# \texttt{GooStats}: A GPU-based framework for multi-variate analysis in particle physics

## TL;DR

GooStats is a GPU-accelerated software framework designed for efficient multi-variate statistical analysis in particle physics, leveraging parallel processing to significantly enhance performance and enable new analytical possibilities.

## Contribution

It introduces a flexible, GPU-based analysis framework built on CERN ROOT, MINUIT, and GooFit, with demonstrated performance improvements and practical applications.

## Key findings

- Significant performance boost using GPU parallelization.
- Successful application to complex statistical problems.
- Framework's flexibility facilitates diverse analyses.

## Abstract

\texttt{GooStats} is a software framework that provides a flexible environment and common tools to implement multi-variate statistical analysis. The framework is built upon the \texttt{CERN ROOT}, \texttt{MINUIT} and \texttt{GooFit} packages. Running a multi-variate analysis in parallel on graphics processing units yields a huge boost in performance and opens new possibilities. The design and benchmark of \texttt{GooStats} are presented in this article along with illustration of its application to statistical problems.