sfFArgsApplyDep: sfFArgsApplyDep

In twSnowfall: tw snowfall extension

Description

Load balanced application of F_APPLY with using result from a previous run to construct arguments.

Usage

sfFArgsApplyDep(N_APPLYCASES, F_ARGS, F_APPLY, SFFARGSAPPLY_initVal, 
    SFFARGSAPPLY_dependsStep = length(SFFARGSAPPLY_initVal), 
    ..., SFFARGSAPPLY_ADDARGS = list(), debugSequential = FALSE, 
    freeMasterNode = FALSE)

Arguments

N_APPLYCASES	number of cases to calculate
F_ARGS	function returning arguments for case i, see details
F_APPLY	function to calculate
SFFARGSAPPLY_initVal	intial values
SFFARGSAPPLY_dependsStep	dependencies in 1..n,
...	further arguments passed to F_APPLY
SFFARGSAPPLY_ADDARGS	results presented to argfun for the first 1..dependsStep results
debugSequential	the number of processors (might be smaller than cluster to assure that previous case i-useNCpus has been evaluated.)
freeMasterNode	if set to TRUE, no job is submitted to first node, so that this node can dispatch jobs without waiting

Author(s)

Thomas Wutzler

See Also

twSnowfall twDynamicClusterApplyDep

Examples

#sfInit(parallel=TRUE,cpus=2)

# using as many cpus as rows in Z
(Z<-matrix(letters[1:12],nrow=3))
F_APPLY <- function(x,z) paste(x,z,sep="");
F_ARGS <- function(i,prevRes){list(x=prevRes,z=Z[i])}	
.res0 <- rep("_",nrow(Z))	# dependStep will be length of .res0
resSeq <- sfFArgsApplyDep( length(Z), F_ARGS, F_APPLY, .res0)
(res <- matrix(sfSimplifyLBResult(resSeq),nrow=nrow(Z)))

# Gives the same results as having one parallel call per column.
# However, in this implementation, the finished nodes do not need to 
# wait for possibly slower finishing of other rows, and can tackle
# already further columns.

twSnowfall documentation built on May 2, 2019, 4:47 p.m.