parallel foreach loops produce mclapply error

Question

Those are my first steps with parallel computing in R. The code below results in the following error. I am clueless, since there is no mclapply function in what I wrote, at least I did not put it explicitly. Error: ``` Error in mclapply(argsList, FUN, mc.preschedule = preschedule, mc.set.seed = set.seed, : (list) object cannot be coerced to type 'integer' Calls: %dopar% -> -> mclapply Execution halted ``` Code: ``` dist<-array(0, dim=c(320,500,25)) mc<-8 cl<-makeCluster(mc) registerDoMC(cl) opts<-list(chunkSize=10) for(a in 1:25) { dist[,,a]<-foreach(x=1:500, .combine='cbind', .options.mc=opts) %:% foreach(y=1:320, .combine='c') %dopar% { gcd.slc(crdsx[y,x], crdsy[y,x], lot[a,5], lot[a,4]) } } stopCluster(cl) ``` On a different machine, it works nicely with ``` registerDoParallel(cl) ``` instead of ``` registerDoMC(cl) ```

Accepted Answer

You're getting that error because `registerDoMC` expects an integer argument, not a cluster object, while `registerDoParallel` expects either an integer or a cluster object. Basically, you need to decide which package to use and not mix them.

If you use `doMC`, then you never create a cluster object. A minimal `doMC` example looks like:

```
library(doMC)
registerDoMC(3)
foreach(i=1:10) %dopar% sqrt(i)
```

The `doParallel` package is a mashup of the `doMC` and `doSNOW` packages, and so you don't need to use cluster objects. Converting the previous example to `doParallel` is very simple:

```
library(doParallel)
registerDoParallel(3)
foreach(i=1:10) %dopar% sqrt(i)
```

The confusing thing is that on Windows, `doParallel` will actually create and use a cluster object behind the scenes, while on Linux and Mac OS X, it doesn't use a cluster object because it uses `mclapply` just as in the `doMC` package. I think that is convenient, but it can be a source of confusion.

parallel foreach loops produce mclapply error

Solution

Problem