E McIntosh

LHC@Home: a BOINC-based volunteer computing infrastructure for physics studies at CERN

Abstract The LHC@Home BOINC project has provided computing capacity for numerical simulations to researchers at CERN since 2004, and has since 2011 been expanded with a wider range of applications. The traditional CERN accelerator physics simulation code SixTrack enjoys continuing volunteers support, and thanks to virtualisation a number of applications from the LHC experiment collaborations and particle theory groups have joined the consolidated LHC@Home BOINC project. This paper addresses the challenges related to traditional and virtualized applications in the BOINC environment, and how volunteer computing has been integrated into the overall computing strategy of the laboratory through the consolidated LHC@Home service. Thanks to the computing power provided by volunteers joining LHC@Home, numerous accelerator beam physics studies have been carried out, yielding an improved understanding of charged particle dynamics in the CERN Large Hadron Collider (LHC) and its future upgrades. The main results are highlighted in this paper.

Parallel algorithms for the analysis of nonlinear betatronic motion

The dynamic aperture represents the volume in phase-space in which stable motion occurs. This is a key parameter to define the performance of a circular machine. The computation of this volume requires CPU-intense numerical simulations. In this paper, some original parallel algorithms to speed-up the evaluation of the dynamic aperture are presented. A detailed analysis of different algorithms is carried out. Furthermore, the dependence of the CPU-time on the phase-space parameters as well as the load balancing of the proposed techniques are studied.

Development of Parallel Codes for the Study of Nonlinear Beam Dynamics

We consider the nonlinear transverse motion in a circular particle accelerator. A key parameter for accelerator performance is the so-called dynamic aperture. This quantity is defined as the volume in phase space of the stable initial conditions. The accurate numerical computation of such a volume is very CPU-time consuming. In this paper we present some original parallel algorithms to speed up the evaluation of the dynamic aperture. A detailed analysis of different algorithms implemented is carried out. Furthermore, we studied the dependence of the CPU-time on the phase space parameters as well as the load balancing of the proposed techniques.