Darwinian gradient descent

Large optimization problems of many variables can be difficult to solve and very computationally intensive. To dedicate greater computer resources to the problem, this thesis proposes a way to distribute the problem over many different computers using the Berkeley Open Infrastructure for Network Computing (BOINC), an open-source platform where people can volunteer their personal computer to work on various problems while their computer is idle. My program runs a genetic version of a gradient descent algorithm, including conjugate gradient methods, that runs the algorithm in parallel on many computers at once to find a solution faster and to avoid some common problems of gradient descent, such as getting trapped in local minima.