These are being exercised and developed in Data Challenges of increasing size and complexity

1. ATLAS Applications Frontier physics on the Grid T.Doherty1, S.George2, K.Harrison2, R.W.L.Jones3, D.Liko4, C.Nicholson1, A.Soroko6, G.Rybkine2,C.L.Tan7 1University of Glasgow, 2RHUL, 3University of Cambridge, 4Lancaster University, 5CERN, 6University of Oxford, 7University of Birmingham ATLAS is a general-purpose particle physics experiment which will study topics including the origin of mass, the processes that allowed an excess of matter over antimatter in the universe, evidence for Supersymmetry and other new physics, including even micro black hole production! The experiment is being constructed by some 1600 scientists in ~150 institutes in 6 continents. The experiment will be located at the 27km circumference Large Hadron Collider at CERN in Geneva. Despite highly efficient filters acting on the raw data read by the detector, the `good’ events will still correspond to several Petabytes of data per year, which will require millions of SpecInt2k to process and analyse. Even now, to design the detector and to understand the physics, many millions of simulated events also have to be produced. A simulated Higgs boson decay in the ATLAS detector Only a Grid can satisfy our requirements. ATLAS is a global collaboration with Grid testbeds already deployed worldwide. While building on generic middleware, we are required to develop several components, which may be reusable. We are also required to build tools that can run tasks in a coherent way across several grid deployments These are being exercised and developed in Data Challenges of increasing size and complexity These have now been performed using three Grid deployments in 85 sites and six continents. They are a proof of principle for Grid-based production. We are merging these activities with a series of Service Challenges to establish the required system.

2. GANGA Grappa GUI GRID Services ? Histograms Monitoring Results JobOptions Virtual Data Algorithms Athena/ GAUDIApplication ? ATLAS Applications Frontier physics on the Grid T.Doherty1, S.George2, K.Harrison2, R.W.L.Jones3, D.Liko4, C.Nicholson1, A.Soroko6, G.Rybkine2,C.L.Tan7 1University of Glasgow, 2RHUL, 3University of Cambridge, 4Lancaster University, 5CERN, 6University of Oxford, 7University of Birmingham The GANGA project provides an interface between the user, the Grid Middleware and the experimental software framework. It is being developed jointly with the LHCb experiment, and as it is using component technologies will allow reuse elsewhere The GANGA frameworks provides command line and graphical interfaces; job preparation templates and tools, including tools to locate datasets; job splitting; and back-ends into various systems including Fork, LSF, PBS, Condor, LCG, gLite, PANDA and Condor systems. The ATLAS Distributed Analysis system supports distributed users, data and processing. This includes Monte Carlo production, data reconstruction and the extraction of summary data. A prototype system based with a GANGA user interface is being rolled-out The large number of Grid sites requires automated and scalable Installation Tools. Coherent rpms and tar files are created from CMT, exposing the package dependencies as PACMAN cache files. PACMAN can pull or push complete installations to remote sites. Scripts have been developed making the process semi-automatic. it is important to note that these tools not only install code but also establish the working environment. ATLAS UK integrates the EGEE/LCG middleware. The most recent data challenge ran over 570000 production jobs in 84 sites using grid tools. Even analysis can now be run this way, and we are now in urgent need of monitoring and accounting tools to manage production and individual users on the same Grid. • Job submission rates are being improved to avoid bottlenecks • The production system has been redesigned to increase performance • A new data handling system has been written and is being rolled-out across the sites. This will be essential for handling the expected real data volumes. An essential element in the Distributed Analysis system is the access metadata describing the event. GridPP is providing effort in the metadata handling for the ATLAS data in two ways. First, it works on the production metadata tool, AMI, and provides the plug-in that allows GANGA to browse AMI. Secondly, we are working on the TAG data. This is contains a record for each event in a sample, with simple descriptive keys that allow physics and trigger signatures to be selected, and also contains information on the file in which the event occurs and a pointer to the event within the file. Preliminary studies have show that this can give allow the fast selection and access for many datasets that are relatively sparsely distributed within the data files