Add threading-based backend to joblib.Parallel

This is very useful when calling GIL-releasing compiled extensions as it removes any memory copy and inte-rprocess communication overhead (pickling) induced by the default multiprocessing backend.

I tested it on the bench_covertype with ExtraTrees of scikit-learn with 10 cores. It runs slightly faster (19s instead of 23s with the current master) and furthermore does not do any memory copy.