title: In mlr and parallelMap it possible to parallelize multiple levels? For example mlr.tuneParams and mlr.benchmark
body: <p>I'm running a mlr benchmark with multiple learners (around 15 different learners) with nested resampling using the irace tuning control.
  My question is: is it possible to run two parallelization levels on parallelMap?</p>
  
  <p>If I use the mlr.benchmark level, the faster learners end firsts and only the more computational demanding learners remain running, a single thread for each. So end up with 4 maybe 5 threads running.</p>
  
  <p>If I use the mlr.tuneParams level, the irace tuning control spawns 6 threads evaluates all of them and then after all of them finish, it creates 6 others. I know that this method is sequential in nature.</p>
  
  <p>My point is either way the CPU cores are not fully used.
  For example if a CPU has 12 cores I could run two learners at same time with each learner using 6 cores for tuning.</p>
  
  <p>Right now I'm doing this manually: I create multiple R sessions and run them separately.</p>
  
  <p>Thanks!</p>