Distributed Offline Data Reconstruction in BaBar

• Main Authors: Pulliam, Teela, Elmer, Peter, Dorigo, Alvise
• Format: Journal Article
• Language: English
• Published: 13.06.2003
• Subjects: Computer Science - Distributed, Parallel, and Cluster Computing
• DOI: 10.48550/arxiv.cs/0306069

The BaBar experiment at SLAC is in its fourth year of running. The data processing system has been continuously evolving to meet the challenges of higher luminosity running and the increasing bulk of data to re-process each year. To meet these goals a two-pass processing architecture has been adopted, where 'rolling calibrations' are quickly calculated on a small fraction of the events in the first pass and the bulk data reconstruction done in the second. This allows for quick detector feedback in the first pass and allows for the parallelization of the second pass over two or more separate farms. This two-pass system allows also for distribution of processing farms off-site. The first such site has been setup at INFN Padova. The challenges met here were many. The software was ported to a full Linux-based, commodity hardware system. The raw dataset, 90 TB, was imported from SLAC utilizing a 155 Mbps network link. A system for quality control and export of the processed data back to SLAC was developed. Between SLAC and Padova we are currently running three pass-one farms, with 32 CPUs each, and nine pass-two farms with 64 to 80 CPUs each. The pass-two farms can process between 2 and 4 million events per day. Details about the implementation and performance of the system will be presented.