2014

Parallelization of maximum likelihood fits on CPU and GPU: Algorithms and Technologies

by Alfio Lazzaro (CERN)

Europe/Rome
Aula Milla (INFN - Padova)

Aula Milla

INFN - Padova

Description

Data analyses based on maximum likelihood fits are commonly used for fitting statistical models to data samples. Large data samples and complex likelihood functions models can be very time-consuming tasks. Therefore, it becomes particularly important to speed-up the evaluation of the likelihood functions. In this presentation Alfio will present an algorithm which benefits from data vectorization and parallelization on CPU and GPU. Thereafter I will discuss the implementation technologies for porting the application on both devices.

Organized by

Franco Simonetto