Alternative chunking

We will now slightly modify the application of chunking in the previous exercise. Instead of a task corresponding to one row, each task will now process 40 rows, which corresponds to 5 tasks in total. You will then compare the shape of the returned object to the one you created in the last exercise. Recall that in both cases you are generating 10 trajectories per each of the 200 rows, which is 2000 trajectories in total, each 15 time points long.

The package parallel and cluster object cl with 4 workers along with all dependent functions and dataset have been exported to the workers. The object res returned by clusterApply() in the previous exercise is also in your workspace, now called res_prev.

Use splitIndices() to split indices of the rows of the ar1est dataset into 5 chunks.
Run ar1_multiple_blocks_of_trajectories() in parallel as in the previous exercise, but passing the split indices as the x argument.
Compare the shape of res and res_prev by printing the str()ucture of each. Why are they different?

Exercise

Alternative chunking

Instructions