Modules to Teach Parallel and Distributed Computing Using MPI for Python and Disco

The ability to design effective solutions using parallel processing should be a required competency for every computing student. However, teaching parallel concepts is sometimes challenging and costly, specially at early stages of a computer science degree. For such reasons we present a set of modules to teach parallel computing paradigms using as examples problems that are computationally intensive, but easy to understand and can be easily implemented using the Python parallelization libraries MPI for Python and Disco.