What are the tools to speed up the running time of machine learning algorithms? I know Spark as the fastest tools for Data processing, but not sure if it would be useful to speed up the running time of ML algorithms. For example, my ML models to be built needs about 24h when I run on my machine on RStudio. I am thinking another tool to reduce this expensive time-cost.

I am talking mainly about the distributed computing tools like spark regardless of the type of algorithm and the size of my data.

Any help is appreciated !
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.