High-statistics and GPU Accelerated Data Analysis

We present methods to perform high statistics data analyses to investigate fundamental neutrino properties in large volume neutrino detectors, fast and with modest computational resources. The introduced measures are threefold: speeding up computations using graphics processors, evaluating the underlying physics processes on a grid instead of treating every event individually and lastly applying smoothing methods to quantities obtained from Monte Carlo simulations. We show that with our method we can get reliable analysis results using significantly less simulation than what is usually needed, and that the timing to run an analysis with our method is independent of sample size. (paper)