Queue of tasks for parallel computing in R -

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the outline of want follows:

#function run 6k times, doesn't return somefunction <- function(integer,string) {...} #parameters passed params <- data.frame(ints=1:6000, strings=...) #number of cores system has numcores <- detectcores()  count <- 1; #run while there still tasks run , there free core while(count <= 6000 && <# of running tasks < numcores>) {    count <- count + 1;    <assign somefunction(params$ints[count],params$strings[count]) free core> }

the 2 pieces of code in <> brackets not sure how proceed. on ubuntu system, can use multicore package.

i suspect may need integer keep track of how many cores being used , when process finishes, subtracts 1 integer , new process adds one, or maybe array of length numcores keep 0 or 1 if it's being used or not.

you should use either multicore or snow packages. snow, can accomplish after pretty simply:

clust<-makecluster(detectcores()) clusterexport(clust,"somefunction") ## added on edit, see comment steve weston clustfun<-function(i,params){somefunction(params$ints[i],params$strings[i])} clusterapply(clust,1:6000,clustfun,params)

this evaluate calls in parallel , assign results list of length 6000. can use clusterapplylb performs load-balancing similar describing.

http://cran.r-project.org/web/packages/snow/index.html


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