lue_scalability for scalability experiments

One of the goals for developing LUE is to research scalable algorithms for spatial analysis. A LUE computation should make good use of additional hardware, to make computations finish faster, or to make larger computations feasible.

Scalability experiments involve executing a certain computation many times, while varying the amount of hardware and/or data, and recording the latencies involved. Afterwards, all recorded latencies have to be aggregated, statistics computed, and further postprocessed to end up with scalability plots showing the efficiencies.

The example below shows the results of a strong scalability experiment of a LUE version of Conway's Game of Life. The second plot shows that using 12 CPU cores instead of one, speeds up the model almost 10 times.

To make it convenient to perform scalability experiments, we have developed the lue_scalability.py command. This command removes much of the administrative and practical burdens of performing such experiments. For more information, see the manual about scalability.