Parallel computing using latrend
The model estimation functions support parallel computation through the use of the foreach mechanism. In order to make use of parallel execution, a parallel back-end must be registered.
On Windows, the parallel-package can be used to define parallel socket workers.
nCores = parallel::detectCores(logical = FALSE) cl = parallel::makeCluster(nCores - 1) parallel::clusterEvalQ(cl, expr=library(latrend))
Then, register the cluster as the parallel back-end using the doParallel package:
doParallel::registerDoParallel(cl)
If you defined your own lcMethod or lcModel extension classes, make sure to load them on the workers as well.
This can be done, for example, using:
parallel::clusterEvalQ(cl,
expr = setClass('lcMethodMyImpl', contains = "lcMethod"))On Unix systems, it is easier to setup parallelization as the R process is forked.
In this example we use the doMC package:
nCores = parallel::detectCores(logical = FALSE) doMC::registerDoMC(nCores - 1)
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