Parallel Computing Studies for the Alignment of the ATLAS Silicon Tracker

The silicon system of the ATLAS Inner Detector consists of about 6000 modules in its Semiconductor Tracker and Pixel Detector. Therefore, the offline global fit alignment algorithm has to deal with solving a problem of up to 36000 degrees of freedom.32-bit single-CPU platforms were foreseen to be unable to handle such large-size operations needed by the algorithm. The proposed solution is to utilize a Beowulfcluster with a 64-bit architecture. We have performed the initial studies on performance of such a system using SCARF RAL cluster, compared with earlier predictions, obtained the first promising results on parallel computing for the ATLAS tracker alignment. After a brief introduction with the motivation, we will describe the hardware and software used and present the results of the studies, using also examples from the ATLAS simulated data.