Hello!
 
I'm processing Raster-images splitting the work on a quadcore CPU using snowfall.
The Problem is, that in the images there are areas with much CPU work and other with less. Using "sfInit(parallel=TRUE, cpus=4)" some CPU has very much work to do (~12h) and the other just a few minutes.
 
The function I use is "sfLapply()" because it had the best "system.time()" results. I tryed "sfClusterApplyLB()" but CPUs work here with quite low performance (~15% each) and it took more time.
 
Using "sfClusterSplit()" the vector is divided in 4 consecutive parts, I'm looking for a different method to divide that vector:
 
Example: not  V1 = 1,2,3; V2= 4,5,6 but V1=1,3,5; V2=2,4,6, or maybe divided by random is good too.
 
Thanks to all, geatings Matteo

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