run a for loop in parallel in R

Question

I have a for loop that is something like this:

for (i=1:150000) {    tempMatrix = {}    tempMatrix = functionThatDoesSomething() #calling a function    finalMatrix =  cbind(finalMatrix, tempMatrix)  } 

Could you tell me how to make this parallel ?

I tried this based on an example online, but am not sure if the syntax is correct. It also didn't increase the speed much.

finalMatrix = foreach(i=1:150000, .combine=cbind) %dopar%  {    tempMatrix = {}    tempMatrix = functionThatDoesSomething() #calling a function     cbind(finalMatrix, tempMatrix)  } 

Answer 1

Thanks for your feedback. I did look up parallel after I posted this question.

Finally after a few tries, I got it running. I have added the code below in case it is useful to others

library(foreach) library(doParallel)  #setup parallel backend to use many processors cores=detectCores() cl <- makeCluster(cores[1]-1) #not to overload your computer registerDoParallel(cl)  finalMatrix <- foreach(i=1:150000, .combine=cbind) %dopar% {    tempMatrix = functionThatDoesSomething() #calling a function    #do other things if you want     tempMatrix #Equivalent to finalMatrix = cbind(finalMatrix, tempMatrix) } #stop cluster stopCluster(cl) 

Note - I must add a note that if the user allocates too many processes, then user may get this error: Error in serialize(data, node$con) : error writing to connection

Note - If .combine in the foreach statement is rbind , then the final object returned would have been created by appending output of each loop row-wise.

Hope this is useful for folks trying out parallel processing in R for the first time like me.

References: http://www.r-bloggers.com/parallel-r-loops-for-windows-and-linux/ https://beckmw.wordpress.com/2014/01/21/a-brief-foray-into-parallel-processing-with-r/