Create a cluster of nodes for parallel computation
makeCluster(
numberOfThreads,
singleThreadToMain = TRUE,
setAndromedaTempFolder = TRUE,
setAndromedaMemoryLimit = TRUE,
setAndromedaThreads = TRUE
)Arguments
- numberOfThreads
Number of parallel threads.
- singleThreadToMain
If
numberOfThreadsis 1, should we fall back to running the process in the main thread?- setAndromedaTempFolder
When TRUE, the andromedaTempFolder option will be copied to each thread.
- setAndromedaMemoryLimit
When TRUE, the andromedaMemoryLimit option will be set in each thread to be either the global andromedaMemoryLimit / numberOfThreads or 20 percent of the system memory / number of threads.
- setAndromedaThreads
When TRUE, the andromedaThreads option will be set in each thread to be the global andromedaThreads / numberOfThreads.
Value
An object representing the cluster.
Examples
fun <- function(x) {
return (x^2)
}
cluster <- makeCluster(numberOfThreads = 3)
clusterApply(cluster, 1:10, fun)
#> | | | 0% | |======= | 10% | |============== | 20% | |===================== | 30% | |============================ | 40% | |=================================== | 50% | |========================================== | 60% | |================================================= | 70% | |======================================================== | 80% | |=============================================================== | 90% | |======================================================================| 100%
#> [[1]]
#> [1] 1
#>
#> [[2]]
#> [1] 4
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#> [[3]]
#> [1] 9
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#> [[4]]
#> [1] 16
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#> [1] 25
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#> [1] 36
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#> [1] 49
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#> [[8]]
#> [1] 64
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#> [[9]]
#> [1] 81
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#> [[10]]
#> [1] 100
#>
stopCluster(cluster)