Write out the C++ pseudocode of the K-Means Parallel algorithm from the slides(but in more details) so add loops, termination conditions, functions/procedures/methods and explain your data structures.

Then explain what you paralleized, and what decomposition you used(task,data, both and in what order)

The K-Means Clustering Method Given k, the k-means algorithm is implemented in four steps: Partition objects into k nonempty subsets - Compute seed points as the centroids of the clusters of the current partitioning (the centroid is the center, i.e., mean point, of the cluster) Assign each object to the cluster with the nearest seed point Go back to Step 2, stop when the assignment does not change