() now asserts that each cluster node is functioning by retrieving and recording the node’s session information including the process ID of the corresponding R process.
makeClusterPSOCK() gained more detailed descriptions on arguments and what their defaults are.connectTimeout and timeout of makeNodePSOCK() can now be controlled via global options.availableCores(method = "mc.cores") is now defunct in favor of "mc.cores+1".makeClusterPSOCK() treats workers that refer to a local machine by its local or canonical hostname as "localhost". This avoids having to launch such workers over SSH, which may not be supported on all systems / compute cluster.
Added availableWorkers(). By default it returns localhost workers according to availableCores(). In addition, it detects common HPC allocations given in environment variables set by the HPC scheduler.
Option future.availableCores.fallback, which defaults to environment variable R_FUTURE_AVAILABLECORES_FALLBACK can now be used to specify the default number of cores / workers returned by availableCores() and availableWorkers() when no other settings are available. For instance, if R_FUTURE_AVAILABLECORES_FALLBACK=1 is set system wide in an HPC environment, then all R processes that uses availableCores() to detect how many cores can be used will run as single-core processes. Without this fallback setting, and without other core-specifying settings, the default will be to use all cores on the machine, which does not play well on multi-user systems.
Creation of cluster futures (including multisession ones) would time out already after 40 seconds if all workers were busy. New default timeout is 30 days (option future.wait.timeout).
availableCores(methods = "_R_CHECK_LIMIT_CORES_") would give an error if not running R CMD check.
Added makeClusterPSOCK() - a version of parallel::makePSOCKcluster() that allows for more flexible control of how PSOCK cluster workers are set up and how they are launched and communicated with if running on external machines.
Added generic as.cluster() for coercing objects to cluster objects to be used as in plan(cluster, workers = as.cluster(x)). Also added a c() implementation for cluster objects such that multiple cluster objects can be combined into a single one.
user to remote() was ignored (since 1.1.0).workers = "localhost" they (again) use the exact same R executable as the main / calling R session (in all other cases it uses whatever Rscript is found on the PATH). This was already indeed implemented in 1.0.1, but with the added support for reverse SSH tunnels in 1.1.0 this default behavior was lost.cluster() and remote() to connect to remote clusters / machines. As long as you can connect via SSH to those machines, it works also with these future. The new code completely avoids incoming firewall and incoming port forwarding issues previously needed. This is done by using reverse SSH tunneling. There is also no need to worry about internal or external IP numbers.availableCores() also acknowledges environment variable NSLOTS set by Sun/Oracle Grid Engine (SGE).availableCores() returns 3L (=2L+1L) instead of 2L if _R_CHECK_LIMIT_CORES_ is set.availableCores() also acknowledges the number of CPUs allotted by Slurm.availableCores("mc.cores") returns getOption("mc.cores") + 1L, because option mc.cores specifies “allowed number of additional R processes” to be used in addition to the main R process.These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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