A)Write out pseudocode in C++ of the parallel algorithm (this means more detail than some of the slides) -- so, loops, termination conditions, functions/procedures/methods (objects or no objects). Explain what are your data structures.

B) Explain what you parallelized, and what decomposition(s) you used (task, data, both (and in what order).

C)Provide an example -- Assume you have 4 cores and 4 threads per core.

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 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