What are the tools to speed up the running time of machine learning algorithms?
It all depends on the model you are running and your chosen sample sizing. 

The sample sizing is obvious, so I won't go into that (or at least it should be obvious to you vis-a-vis how R handles data). But the chosen model can have an effect. For example, neural networks are one of the rare problems in computing that you actually can throw more hardware at to improve. That's going to be a while different experience than, say, gradient boosting or something along those lines.