Performance evaluation of ML algorithms

[wynot12]

We've implemented some ML algorithms in #2.

As a starting point of #4, we have to do some performance test on ML algorithms.
It would be better to start with K-means that we think it is the most sophisticated implementation among our algorithm.

Measuring factors:

• Running time per iteration
• Training data set vs running time
• Node number vs computation,communication time
• Elastis MPI's reconfiguration time (this would soon include Split/Merge system primitives from Step 2 - Implement system primitives #2)

Measuring factors can be updated anytime.

We can utilize the newly built logging system from reef's main branch.
apache/reef#8

[wynot12]

Before this issue, we are gonna build dolphin runtime first.

This issue is temporarily paused.