Jeremy Bejarano

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Due to current data collection technology, our ability to gather data has surpassed our ability to analyze it. In particular, k-means, one of the simplest and fastest clustering algorithms, is ill-equipped to handle extremely large datasets on even the most powerful machines. Our new algorithm uses a sample from a dataset to decrease run-time by reducing(More)
In this project I have two goals: (1) demonstrate the power and scalability of the distributed memory multiprocessing in solving problems in economics and (2) demonstrated how the distributed memory model requires a modified approach to algorithm design. In particular, I will show how to implement a parallel numerical solution to a simple continuous-time(More)