Enabling the ATLAS Experiment at the LHC for High Performance Computing

In this thesis, I studied the feasibility of running computer data analysis programs from the Worldwide LHC Computing Grid, in particular large-scale simulations of the ATLAS experiment at the CERN LHC, on current general purpose High Performance Computing (HPC) systems. An approach for integrating HPC systems into the Grid is proposed, which has been implemented and tested on the "Todi" HPC machine at the Swiss National Supercomputing Centre (CSCS). Over the course of the test, more than 500000 CPU-hours of processing time have been provided to ATLAS, which is roughly equivalent to the combined computing power of the two ATLAS clusters at the University of Bern. This showed that current HPC systems can be used to efficiently run large-scale simulations of the ATLAS detector and of the detected physics processes. As a first conclusion of my work, one can argue that, in perspective, running large-scale tasks on a few large machines might be more cost-effective than running on relatively small dedicated computing clusters. The second part of the thesis work covers a study of the discovery potential for supersymmetry (SUSY) by studying ATLAS events with one lepton, two b-jets and missing transverse momentum in the final state. By using flat-random distributed pMSSM models, I identified some models which could possibly lead to the discovery of SUSY by this specific channel.