The BaBar experiment has been taking data since 1999, investigating the violation of charge and parity (CP) symmetry in the field of High Energy Physics. Event simulation is an intensive computing task, due to the complexity of the algorithm based on the Monte Carlo method implemented using the GEANT engine. The simulation input data are stored in ROOT format, they are classified into two categories: conditions data for describing the detector status when data are recorded, and background triggers data for including the noise signal necessary to obtain a realistic simulation. In order to satisfy these requirements, in the traditional BaBar computing model events are distributed over several sites involved in the collaboration where each site manager centrally manages a private farm dedicated to simulation production. The new grid approach applied to the BaBar production framework is discussed along with the schema adopted for data deployment
via Xrootd/Scalla servers, including data management using grid middleware on distributed storage facilities spread over the INFN-GRID network. A comparison between the two models is provided, describing also the custom applications
developed for performing the whole production task on the grid and showing the results achieved
