21โ€“25 May 2012
New York City, NY, USA
US/Eastern timezone

Session

Distributed Processing and Analysis on Grids and Clouds

03
21 May 2012, 13:30
New York City, NY, USA

New York City, NY, USA

Conveners

Distributed Processing and Analysis on Grids and Clouds

  • Oliver Gutsche (Fermi National Accelerator Lab. (US))

Distributed Processing and Analysis on Grids and Clouds

  • Johannes Elmsheuser (Ludwig-Maximilians-Univ. Muenchen (DE))

Distributed Processing and Analysis on Grids and Clouds

  • Philippe Canal (Fermi National Accelerator Lab. (US))

Distributed Processing and Analysis on Grids and Clouds

  • Philippe Canal (Fermi National Accelerator Lab. (US))

Distributed Processing and Analysis on Grids and Clouds

  • Oliver Gutsche (Fermi National Accelerator Lab. (US))

Distributed Processing and Analysis on Grids and Clouds

  • Johannes Elmsheuser (Ludwig-Maximilians-Univ. Muenchen (DE))

Distributed Processing and Analysis on Grids and Clouds

  • Oliver Gutsche (Fermi National Accelerator Lab. (US))

Presentation materials

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  1. Pablo Saiz (CERN)
    21/05/2012, 13:30
    Distributed Processing and Analysis on Grids and Clouds (track 3)
    Parallel
    AliEn is the GRID middleware used by the ALICE collaboration. It provides all the components that are needed to manage the distributed resources. AliEn is used for all the computing workflows of the experiment: Montecarlo production, data replication and reconstruction and organixed or chaotic user analysis. Moreover, AliEn is also being used by other experiments like PANDA and CBM. The...
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  2. Vincent Garonne (CERN)
    21/05/2012, 13:55
    Distributed Processing and Analysis on Grids and Clouds (track 3)
    Parallel
    The ATLAS collaboration has recorded almost 5PB of RAW data since the LHC started running at the end of 2009. Together with experimental data generated from RAW and complimentary simulation data, and accounting for data replicas on the grid, a total of 74TB is currently stored in the Worldwide LHC Computing Grid by ATLAS. All of this data is managed by the ATLAS Distributed Data Management...
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  3. Dr Stuart Wakefield (Imperial College London)
    21/05/2012, 14:20
    Distributed Processing and Analysis on Grids and Clouds (track 3)
    Parallel
    CMS has started the process of rolling out a new workload management system. This system is currently used for reprocessing and monte carlo production with tests under way using it for user analysis. It was decided to combine, as much as possible, the production/processing, analysis and T0 codebases so as to reduce duplicated functionality and make best use of limited developer...
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  4. Philippe Charpentier (CERN)
    21/05/2012, 14:45
    Distributed Processing and Analysis on Grids and Clouds (track 3)
    Parallel
    The LHCb Data Management System is based on the DIRAC Grid Community Solution. LHCbDirac provides extensions to the basic DMS such as a Bookkeeping System. Datasets are defined as sets of files corresponding to a given query in the Bookkeeping system. Datasets can be manipulated by CLI tools as well as by automatic transformations (removal, replication, processing). A dynamic handling of...
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  5. Dr Maria Girone (CERN)
    21/05/2012, 15:10
    Distributed Processing and Analysis on Grids and Clouds (track 3)
    Parallel
    After two years of LHC data taking, processing and analysis and with numerous changes in computing technology, a number of aspects of the experimentsโ€™ computing as well as WLCG deployment and operations need to evolve. As part of the activities of the Experiment Support group in CERNโ€™s IT department, and reinforced by effort from the EGI-InSPIRE project, we present work aimed at common...
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  6. Andrew John Washbrook (University of Edinburgh (GB))
    21/05/2012, 16:35
    Distributed Processing and Analysis on Grids and Clouds (track 3)
    Parallel
    AthenaMP is the multi-core implementation of the ATLAS software framework and allows the efficient sharing of memory pages between multiple threads of execution. This has now been validated for production and delivers a significant reduction on overall memory footprint with negligible CPU overhead. Before AthenaMP can be routinely run on the LHC Computing Grid, it must be determined how the...
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  7. Dr Jose Hernandez Calama (Centro de Investigaciones Energ. Medioambientales y Tecn. - (ES)
    21/05/2012, 17:00
    Distributed Processing and Analysis on Grids and Clouds (track 3)
    Parallel
    Commodity hardware is going many-core. We might soon not be able to satisfy the job memory needs per core in the current single-core processing model in High Energy Physics. In addition, an ever increasing number of independent and incoherent jobs running on the same physical hardware not sharing resources might significantly affect processing performance. It will be essential to effectively...
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  8. Anar Manafov (GSI - Helmholtzzentrum fur Schwerionenforschung GmbH (DE))
    21/05/2012, 17:25
    Distributed Processing and Analysis on Grids and Clouds (track 3)
    Parallel
    PROOF on Demand (PoD) is a tool-set, which dynamically sets up a PROOF cluster at a userโ€™s request on any resource management system (RMS). It provides a plug-in based system, in order to use different job submission front-ends. PoD is currently shipped with gLite, LSF, PBS (PBSPro/OpenPBS/Torque), Grid Engine (OGE/SGE), Condor, LoadLeveler, and SSH plug-ins. It makes it possible just within...
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  9. Luis Granado Cardoso (CERN)
    21/05/2012, 17:50
    Distributed Processing and Analysis on Grids and Clouds (track 3)
    Parallel
    LHCb is one of the 4 experiments at the LHC accelerator at CERN. LHCb has approximately 1600 (8 cores) PCs for processing the High Level Trigger (HLT) during physics data acquisition. During periods when data acquisition is not required or the resources needed for data acquisition are reduced, like accelerator Machine Development (MD) periods or technical shutdowns, most of these PCs are idle...
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  10. Artem Harutyunyan (CERN)
    22/05/2012, 13:30
    Distributed Processing and Analysis on Grids and Clouds (track 3)
    Parallel
    CernVM Co-Pilot is a framework for instantiating an ad-hoc computing infrastructure on top of distributed computing resources. Such resources include commercial computing clouds (e.g. Amazon EC2), scientific computing clouds (e.g. CERN lxcloud), as well as the machines of users participating in volunteer computing projects (e.g. BOINC). The framework consists of components that communicate...
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  11. Victor Manuel Fernandez Albor (Universidade de Santiago de Compostela (ES)), Victor Mendez Munoz (Port d'Informaciรณ Cientรญfica (PIC))
    22/05/2012, 13:55
    Distributed Processing and Analysis on Grids and Clouds (track 3)
    Parallel
    The increasing availability of cloud resources is making the scientific community to consider a choice between Grid and Cloud. The DIRAC framework for distributed computing is an easy way to obtain resources from both systems. In this paper we explain the integration of DIRAC with a two Open-source Cloud Managers, OpenNebula and CloudStack. They are computing tools to manage the...
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  12. Fernando Harald Barreiro Megino (CERN IT ES)
    22/05/2012, 14:20
    Distributed Processing and Analysis on Grids and Clouds (track 3)
    Parallel
    The ATLAS Computing Model was designed around the concepts of grid computing; since the start of data-taking, this model has proven very successful in the federated operation of more than one hundred Worldwide LHC Computing Grid (WLCG) sites for offline data distribution, storage, processing and analysis. However, new paradigms in computing, namely virtualization and cloud computing, present...
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  13. Oliver Oberst (KIT - Karlsruhe Institute of Technology (DE))
    22/05/2012, 14:45
    Distributed Processing and Analysis on Grids and Clouds (track 3)
    Parallel
    The specific requirements concerning the software environment within the HEP community constrain the choice of resource providers for the outsourcing of computing infrastructure. The use of virtualization in HPC clusters and in the context of cloud resources is therefore a subject of recent developments in scientific computing. The dynamic virtualization of worker nodes in common batch...
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  14. Mr Alessandro Italiano (INFN-CNAF), Dr Giacinto Donvito (INFN-Bari)
    22/05/2012, 15:10
    Distributed Processing and Analysis on Grids and Clouds (track 3)
    Parallel
    In this paper we present the latest developments introduced in the WNoDeS framework (http://web.infn.it/wnodes); we will in particular describe inter-cloud connectivity, support for multiple batch systems, and coexistence of virtual and real environments on a single hardware. Specific effort has been dedicated to the work needed to deploy a "multi-sites" WNoDeS installation. The goal is to...
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  15. Thomas Kuhr (KIT - Karlsruhe Institute of Technology (DE))
    22/05/2012, 16:35
    Distributed Processing and Analysis on Grids and Clouds (track 3)
    Parallel
    The Belle II experiment, a next-generation B factory experiment at KEK, is expected to record a two orders of magnitude larger data volume than its predecessor, the Belle experiment. The data size and rate are comparable to or more than the ones of LHC experiments and requires to change the computing model from the Belle way, where basically all computing resources were provided by KEK, to a...
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  16. Daniel Colin Van Der Ster (CERN)
    22/05/2012, 16:35
    Distributed Processing and Analysis on Grids and Clouds (track 3)
    Parallel
    Frequent validation and stress testing of the network, storage and CPU resources of a grid site is essential to achieve high performance and reliability. HammerCloud was previously introduced with the goals of enabling VO- and site-administrators to run such tests in an automated or on-demand manner. The ATLAS, CMS and LHCb experiments have all developed VO plugins for the service and have...
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  17. Dmitry Ozerov (Deutsches Elektronen-Synchrotron (DE)), Dr Patrick Fuhrmann (DESY)
    22/05/2012, 17:00
    Distributed Processing and Analysis on Grids and Clouds (track 3)
    Parallel
    One of the most crucial requirement for online storage is the fast and efficient access to data. Although smart client side caching often compensates for discomforts like latencies and server disk congestion, spinning disks, with their limited ability to serve multi stream random access patterns, seem to be the cause of most of the observed inefficiencies. With the appearance of the...
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  18. Mrs Jianlin Zhu (Central China Normal University (CN))
    22/05/2012, 17:00
    Distributed Processing and Analysis on Grids and Clouds (track 3)
    Parallel
    A Grid is a geographically distributed environment with autonomous sites that share resources collaboratively. In this context, the main issue within a Grid is encouraging site to site interactions, increasing the trust, confidence and reliability of the sites to share resources. To achieve this, the trust concept is vital component in every service transaction, and needs to be applied in the...
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  19. Dr Stefan Lueders (CERN)
    22/05/2012, 17:25
    Distributed Processing and Analysis on Grids and Clouds (track 3)
    Parallel
    Access protection is one of the cornerstones of security. The rule of least-privilege demands that any access to computer resources like computing services or web applications is restricted in such a way that only users with a need-to can access those resources. Usually this is done when authenticating the user asking her for something she knows, e.g. a (public) username and secret password....
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  20. Parag Mhashilkar (Fermi National Accelerator Laboratory)
    22/05/2012, 17:25
    Distributed Processing and Analysis on Grids and Clouds (track 3)
    Parallel
    Grid computing has enabled scientific communities to effectively share computing resources distributed over many independent sites. Several such communities, or Virtual Organizations (VO), in the Open Science Grid and the European Grid Infrastructure use the glideinWMS system to run complex application work-flows. GlideinWMS is a pilot-based workload management system (WMS) that creates on...
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  21. Iwona Sakrejda, Jeff Porter (Lawrence Berkeley National Lab. (US))
    22/05/2012, 17:50
    Distributed Processing and Analysis on Grids and Clouds (track 3)
    Parallel
    The ALICE Grid infrastructure is based on AliEn, a lightweight open source framework built on Web Services and a Distributed Agent Model in which job agents are submitted onto a grid site to prepare the environment and pull work from a central task queue located at CERN. In the standard configuration, each ALICE grid site supports an ALICE-specific VO box as a single point of contact between...
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  22. Dr Andrea Sciaba (CERN), Lothar A.T. Bauerdick (Fermi National Accelerator Lab. (US))
    22/05/2012, 17:50
    Distributed Processing and Analysis on Grids and Clouds (track 3)
    Parallel
    The operation of the CMS computing system requires a complex monitoring system to cover all its aspects: central services, databases, the distributed computing infrastructure, production and analysis workflows, the global overview of the CMS computing activities and the related historical information. Several tools are available to provide this information, developed both inside and outside of...
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  23. Tony Cass (CERN)
    24/05/2012, 13:30
    Distributed Processing and Analysis on Grids and Clouds (track 3)
    Parallel
    The HEPiX Virtualisation Working Group has sponsored the development of policies and technologies that permit Grid sites to safely instantiate remotely generated virtual machine images confident in the knowledge that they will be able to meet their obligations, most notably in terms of guaranteeing the accountability and traceability of any Grid Job activity at their site. We will present...
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  24. Jeff Templon (NIKHEF (NL))
    24/05/2012, 13:55
    Distributed Processing and Analysis on Grids and Clouds (track 3)
    Parallel
    This contribution describes a prototype grid proxy cache system developed at Nikhef, motivated by a desire to construct the first building block of a future https-based Content Delivery Network for multiple-VO grid infrastructures. Two goals drove the project: firstly to provide a "native view" of the grid for desktop-type users, and secondly to improve performance for physics-analysis type...
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  25. Dr Armando Fella (INFN Pisa)
    24/05/2012, 14:20
    Distributed Processing and Analysis on Grids and Clouds (track 3)
    Parallel
    The SuperB asymmetric energy e+e- collider and detector to be built at the newly founded Nicola Cabibbo Lab will provide a uniquely sensitive probe of New Physics in the flavor sector of the Standard Model. Studying minute effects in the heavy quark and heavy lepton sectors requires a data sample of 75 ab-1 and a luminosity target of 10^36 cm-2 s-1. The increasing network performance also...
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  26. Dr Balazs Konya (Lund University (SE))
    24/05/2012, 14:45
    Distributed Processing and Analysis on Grids and Clouds (track 3)
    Parallel
    Scientific research communities have benefited recently from the increasing availability of computing and data infrastructures with unprecedented capabilities for large scale distributed initiatives. These infrastructures are largely defined and enabled by the middleware they deploy. One of the major issues in the current usage of research infrastructures is the need to use similar but often...
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  27. Mrs Ruth Pordes (Fermi National Accelerator Lab. (US))
    24/05/2012, 15:10
    Distributed Processing and Analysis on Grids and Clouds (track 3)
    Parallel
    As it enters adolescence the Open Science Grid (OSG) is bringing a maturing fabric of Distributed High Throughput Computing (DHTC) services that supports an expanding HEP community to an increasingly diverse spectrum of domain scientists. Working closely with researchers on campuses throughout the US and in collaboration with national cyberinfrastructure initiatives, we transform their...
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  28. Paul Millar (Deutsches Elektronen-Synchrotron (DE))
    24/05/2012, 16:35
    Distributed Processing and Analysis on Grids and Clouds (track 3)
    Parallel
    For over a decade, dCache has been synonymous with large-capacity, fault-tolerant storage using commodity hardware that supports seamless data migration to and from tape. Over that time, it has satisfied the requirements of various demanding scientific user communities to store their data, transfer it between sites and fast, site-local access. When the dCache project started, the focus was...
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  29. Mr Zsolt Molnรกr (CERN)
    24/05/2012, 17:00
    Distributed Processing and Analysis on Grids and Clouds (track 3)
    Parallel
    LHC experiments at CERN and worldwide utilize WLCG resources and middleware components to perform distributed computing tasks. One of the most important tasks is reliable file replication. It is a complex problem, suffering from transfer failures, disconnections, transfer duplication, server and network overload, differences in storage systems, etc. To address these problems, EMI and gLite...
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  30. Dr Domenico Giordano (CERN), Fernando Harald Barreiro Megino (Universidad Autonoma de Madrid (ES))
    24/05/2012, 17:25
    Distributed Processing and Analysis on Grids and Clouds (track 3)
    Parallel
    During the first two years of data taking, the CMS experiment has collected over 20 PetaBytes of data and processed and analyzed it on the distributed, multi-tiered computing infrastructure on the WorldWide LHC Computing Grid. Given the increasing data volume that has to be stored and efficiently analyzed, it is a challenge for several LHC experiments to optimize and automate the data...
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  31. Tadashi Maeno (Brookhaven National Laboratory (US))
    24/05/2012, 17:50
    Distributed Processing and Analysis on Grids and Clouds (track 3)
    Parallel
    The PanDA Production and Distributed Analysis System is the ATLAS workload management system for processing user analysis, group analysis and production jobs. In 2011 more than 1400 users have submitted jobs through PanDA to the ATLAS grid infrastructure. The system processes more than 2 million analysis jobs per week. Analysis jobs are routed to sites based on the availability of relevant...
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