Simple TBB-based parallelization for the cascade. Small improvements with little effort.

I planned on training DPMs with quite many components and I noticed that the cascade code was not parallelized so I thought that I would throw in a few minutes for a simple parallelisation. It is in no way optimal, but rather a "small improvement with little effort" thing. Anyways, someone else might find it useful too so that's why I created this pull request.

Parallelizes over scales by default, but can parallelize over components (currently via an ifdef flag in cascade.cc). Gives about 50% speedup on a dual-core (4 virtual cores) processor for two of the models in the demo_cascade example, but only 10% for the last one. Haven't tried it on a machine with more cores yet, but I expect the that the model complexity needs to be higher (e.g. more components) for bigger gains.