The LHCb experiment is dedicated to precision measurements of CP violation and rare decays of B hadrons at the Large Hadron Collider (LHC) at CERN (Geneva). The initial configuration and expected performance of the detector and associated systems, as established by test beam measurements and simulation studies, is described.

An overview of the electromagnetic (EM) physics of the Geant4 toolkit is presented. Two sets of EM models are available: the "Standard" initially focused on high energy physics (HEP) while the "Low-energy" was developed for medical, space and other applications. The "Standard" models provide a faster computation but are less accurate for keV energies, the "Low-energy" models are more CPU time consuming. A common interface to EM physics models has been developed allowing a natural combination of ultra-relativistic, relativistic and low-energy models for the same run providing both precision and CPU performance. Due to this migration additional capabilities become available. The new developments include relativistic models for bremsstrahlung and e+e-pair production, models of multiple and single scattering, hadron/ion ionization, microdosimetry for very low energies and also improvements in existing Geant4 models. In parallel, validation suites and benchmarks have been intensively developed.

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In this paper, we present the computational task-management tool Ganga, which allows for the specification, submission, bookkeeping and post-processing of computational tasks on a wide set of distributed resources. Ganga has been developed to solve a problem increasingly common in scientific projects, which is that researchers must regularly switch between different processing systems, each with its own command set, to complete their computational tasks. Ganga provides a homogeneous environment for processing data on heterogeneous resources. We give examples from High Energy Physics, demonstrating how an analysis can be developed on a local system and then transparently moved to a Grid system for processing of all available data. Ganga has an API that can be used via an interactive interface, in scripts, or through a GUI. Specific knowledge about types of tasks or computational resources is provided at run-time through a plugin system, making new developments easy to integrate. We give an overview of the Ganga architecture, give examples of current use, and demonstrate how Ganga can be used in many different areas of science.

Abstract. Grids are facing the challenge of seamless integration of the grid power into everyday use. One critical component for this integration is responsiveness, the capacity to support on-demand computing and interactivity. Grid scheduling is involved at two levels in order to provide responsiveness: the policy level and the implementation level. The main contributions of this paper are as follows. First, we present a detailed analysis of the performance of the EGEE grid with respect to responsiveness. Second, we examine two user-level schedulers located between the general scheduling layer and the application layer. These are the DIANE (DIstributed ANalysis Environment) framework, a general-purpose overlay system, and a specialized, embedded scheduler for gPTM3D, an interactive medical image analysis application. Finally, we define and demonstrate a virtualization scheme, which achieves guaranteed turnaround time, schedulability analysis, and provides the basis for differentiated services. Both methods target a brokering-based system organized as a federation of batch-scheduled clusters, and an EGEE implementation is described.