2014
Parallelization of maximum likelihood fits on CPU and GPU: Algorithms and Technologies
by
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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.
Organised by
Franco Simonetto