Sequential and parallel gradient descent algorithms in Java

In my portfolio, I have a project where I implemented the gradient descent method in Java to search for optimal values. This method is used to find the minimum (or maximum) of a function with several parameters. I also implemented its parallel version to speed up computations.

During development, I tested the algorithm on a large amount of data to ensure its efficiency and correctness. I also measured the execution time of the algorithms as the computational complexity increased to assess their speed.

For the parallel version of the algorithm, I investigated the acceleration as the amount of data for computations increased. I found that the acceleration is at least 1.2, indicating the efficiency of the parallel implementation. I also studied the impact of parameters of the parallel algorithm on the achieved acceleration, including the number of subtasks and others.

All results, including algorithm descriptions in pseudocode, have been documented in a docx file for further convenience of use and analysis.