In Homework Assignment 8 we wrote a program that would process a data file, converting the raw data to true stress and strain, and compute the toughness. In this assignment, we will make the integration (i.e. toughness computation) a parallel task.
Your assignment is to complete the Julia module assignment12.jl. Specifically, you must complete the functions partition_data(strain::AbstractArray, stress::AbstractArray, comm::MPI.Comm) and compute_toughness_parallel(filename::String, comm::MPI.Comm).
In partition_data(), the strain/stress arguments are Arrays that contain the entire stress and strain data only on the root processor (i.e. rank 0) and comm is an MPI.COMM_WORLD object. This function should distribute the strain/stress data appropriately and as evenly as possible to all available processors.
compute_toughness_parallel() is already partially implemented, but must be completed with a parallel reduction summation operation to the root processor. This function should return the toughness value after reduction. You should use the implemented trapz() function to perform the integration on each processor before reduction.
When the script is executed with the following command in the Terminal application from the root of the assignment repository
mpiexecjl --project=. -np 2 julia src/assignment12.jl 'data/data.csv'it will print the toughness value to the screen. Your code should be parallel consistent, i.e. it should produce the exact same answer independent of the number of processors you specify.
If you haven't already done so, please run the following commands from the Julia REPL one time before starting your assignment to install the project aware version of mpiexec.
using MPI; MPI.install_mpiexecjl()To see if your answer is correct, run the following command at the Terminal command line from the repository's root directory
julia --project=. -e "using Pkg; Pkg.test()"the tests will run and report if passing or failing.