In this repository is a project I did to utilize parallelization to quicken the process of multipliying large square matrices. This process followed the below laid out steps to achieve the process:

1. Modifying a preexisting tuple communication space to better service arrays and matrices of double values
2. Building a client program, which sends a copy of the original matrix and smaller copies to mulitple worker programs
3. Building a worker program, which intakes the original matrix and smaller copies to carry out a faster multiplication
4. Comparing the parallel results to that of a sequential (normal) matrix multiplication
5. Writing a python script to gather and analyze data on the effects of the smaller matrix size on speed of the parallel multiplication