WorldWideScience

Sample records for atlas computers

  1. ATLAS Distributed Computing Automation

    CERN Document Server

    Schovancova, J; The ATLAS collaboration; Borrego, C; Campana, S; Di Girolamo, A; Elmsheuser, J; Hejbal, J; Kouba, T; Legger, F; Magradze, E; Medrano Llamas, R; Negri, G; Rinaldi, L; Sciacca, G; Serfon, C; Van Der Ster, D C

    2012-01-01

    The ATLAS Experiment benefits from computing resources distributed worldwide at more than 100 WLCG sites. The ATLAS Grid sites provide over 100k CPU job slots, over 100 PB of storage space on disk or tape. Monitoring of status of such a complex infrastructure is essential. The ATLAS Grid infrastructure is monitored 24/7 by two teams of shifters distributed world-wide, by the ATLAS Distributed Computing experts, and by site administrators. In this paper we summarize automation efforts performed within the ATLAS Distributed Computing team in order to reduce manpower costs and improve the reliability of the system. Different aspects of the automation process are described: from the ATLAS Grid site topology provided by the ATLAS Grid Information System, via automatic site testing by the HammerCloud, to automatic exclusion from production or analysis activities.

  2. ATLAS Distributed Computing

    CERN Document Server

    Schovancova, J; The ATLAS collaboration

    2011-01-01

    The poster details the different aspects of the ATLAS Distributed Computing experience after the first year of LHC data taking. We describe the performance of the ATLAS distributed computing system and the lessons learned during the 2010 run, pointing out parts of the system which were in a good shape, and also spotting areas which required improvements. Improvements ranged from hardware upgrade on the ATLAS Tier-0 computing pools to improve data distribution rates, tuning of FTS channels between CERN and Tier-1s, and studying data access patterns for Grid analysis to improve the global processing rate. We show recent software development driven by operational needs with emphasis on data management and job execution in the ATLAS production system.

  3. New ATLAS Software & Computing Organization

    CERN Multimedia

    Barberis, D

    Following the election by the ATLAS Collaboration Board of Dario Barberis (Genoa University/INFN) as Computing Coordinator and David Quarrie (LBNL) as Software Project Leader, it was considered necessary to modify the organization of the ATLAS Software & Computing ("S&C") project. The new organization is based upon the following principles: separation of the responsibilities for computing management from those of software development, with the appointment of a Computing Coordinator and a Software Project Leader who are both members of the Executive Board; hierarchical structure of responsibilities and reporting lines; coordination at all levels between TDAQ, S&C and Physics working groups; integration of the subdetector software development groups with the central S&C organization. A schematic diagram of the new organization can be seen in Fig.1. Figure 1: new ATLAS Software & Computing organization. Two Management Boards will help the Computing Coordinator and the Software Project...

  4. Computational and mathematical methods in brain atlasing.

    Science.gov (United States)

    Nowinski, Wieslaw L

    2017-12-01

    Brain atlases have a wide range of use from education to research to clinical applications. Mathematical methods as well as computational methods and tools play a major role in the process of brain atlas building and developing atlas-based applications. Computational methods and tools cover three areas: dedicated editors for brain model creation, brain navigators supporting multiple platforms, and atlas-assisted specific applications. Mathematical methods in atlas building and developing atlas-aided applications deal with problems in image segmentation, geometric body modelling, physical modelling, atlas-to-scan registration, visualisation, interaction and virtual reality. Here I overview computational and mathematical methods in atlas building and developing atlas-assisted applications, and share my contribution to and experience in this field.

  5. Support system for ATLAS distributed computing operations

    CERN Document Server

    Kishimoto, Tomoe; The ATLAS collaboration

    2018-01-01

    The ATLAS distributed computing system has allowed the experiment to successfully meet the challenges of LHC Run 2. In order for distributed computing to operate smoothly and efficiently, several support teams are organized in the ATLAS experiment. The ADCoS (ATLAS Distributed Computing Operation Shifts) is a dedicated group of shifters who follow and report failing jobs, failing data transfers between sites, degradation of ATLAS central computing services, and more. The DAST (Distributed Analysis Support Team) provides user support to resolve issues related to running distributed analysis on the grid. The CRC (Computing Run Coordinator) maintains a global view of the day-to-day operations. In this presentation, the status and operational experience of the support system for ATLAS distributed computing in LHC Run 2 will be reported. This report also includes operations experience from the grid site point of view, and an analysis of the errors that create the biggest waste of wallclock time. The report of oper...

  6. Exploitation of heterogeneous resources for ATLAS Computing

    CERN Document Server

    Chudoba, Jiri; The ATLAS collaboration

    2018-01-01

    LHC experiments require significant computational resources for Monte Carlo simulations and real data processing and the ATLAS experiment is not an exception. In 2017, ATLAS exploited steadily almost 3M HS06 units, which corresponds to about 300 000 standard CPU cores. The total disk and tape capacity managed by the Rucio data management system exceeded 350 PB. Resources are provided mostly by Grid computing centers distributed in geographically separated locations and connected by the Grid middleware. The ATLAS collaboration developed several systems to manage computational jobs, data files and network transfers. ATLAS solutions for job and data management (PanDA and Rucio) were generalized and now are used also by other collaborations. More components are needed to include new resources such as private and public clouds, volunteers' desktop computers and primarily supercomputers in major HPC centers. Workflows and data flows significantly differ for these less traditional resources and extensive software re...

  7. Volunteer computing experience with ATLAS@Home

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00068610; The ATLAS collaboration; Bianchi, Riccardo-Maria; Cameron, David; Filipčič, Andrej; Lançon, Eric; Wu, Wenjing

    2016-01-01

    ATLAS@Home is a volunteer computing project which allows the public to contribute to computing for the ATLAS experiment through their home or office computers. The project has grown continuously since its creation in mid-2014 and now counts almost 100,000 volunteers. The combined volunteers’ resources make up a sizeable fraction of overall resources for ATLAS simulation. This paper takes stock of the experience gained so far and describes the next steps in the evolution of the project. These improvements include running natively on Linux to ease the deployment on for example university clusters, using multiple cores inside one task to reduce the memory requirements and running different types of workload such as event generation. In addition to technical details the success of ATLAS@Home as an outreach tool is evaluated.

  8. Volunteer Computing Experience with ATLAS@Home

    CERN Document Server

    Cameron, David; The ATLAS collaboration; Bourdarios, Claire; Lan\\c con, Eric

    2016-01-01

    ATLAS@Home is a volunteer computing project which allows the public to contribute to computing for the ATLAS experiment through their home or office computers. The project has grown continuously since its creation in mid-2014 and now counts almost 100,000 volunteers. The combined volunteers' resources make up a sizable fraction of overall resources for ATLAS simulation. This paper takes stock of the experience gained so far and describes the next steps in the evolution of the project. These improvements include running natively on Linux to ease the deployment on for example university clusters, using multiple cores inside one job to reduce the memory requirements and running different types of workload such as event generation. In addition to technical details the success of ATLAS@Home as an outreach tool is evaluated.

  9. Volunteer Computing Experience with ATLAS@Home

    Science.gov (United States)

    Adam-Bourdarios, C.; Bianchi, R.; Cameron, D.; Filipčič, A.; Isacchini, G.; Lançon, E.; Wu, W.; ATLAS Collaboration

    2017-10-01

    ATLAS@Home is a volunteer computing project which allows the public to contribute to computing for the ATLAS experiment through their home or office computers. The project has grown continuously since its creation in mid-2014 and now counts almost 100,000 volunteers. The combined volunteers’ resources make up a sizeable fraction of overall resources for ATLAS simulation. This paper takes stock of the experience gained so far and describes the next steps in the evolution of the project. These improvements include running natively on Linux to ease the deployment on for example university clusters, using multiple cores inside one task to reduce the memory requirements and running different types of workload such as event generation. In addition to technical details the success of ATLAS@Home as an outreach tool is evaluated.

  10. Analytics Platform for ATLAS Computing Services

    CERN Document Server

    Vukotic, Ilija; The ATLAS collaboration; Bryant, Lincoln

    2016-01-01

    Big Data technologies have proven to be very useful for storage, processing and visualization of derived metrics associated with ATLAS distributed computing (ADC) services. Log file data and database records, and metadata from a diversity of systems have been aggregated and indexed to create an analytics platform for ATLAS ADC operations analysis. Dashboards, wide area data access cost metrics, user analysis patterns, and resource utilization efficiency charts are produced flexibly through queries against a powerful analytics cluster. Here we explore whether these techniques and analytics ecosystem can be applied to add new modes of open, quick, and pervasive access to ATLAS event data so as to simplify access and broaden the reach of ATLAS public data to new communities of users. An ability to efficiently store, filter, search and deliver ATLAS data at the event and/or sub-event level in a widely supported format would enable or significantly simplify usage of machine learning tools like Spark, Jupyter, R, S...

  11. ATLAS Cloud Computing R&D project

    CERN Document Server

    Panitkin, S; The ATLAS collaboration; Caballero Bejar, J; Benjamin, D; DiGirolamo, A; Gable, I; Hendrix, V; Hover, J; Kucharczuk, K; Medrano LLamas, R; Ohman, H; Paterson, M; Sobie, R; Taylor, R; Walker, R; Zaytsev, A

    2013-01-01

    The computing model of the ATLAS experiment was designed around the concept of grid computing and, since the start of data taking, this model has proven very successful. However, new cloud computing technologies bring attractive features to improve the operations and elasticity of scientific distributed computing. ATLAS sees grid and cloud computing as complementary technologies that will coexist at different levels of resource abstraction, and two years ago created an R&D working group to investigate the different integration scenarios. The ATLAS Cloud Computing R&D has been able to demonstrate the feasibility of offloading work from grid to cloud sites and, as of today, is able to integrate transparently various cloud resources into the PanDA workload management system. The ATLAS Cloud Computing R&D is operating various PanDA queues on private and public resources and has provided several hundred thousand CPU days to the experiment. As a result, the ATLAS Cloud Computing R&D group has gained...

  12. Exploiting Virtualization and Cloud Computing in ATLAS

    International Nuclear Information System (INIS)

    Harald Barreiro Megino, Fernando; Van der Ster, Daniel; Benjamin, Doug; De, Kaushik; Gable, Ian; Paterson, Michael; Taylor, Ryan; Hendrix, Val; Vitillo, Roberto A; Panitkin, Sergey; De Silva, Asoka; Walker, Rod

    2012-01-01

    The ATLAS Computing Model was designed around the concept 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 improved strategies for managing and provisioning IT resources that could allow ATLAS to more flexibly adapt and scale its storage and processing workloads on varied underlying resources. In particular, ATLAS is developing a “grid-of-clouds” infrastructure in order to utilize WLCG sites that make resources available via a cloud API. This work will present the current status of the Virtualization and Cloud Computing R and D project in ATLAS Distributed Computing. First, strategies for deploying PanDA queues on cloud sites will be discussed, including the introduction of a “cloud factory” for managing cloud VM instances. Next, performance results when running on virtualized/cloud resources at CERN LxCloud, StratusLab, and elsewhere will be presented. Finally, we will present the ATLAS strategies for exploiting cloud-based storage, including remote XROOTD access to input data, management of EC2-based files, and the deployment of cloud-resident LCG storage elements.

  13. ATLAS Distributed Computing: Its Central Services core

    CERN Document Server

    Lee, Christopher Jon; The ATLAS collaboration

    2018-01-01

    The ATLAS Distributed Computing (ADC) Project is responsible for the off-line processing of data produced by the ATLAS experiment at the Large Hadron Collider (LHC) at CERN. It facilitates data and workload management for ATLAS computing on the Worldwide LHC Computing Grid (WLCG). ADC Central Services operations (CSops)is a vital part of ADC, responsible for the deployment and configuration of services needed by ATLAS computing and operation of those services on CERN IT infrastructure, providing knowledge of CERN IT services to ATLAS service managers and developers, and supporting them in case of issues. Currently this entails the management of thirty seven different OpenStack projects, with more than five thousand cores allocated for these virtual machines, as well as overseeing the distribution of twenty nine petabytes of storage space in EOS for ATLAS. As the LHC begins to get ready for the next long shut-down, which will bring in many new upgrades to allow for more data to be captured by the on-line syste...

  14. ATLAS Distributed Computing: Experience and Evolution

    CERN Document Server

    Nairz, A; The ATLAS collaboration

    2013-01-01

    The ATLAS experiment has just concluded its first running period which commenced in 2010. After two years of remarkable performance from the LHC and ATLAS, the experiment has accumulated more than 25 fb-1 of data. The total volume of beam and simulated data products exceeds 100 PB distributed across more than 150 computing centers around the world, managed by the experiment's distributed data management system. These sites have provided up to 150,000 computing cores to ATLAS's global production and analysis processing system, enabling a rich physics program including the discovery of the Higgs-like boson in 2012. The wealth of accumulated experience in global data-intensive computing at this massive scale, and the considerably more challenging requirements of LHC computing from 2014 when the LHC resumes operation, are driving a comprehensive design and development cycle to prepare a revised computing model together with data processing and management systems able to meet the demands of higher trigger rates, e...

  15. ATLAS distributed computing: experience and evolution

    CERN Document Server

    Nairz, A; The ATLAS collaboration

    2014-01-01

    The ATLAS experiment has just concluded its first running period which commenced in 2010. After two years of remarkable performance from the LHC and ATLAS, the experiment has accumulated more than 25/fb of data. The total volume of beam and simulated data products exceeds 100~PB distributed across more than 150 computing centres around the world, managed by the experiment's distributed data management system. These sites have provided up to 150,000 computing cores to ATLAS's global production and analysis processing system, enabling a rich physics programme including the discovery of the Higgs-like boson in 2012. The wealth of accumulated experience in global data-intensive computing at this massive scale, and the considerably more challenging requirements of LHC computing from 2015 when the LHC resumes operation, are driving a comprehensive design and development cycle to prepare a revised computing model together with data processing and management systems able to meet the demands of higher trigger rates, e...

  16. The Evolution of Cloud Computing in ATLAS

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00224309; Berghaus, Frank; Brasolin, Franco; Cordeiro, Cristovao; Desmarais, Ron; Field, Laurence; Gable, Ian; Giordano, Domenico; Di Girolamo, Alessandro; Hover, John; Leblanc, Matthew Edgar; Love, Peter; Paterson, Michael; Sobie, Randall; Zaytsev, Alexandr

    2015-01-01

    The ATLAS experiment has successfully incorporated cloud computing technology and cloud resources into its primarily grid-based model of distributed computing. Cloud R&D activities continue to mature and transition into stable production systems, while ongoing evolutionary changes are still needed to adapt and refine the approaches used, in response to changes in prevailing cloud technology. In addition, completely new developments are needed to handle emerging requirements. This paper describes the overall evolution of cloud computing in ATLAS. The current status of the virtual machine (VM) management systems used for harnessing infrastructure as a service (IaaS) resources are discussed. Monitoring and accounting systems tailored for clouds are needed to complete the integration of cloud resources within ATLAS' distributed computing framework. We are developing and deploying new solutions to address the challenge of operation in a geographically distributed multi-cloud scenario, including a system for ma...

  17. The Evolution of Cloud Computing in ATLAS

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00224309; The ATLAS collaboration; Berghaus, Frank; Love, Peter; Leblanc, Matthew Edgar; Di Girolamo, Alessandro; Paterson, Michael; Gable, Ian; Sobie, Randall; Field, Laurence

    2015-01-01

    The ATLAS experiment has successfully incorporated cloud computing technology and cloud resources into its primarily grid-based model of distributed computing. Cloud R&D activities continue to mature and transition into stable production systems, while ongoing evolutionary changes are still needed to adapt and refine the approaches used, in response to changes in prevailing cloud technology. In addition, completely new developments are needed to handle emerging requirements. This work will describe the overall evolution of cloud computing in ATLAS. The current status of the VM management systems used for harnessing IAAS resources will be discussed. Monitoring and accounting systems tailored for clouds are needed to complete the integration of cloud resources within ATLAS' distributed computing framework. We are developing and deploying new solutions to address the challenge of operation in a geographically distributed multi-cloud scenario, including a system for managing VM images across multiple clouds, ...

  18. ATLAS Distributed Computing in LHC Run2

    CERN Document Server

    Campana, Simone; The ATLAS collaboration

    2015-01-01

    The ATLAS Distributed Computing infrastructure has evolved after the first period of LHC data taking in order to cope with the challenges of the upcoming LHC Run2. An increased data rate and computing demands of the Monte-Carlo simulation, as well as new approaches to ATLAS analysis, dictated a more dynamic workload management system (ProdSys2) and data management system (Rucio), overcoming the boundaries imposed by the design of the old computing model. In particular, the commissioning of new central computing system components was the core part of the migration toward the flexible computing model. The flexible computing utilization exploring the opportunistic resources such as HPC, cloud, and volunteer computing is embedded in the new computing model, the data access mechanisms have been enhanced with the remote access, and the network topology and performance is deeply integrated into the core of the system. Moreover a new data management strategy, based on defined lifetime for each dataset, has been defin...

  19. Exploiting Virtualization and Cloud Computing in ATLAS

    CERN Multimedia

    CERN. Geneva

    2012-01-01

    This work will present the current status of the Virtualization and Cloud Computing R&D project in ATLAS Distributed Computing. First, strategies for deploying PanDA queues on cloud sites will be discussed, including the introduction of a "cloud factory" for managing cloud VM instances. Ne...

  20. ATLAS distributed computing: experience and evolution

    International Nuclear Information System (INIS)

    Nairz, A

    2014-01-01

    The ATLAS experiment has just concluded its first running period which commenced in 2010. After two years of remarkable performance from the LHC and ATLAS, the experiment has accumulated more than 25 fb −1 of data. The total volume of beam and simulated data products exceeds 100 PB distributed across more than 150 computing centres around the world, managed by the experiment's distributed data management system. These sites have provided up to 150,000 computing cores to ATLAS's global production and analysis processing system, enabling a rich physics programme including the discovery of the Higgs-like boson in 2012. The wealth of accumulated experience in global data-intensive computing at this massive scale, and the considerably more challenging requirements of LHC computing from 2015 when the LHC resumes operation, are driving a comprehensive design and development cycle to prepare a revised computing model together with data processing and management systems able to meet the demands of higher trigger rates, energies and event complexities. An essential requirement will be the efficient utilisation of current and future processor technologies as well as a broad range of computing platforms, including supercomputing and cloud resources. We will report on experience gained thus far and our progress in preparing ATLAS computing for the future

  1. ATLAS computing on CSCS HPC

    Science.gov (United States)

    Filipcic, A.; Haug, S.; Hostettler, M.; Walker, R.; Weber, M.

    2015-12-01

    The Piz Daint Cray XC30 HPC system at CSCS, the Swiss National Supercomputing centre, was the highest ranked European system on TOP500 in 2014, also featuring GPU accelerators. Event generation and detector simulation for the ATLAS experiment have been enabled for this machine. We report on the technical solutions, performance, HPC policy challenges and possible future opportunities for HEP on extreme HPC systems. In particular a custom made integration to the ATLAS job submission system has been developed via the Advanced Resource Connector (ARC) middleware. Furthermore, a partial GPU acceleration of the Geant4 detector simulations has been implemented.

  2. ATLAS computing on CSCS HPC

    CERN Document Server

    Hostettler, Michael Artur; The ATLAS collaboration; Haug, Sigve; Walker, Rodney; Weber, Michele

    2015-01-01

    The Piz Daint Cray XC30 HPC system at CSCS, the Swiss National Supercomputing centre, was in 2014 the highest ranked European system on TOP500, also featuring GPU accelerators. Event generation and detector simulation for the ATLAS experiment have been enabled for this machine. We report on the technical solutions, performance, HPC policy challenges and possible future opportunities for HEP on extreme HPC systems. In particular a custom made integration to the ATLAS job submission system has been developed via the Advanced Resource Connector (ARC) middleware. Furthermore, some GPU acceleration of the Geant4 detector simulations has been implemented to justify the allocation request for this machine.

  3. ATLAS computing on CSCS HPC

    CERN Document Server

    Filipcic, Andrej; The ATLAS collaboration; Weber, Michele; Walker, Rodney; Hostettler, Michael Artur

    2015-01-01

    The Piz Daint Cray XC30 HPC system at CSCS, the Swiss National Supercomputing centre, is in 2014 the highest ranked European system on TOP500, also featuring GPU accelerators. Event generation and detector simulation for the ATLAS experiment has been enabled for this machine. We report on the technical solutions, performance, HPC policy challenges and possible future opportunities for HEP on extreme HPC systems. In particular a custom made integration to the ATLAS job submission system has been developed via the Advanced Resource Connector (ARC) middleware. Further, some GPU acceleration of the Geant4 detector simulations were implemented to justify the allocation request for this machine.

  4. AGIS: Integration of new technologies used in ATLAS Distributed Computing

    OpenAIRE

    Anisenkov, Alexey; Di Girolamo, Alessandro; Alandes Pradillo, Maria

    2017-01-01

    The variety of the ATLAS Distributed Computing infrastructure requires a central information system to define the topology of computing resources and to store different parameters and configuration data which are needed by various ATLAS software components. The ATLAS Grid Information System (AGIS) is the system designed to integrate configuration and status information about resources, services and topology of the computing infrastructure used by ATLAS Distributed Computing applications and s...

  5. AGIS: Evolution of Distributed Computing Information system for ATLAS

    CERN Document Server

    Anisenkov, Alexey; The ATLAS collaboration; Alandes Pradillo, Maria; Karavakis, Edward

    2015-01-01

    The variety of the ATLAS Computing Infrastructure requires a central information system to define the topology of computing resources and to store the different parameters and configuration data which are needed by the various ATLAS software components. The ATLAS Grid Information System is the system designed to integrate configuration and status information about resources, services and topology of the computing infrastructure used by ATLAS Distributed Computing applications and services.

  6. Operation of the ATLAS distributed computing

    CERN Document Server

    Barreiro Megino, Fernando Harald; The ATLAS collaboration

    2018-01-01

    We describe the central operation of the ATLAS distributed computing system. The majority of compute intensive activities within ATLAS are carried out on some 350,000 CPU cores on the Grid, augmented by opportunistic usage of significant HPC and volunteer resources. The increasing scale, and challenging new payloads, demand fine-tuning of operational procedures together with timely developments of the production system. We describe several such developments, motivated directly from operational experience. Optimization of inefficient task requests, from both official production and users, is made possible by automatic detection of payload properties. User education, job shaping or preventative throttling help to increase the overall throughput of the available resources.

  7. Overview of the ATLAS distributed computing system

    CERN Document Server

    Elmsheuser, Johannes; The ATLAS collaboration

    2018-01-01

    The CERN ATLAS experiment successfully uses a worldwide computing infrastructure to support the physics program during LHC Run 2. The grid workflow system PanDA routinely manages 250 to 500 thousand concurrently running production and analysis jobs to process simulation and detector data. In total more than 300 PB of data is distributed over more than 150 sites in the WLCG and handled by the ATLAS data management system Rucio. To prepare for the ever growing LHC luminosity in future runs new developments are underway to even more efficiently use opportunistic resources such as HPCs and utilize new technologies. This presentation will review and explain the outline and the performance of the ATLAS distributed computing system and give an outlook to new workflow and data management ideas for the beginning of the LHC Run 3.

  8. AGIS: Integration of new technologies used in ATLAS Distributed Computing

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00291854; The ATLAS collaboration; Di Girolamo, Alessandro; Alandes Pradillo, Maria

    2017-01-01

    The variety of the ATLAS Distributed Computing infrastructure requires a central information system to define the topology of computing resources and to store different parameters and configuration data which are needed by various ATLAS software components. The ATLAS Grid Information System (AGIS) is the system designed to integrate configuration and status information about resources, services and topology of the computing infrastructure used by ATLAS Distributed Computing applications and services. Being an intermediate middleware system between clients and external information sources (like central BDII, GOCDB, MyOSG), AGIS defines the relations between experiment specific used resources and physical distributed computing capabilities. Being in production during LHC Runl AGIS became the central information system for Distributed Computing in ATLAS and it is continuously evolving to fulfil new user requests, enable enhanced operations and follow the extension of the ATLAS Computing model. The ATLAS Computin...

  9. Consolidation of cloud computing in ATLAS

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00224309; The ATLAS collaboration; Cordeiro, Cristovao; Hover, John; Kouba, Tomas; Love, Peter; Mcnab, Andrew; Schovancova, Jaroslava; Sobie, Randall; Giordano, Domenico

    2017-01-01

    Throughout the first half of LHC Run 2, ATLAS cloud computing has undergone a period of consolidation, characterized by building upon previously established systems, with the aim of reducing operational effort, improving robustness, and reaching higher scale. This paper describes the current state of ATLAS cloud computing. Cloud activities are converging on a common contextualization approach for virtual machines, and cloud resources are sharing monitoring and service discovery components. We describe the integration of Vacuum resources, streamlined usage of the Simulation at Point 1 cloud for offline processing, extreme scaling on Amazon compute resources, and procurement of commercial cloud capacity in Europe. Finally, building on the previously established monitoring infrastructure, we have deployed a real-time monitoring and alerting platform which coalesces data from multiple sources, provides flexible visualization via customizable dashboards, and issues alerts and carries out corrective actions in resp...

  10. Consolidation of cloud computing in ATLAS

    Science.gov (United States)

    Taylor, Ryan P.; Domingues Cordeiro, Cristovao Jose; Giordano, Domenico; Hover, John; Kouba, Tomas; Love, Peter; McNab, Andrew; Schovancova, Jaroslava; Sobie, Randall; ATLAS Collaboration

    2017-10-01

    Throughout the first half of LHC Run 2, ATLAS cloud computing has undergone a period of consolidation, characterized by building upon previously established systems, with the aim of reducing operational effort, improving robustness, and reaching higher scale. This paper describes the current state of ATLAS cloud computing. Cloud activities are converging on a common contextualization approach for virtual machines, and cloud resources are sharing monitoring and service discovery components. We describe the integration of Vacuum resources, streamlined usage of the Simulation at Point 1 cloud for offline processing, extreme scaling on Amazon compute resources, and procurement of commercial cloud capacity in Europe. Finally, building on the previously established monitoring infrastructure, we have deployed a real-time monitoring and alerting platform which coalesces data from multiple sources, provides flexible visualization via customizable dashboards, and issues alerts and carries out corrective actions in response to problems.

  11. System administration of ATLAS TDAQ computing environment

    Science.gov (United States)

    Adeel-Ur-Rehman, A.; Bujor, F.; Benes, J.; Caramarcu, C.; Dobson, M.; Dumitrescu, A.; Dumitru, I.; Leahu, M.; Valsan, L.; Oreshkin, A.; Popov, D.; Unel, G.; Zaytsev, A.

    2010-04-01

    This contribution gives a thorough overview of the ATLAS TDAQ SysAdmin group activities which deals with administration of the TDAQ computing environment supporting High Level Trigger, Event Filter and other subsystems of the ATLAS detector operating on LHC collider at CERN. The current installation consists of approximately 1500 netbooted nodes managed by more than 60 dedicated servers, about 40 multi-screen user interface machines installed in the control rooms and various hardware and service monitoring machines as well. In the final configuration, the online computer farm will be capable of hosting tens of thousands applications running simultaneously. The software distribution requirements are matched by the two level NFS based solution. Hardware and network monitoring systems of ATLAS TDAQ are based on NAGIOS and MySQL cluster behind it for accounting and storing the monitoring data collected, IPMI tools, CERN LANDB and the dedicated tools developed by the group, e.g. ConfdbUI. The user management schema deployed in TDAQ environment is founded on the authentication and role management system based on LDAP. External access to the ATLAS online computing facilities is provided by means of the gateways supplied with an accounting system as well. Current activities of the group include deployment of the centralized storage system, testing and validating hardware solutions for future use within the ATLAS TDAQ environment including new multi-core blade servers, developing GUI tools for user authentication and roles management, testing and validating 64-bit OS, and upgrading the existing TDAQ hardware components, authentication servers and the gateways.

  12. ATLAS Distributed Computing in LHC Run2

    International Nuclear Information System (INIS)

    Campana, Simone

    2015-01-01

    The ATLAS Distributed Computing infrastructure has evolved after the first period of LHC data taking in order to cope with the challenges of the upcoming LHC Run-2. An increase in both the data rate and the computing demands of the Monte-Carlo simulation, as well as new approaches to ATLAS analysis, dictated a more dynamic workload management system (Prodsys-2) and data management system (Rucio), overcoming the boundaries imposed by the design of the old computing model. In particular, the commissioning of new central computing system components was the core part of the migration toward a flexible computing model. A flexible computing utilization exploring the use of opportunistic resources such as HPC, cloud, and volunteer computing is embedded in the new computing model; the data access mechanisms have been enhanced with the remote access, and the network topology and performance is deeply integrated into the core of the system. Moreover, a new data management strategy, based on a defined lifetime for each dataset, has been defined to better manage the lifecycle of the data. In this note, an overview of an operational experience of the new system and its evolution is presented. (paper)

  13. Consolidation of Cloud Computing in ATLAS

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00224309; The ATLAS collaboration; Cordeiro, Cristovao; Di Girolamo, Alessandro; Hover, John; Kouba, Tomas; Love, Peter; Mcnab, Andrew; Schovancova, Jaroslava; Sobie, Randall

    2016-01-01

    Throughout the first year of LHC Run 2, ATLAS Cloud Computing has undergone a period of consolidation, characterized by building upon previously established systems, with the aim of reducing operational effort, improving robustness, and reaching higher scale. This paper describes the current state of ATLAS Cloud Computing. Cloud activities are converging on a common contextualization approach for virtual machines, and cloud resources are sharing monitoring and service discovery components. We describe the integration of Vac resources, streamlined usage of the High Level Trigger cloud for simulation and reconstruction, extreme scaling on Amazon EC2, and procurement of commercial cloud capacity in Europe. Building on the previously established monitoring infrastructure, we have deployed a real-time monitoring and alerting platform which coalesces data from multiple sources, provides flexible visualization via customizable dashboards, and issues alerts and carries out corrective actions in response to problems. ...

  14. ATLAS and LHC computing on CRAY

    CERN Document Server

    Haug, Sigve; The ATLAS collaboration

    2016-01-01

    Access and exploitation of large scale computing resources, such as those offered by general purpose HPC centres, is one import measure for ATLAS and the other Large Hadron Collider experiments in order to meet the challenge posed by the full exploitation of the future data within the constraints of flat budgets. We report on the effort moving the Swiss WLCG T2 computing, serving ATLAS, CMS and LHCb from a dedicated cluster to the large CRAY systems at the Swiss National Supercomputing Centre CSCS. These systems do not only offer very efficient hardware, cooling and highly competent operators, but also have large backfill potentials due to size and multidisciplinary usage and potential gains due to economy at scale. Technical solutions, performance, expected return and future plans are discussed.

  15. ATLAS and LHC computing on CRAY

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00297774; The ATLAS collaboration; Haug, Sigve

    2017-01-01

    Access and exploitation of large scale computing resources, such as those offered by general purpose HPC centres, is one important measure for ATLAS and the other Large Hadron Collider experiments in order to meet the challenge posed by the full exploitation of the future data within the constraints of flat budgets. We report on the effort of moving the Swiss WLCG T2 computing, serving ATLAS, CMS and LHCb, from a dedicated cluster to the large Cray systems at the Swiss National Supercomputing Centre CSCS. These systems do not only offer very efficient hardware, cooling and highly competent operators, but also have large backfill potentials due to size and multidisciplinary usage and potential gains due to economy at scale. Technical solutions, performance, expected return and future plans are discussed.

  16. Automating usability of ATLAS distributed computing resources

    International Nuclear Information System (INIS)

    Tupputi, S A; Girolamo, A Di; Kouba, T; Schovancová, J

    2014-01-01

    The automation of ATLAS Distributed Computing (ADC) operations is essential to reduce manpower costs and allow performance-enhancing actions, which improve the reliability of the system. In this perspective a crucial case is the automatic handling of outages of ATLAS computing sites storage resources, which are continuously exploited at the edge of their capabilities. It is challenging to adopt unambiguous decision criteria for storage resources of non-homogeneous types, sizes and roles. The recently developed Storage Area Automatic Blacklisting (SAAB) tool has provided a suitable solution, by employing an inference algorithm which processes history of storage monitoring tests outcome. SAAB accomplishes both the tasks of providing global monitoring as well as automatic operations on single sites. The implementation of the SAAB tool has been the first step in a comprehensive review of the storage areas monitoring and central management at all levels. Such review has involved the reordering and optimization of SAM tests deployment and the inclusion of SAAB results in the ATLAS Site Status Board with both dedicated metrics and views. The resulting structure allows monitoring the storage resources status with fine time-granularity and automatic actions to be taken in foreseen cases, like automatic outage handling and notifications to sites. Hence, the human actions are restricted to reporting and following up problems, where and when needed. In this work we show SAAB working principles and features. We present also the decrease of human interactions achieved within the ATLAS Computing Operation team. The automation results in a prompt reaction to failures, which leads to the optimization of resource exploitation.

  17. Xcache in the ATLAS Distributed Computing Environment

    CERN Document Server

    Hanushevsky, Andrew; The ATLAS collaboration

    2018-01-01

    Built upon the Xrootd Proxy Cache (Xcache), we developed additional features to adapt the ATLAS distributed computing and data environment, especially its data management system RUCIO, to help improve the cache hit rate, as well as features that make the Xcache easy to use, similar to the way the Squid cache is used by the HTTP protocol. We are optimizing Xcache for the HPC environments, and adapting the HL-LHC Data Lakes design as its component for data delivery. We packaged the software in CVMFS, in Docker and Singularity containers in order to standardize the deployment and reduce the cost to resolve issues at remote sites. We are also integrating it into RUCIO as a volatile storage systems, and into various ATLAS workflow such as user analysis,

  18. Data analytics in the ATLAS Distributed Computing

    CERN Document Server

    Vukotic, Ilija; The ATLAS collaboration; Bryant, Lincoln

    2015-01-01

    The ATLAS Data analytics effort is focused on creating systems which provide the ATLAS ADC with new capabilities for understanding distributed systems and overall operational performance. These capabilities include: warehousing information from multiple systems (the production and distributed analysis system - PanDA, the distributed data management system - Rucio, the file transfer system, various monitoring services etc. ); providing a platform to execute arbitrary data mining and machine learning algorithms over aggregated data; satisfy a variety of use cases for different user roles; host new third party analytics services on a scalable compute platform. We describe the implemented system where: data sources are existing RDBMS (Oracle) and Flume collectors; a Hadoop cluster is used to store the data; native Hadoop and Apache Pig scripts are used for data aggregation; and R for in-depth analytics. Part of the data is indexed in ElasticSearch so both simpler investigations and complex dashboards can be made ...

  19. ATLAS computing on Swiss Cloud SWITCHengines

    Science.gov (United States)

    Haug, S.; Sciacca, F. G.; ATLAS Collaboration

    2017-10-01

    Consolidation towards more computing at flat budgets beyond what pure chip technology can offer, is a requirement for the full scientific exploitation of the future data from the Large Hadron Collider at CERN in Geneva. One consolidation measure is to exploit cloud infrastructures whenever they are financially competitive. We report on the technical solutions and the performances used and achieved running simulation tasks for the ATLAS experiment on SWITCHengines. SWITCHengines is a new infrastructure as a service offered to Swiss academia by the National Research and Education Network SWITCH. While solutions and performances are general, financial considerations and policies, on which we also report, are country specific.

  20. ATLAS computing on Swiss Cloud SWITCHengines

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00215485; The ATLAS collaboration; Sciacca, Gianfranco

    2017-01-01

    Consolidation towards more computing at flat budgets beyond what pure chip technology can offer, is a requirement for the full scientific exploitation of the future data from the Large Hadron Collider at CERN in Geneva. One consolidation measure is to exploit cloud infrastructures whenever they are financially competitive. We report on the technical solutions and the performances used and achieved running simulation tasks for the ATLAS experiment on SWITCHengines. SWITCHengines is a new infrastructure as a service offered to Swiss academia by the National Research and Education Network SWITCH. While solutions and performances are general, financial considerations and policies, on which we also report, are country specific.

  1. ATLAS Computing on the Swiss Cloud SWITCHengines

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00215485; The ATLAS collaboration; Sciacca, Gianfranco

    2016-01-01

    Consolidation towards more computing at flat budgets beyond what pure chip technology can offer, is a requirement for the full scientific exploitation of the future data from the Large Hadron Collider. One consolidation measure is to exploit cloud infrastructures whenever they are financially competitive. We report on the technical solutions and the performance used and achieved running ATLAS production on SWITCHengines. SWITCHengines is the new cloud infrastructure offered to Swiss academia by the National Research and Education Network SWITCH. While solutions and performances are general, financial considerations and policies, which we also report on, are country specific.

  2. AGIS: Integration of new technologies used in ATLAS Distributed Computing

    Science.gov (United States)

    Anisenkov, Alexey; Di Girolamo, Alessandro; Alandes Pradillo, Maria

    2017-10-01

    The variety of the ATLAS Distributed Computing infrastructure requires a central information system to define the topology of computing resources and to store different parameters and configuration data which are needed by various ATLAS software components. The ATLAS Grid Information System (AGIS) is the system designed to integrate configuration and status information about resources, services and topology of the computing infrastructure used by ATLAS Distributed Computing applications and services. Being an intermediate middleware system between clients and external information sources (like central BDII, GOCDB, MyOSG), AGIS defines the relations between experiment specific used resources and physical distributed computing capabilities. Being in production during LHC Runl AGIS became the central information system for Distributed Computing in ATLAS and it is continuously evolving to fulfil new user requests, enable enhanced operations and follow the extension of the ATLAS Computing model. The ATLAS Computing model and data structures used by Distributed Computing applications and services are continuously evolving and trend to fit newer requirements from ADC community. In this note, we describe the evolution and the recent developments of AGIS functionalities, related to integration of new technologies recently become widely used in ATLAS Computing, like flexible computing utilization of opportunistic Cloud and HPC resources, ObjectStore services integration for Distributed Data Management (Rucio) and ATLAS workload management (PanDA) systems, unified storage protocols declaration required for PandDA Pilot site movers and others. The improvements of information model and general updates are also shown, in particular we explain how other collaborations outside ATLAS could benefit the system as a computing resources information catalogue. AGIS is evolving towards a common information system, not coupled to a specific experiment.

  3. Automating ATLAS Computing Operations using the Site Status Board

    CERN Document Server

    Andreeva, J; The ATLAS collaboration; Campana, S; Di Girolamo, A; Espinal Curull, X; Gayazov, S; Magradze, E; Nowotka, MM; Rinaldi, L; Saiz, P; Schovancova, J; Stewart, GA; Wright, M

    2012-01-01

    The automation of operations is essential to reduce manpower costs and improve the reliability of the system. The Site Status Board (SSB) is a framework which allows Virtual Organizations to monitor their computing activities at distributed sites and to evaluate site performance. The ATLAS experiment intensively uses SSB for the distributed computing shifts, for estimating data processing and data transfer efficiencies at a particular site, and for implementing automatic exclusion of sites from computing activities, in case of potential problems. ATLAS SSB provides a real-time aggregated monitoring view and keeps the history of the monitoring metrics. Based on this history, usability of a site from the perspective of ATLAS is calculated. The presentation will describe how SSB is integrated in the ATLAS operations and computing infrastructure and will cover implementation details of the ATLAS SSB sensors and alarm system, based on the information in SSB. It will demonstrate the positive impact of the use of SS...

  4. AGIS: Evolution of Distributed Computing information system for ATLAS

    Science.gov (United States)

    Anisenkov, A.; Di Girolamo, A.; Alandes, M.; Karavakis, E.

    2015-12-01

    ATLAS, a particle physics experiment at the Large Hadron Collider at CERN, produces petabytes of data annually through simulation production and tens of petabytes of data per year from the detector itself. The ATLAS computing model embraces the Grid paradigm and a high degree of decentralization of computing resources in order to meet the ATLAS requirements of petabytes scale data operations. It has been evolved after the first period of LHC data taking (Run-1) in order to cope with new challenges of the upcoming Run- 2. In this paper we describe the evolution and recent developments of the ATLAS Grid Information System (AGIS), developed in order to integrate configuration and status information about resources, services and topology of the computing infrastructure used by the ATLAS Distributed Computing applications and services.

  5. AGIS: Integration of new technologies used in ATLAS Distributed Computing

    CERN Document Server

    Anisenkov, Alexey; The ATLAS collaboration; Alandes Pradillo, Maria

    2016-01-01

    AGIS is the information system designed to integrate configuration and status information about resources, services and topology of the computing infrastructure used by ATLAS Distributed Computing (ADC) applications and services. In this note, we describe the evolution and the recent developments of AGIS functionalities, related to integration of new technologies recently become widely used in ATLAS Computing like flexible computing utilization of opportunistic Cloud and HPC resources, ObjectStore services integration for Distributed Data Management (Rucio) and ATLAS workload management (PanDA) systems, unified storage protocols declaration required for PandDA Pilot site movers and others.

  6. Advances in ATLAS@Home towards a major ATLAS computing resource

    CERN Document Server

    Cameron, David; The ATLAS collaboration

    2018-01-01

    The volunteer computing project ATLAS@Home has been providing a stable computing resource for the ATLAS experiment since 2013. It has recently undergone some significant developments and as a result has become one of the largest resources contributing to ATLAS computing, by expanding its scope beyond traditional volunteers and into exploitation of idle computing power in ATLAS data centres. Removing the need for virtualization on Linux and instead using container technology has made the entry barrier significantly lower data centre participation and in this paper, we describe the implementation and results of this change. We also present other recent changes and improvements in the project. In early 2017 the ATLAS@Home project was merged into a combined LHC@Home platform, providing a unified gateway to all CERN-related volunteer computing projects. The ATLAS Event Service shifts data processing from file-level to event-level and we describe how ATLAS@Home was incorporated into this new paradigm. The finishing...

  7. Evolving ATLAS Computing For Today’s Networks

    CERN Document Server

    Campana, S; The ATLAS collaboration; Jezequel, S; Negri, G; Serfon, C; Ueda, I

    2012-01-01

    The ATLAS computing infrastructure was designed many years ago based on the assumption of rather limited network connectivity between computing centres. ATLAS sites have been organized in a hierarchical model, where only a static subset of all possible network links can be exploited and a static subset of well connected sites (CERN and the T1s) can cover important functional roles such as hosting master copies of the data. The pragmatic adoption of such simplified approach, in respect of a more relaxed scenario interconnecting all sites, was very beneficial during the commissioning of the ATLAS distributed computing system and essential in reducing the operational cost during the first two years of LHC data taking. In the mean time, networks evolved far beyond this initial scenario: while a few countries are still poorly connected with the rest of the WLCG infrastructure, most of the ATLAS computing centres are now efficiently interlinked. Our operational experience in running the computing infrastructure in ...

  8. ATLAS@Home: Harnessing Volunteer Computing for HEP

    International Nuclear Information System (INIS)

    Adam-Bourdarios, C; Cameron, D; Filipčič, A; Lancon, E; Wu, W

    2015-01-01

    A recent common theme among HEP computing is exploitation of opportunistic resources in order to provide the maximum statistics possible for Monte Carlo simulation. Volunteer computing has been used over the last few years in many other scientific fields and by CERN itself to run simulations of the LHC beams. The ATLAS@Home project was started to allow volunteers to run simulations of collisions in the ATLAS detector. So far many thousands of members of the public have signed up to contribute their spare CPU cycles for ATLAS, and there is potential for volunteer computing to provide a significant fraction of ATLAS computing resources. Here we describe the design of the project, the lessons learned so far and the future plans. (paper)

  9. ATLAS@Home: Harnessing Volunteer Computing for HEP

    CERN Document Server

    Bourdarios, Claire; Filipcic, Andrej; Lancon, Eric; Wu, Wenjing

    2015-01-01

    A recent common theme among HEP computing is exploitation of opportunistic resources in order to provide the maximum statistics possible for Monte-Carlo simulation. Volunteer computing has been used over the last few years in many other scientific fields and by CERN itself to run simulations of the LHC beams. The ATLAS@Home project was started to allow volunteers to run simulations of collisions in the ATLAS detector. So far many thousands of members of the public have signed up to contribute their spare CPU cycles for ATLAS, and there is potential for volunteer computing to provide a significant fraction of ATLAS computing resources. Here we describe the design of the project, the lessons learned so far and the future plans.

  10. The Next Generation ARC Middleware and ATLAS Computing Model

    CERN Document Server

    Filipcic, A; The ATLAS collaboration; Smirnova, O; Konstantinov, A; Karpenko, D

    2012-01-01

    The distributed NDGF Tier-1 and associated Nordugrid clusters are well integrated into the ATLAS computing model but follow a slightly different paradigm than other ATLAS resources. The current strategy does not divide the sites as in the commonly used hierarchical model, but rather treats them as a single storage endpoint and a pool of distributed computing nodes. The next generation ARC middleware with its several new technologies provides new possibilities in development of the ATLAS computing model, such as pilot jobs with pre-cached input files, automatic job migration between the sites, integration of remote sites without connected storage elements, and automatic brokering for jobs with non-standard resource requirements. ARC's data transfer model provides an automatic way for the computing sites to participate in ATLAS' global task management system without requiring centralised brokering or data transfer services. The powerful API combined with Python and Java bindings can easily be used to build new ...

  11. Common accounting system for monitoring the ATLAS distributed computing resources

    International Nuclear Information System (INIS)

    Karavakis, E; Andreeva, J; Campana, S; Saiz, P; Gayazov, S; Jezequel, S; Sargsyan, L; Schovancova, J; Ueda, I

    2014-01-01

    This paper covers in detail a variety of accounting tools used to monitor the utilisation of the available computational and storage resources within the ATLAS Distributed Computing during the first three years of Large Hadron Collider data taking. The Experiment Dashboard provides a set of common accounting tools that combine monitoring information originating from many different information sources; either generic or ATLAS specific. This set of tools provides quality and scalable solutions that are flexible enough to support the constantly evolving requirements of the ATLAS user community.

  12. The December 2006 ATLAS Computing & Software Workshop

    CERN Multimedia

    Fred Luehring

    The 29th ATLAS Computing & Software Workshop was held on December 11-15 at CERN. With the rapidly approaching onset of data taking, the workshop participants had an air of urgency about them. There was considerable discussion on hot topics such as physics validation of the software, data analysis, actual software production on the GRID, and the schedule of work for 2007 including the Final Dress Rehearsal (FDR). However don't be fooled, the workshop was not all work - there were also two social events which were greatly enjoyed by the attendees. The workshop welcomed Wouter Verkerke as the new Physics Validation Coordinator (replacing Davide Costanzo). Most recent validation work has centered on the 12.0.X release series that will be used for the Computing System Commissioning (CSC) exercise. The validation is now a big job because it needs to be done over a variety of conditions (magnetic field on/off, aligned/misaligned geometry) for every candidate release. Luckily there have been a large number of pe...

  13. ATLAS computing activities and developments in the Italian Grid cloud

    International Nuclear Information System (INIS)

    Rinaldi, L; Ciocca, C; K, M; Annovi, A; Antonelli, M; Martini, A; Barberis, D; Brunengo, A; Corosu, M; Barberis, S; Carminati, L; Campana, S; Di, A; Capone, V; Carlino, G; Doria, A; Esposito, R; Merola, L; De, A; Luminari, L

    2012-01-01

    The large amount of data produced by the ATLAS experiment needs new computing paradigms for data processing and analysis, which involve many computing centres spread around the world. The computing workload is managed by regional federations, called “clouds”. The Italian cloud consists of a main (Tier-1) center, located in Bologna, four secondary (Tier-2) centers, and a few smaller (Tier-3) sites. In this contribution we describe the Italian cloud facilities and the activities of data processing, analysis, simulation and software development performed within the cloud, and we discuss the tests of the new computing technologies contributing to evolution of the ATLAS Computing Model.

  14. ATLAS Distributed Computing Monitoring tools during the LHC Run I

    CERN Document Server

    Schovancova, J; The ATLAS collaboration; Di Girolamo, A; Jezequel, S; Ueda, I; Wenaus, T

    2013-01-01

    This contribution summarizes evolution of the ATLAS Distributed Computing (ADC) Monitoring project during the LHC Run I. The ADC Monitoring targets at the three groups of customers: ADC Operations team to early identify malfunctions and escalate issues to an activity or a service expert, ATLAS national contacts and sites for the real-time monitoring and long-term measurement of the performance of the provided computing resources, and the ATLAS Management for long-term trends and accounting information about the ATLAS Distributed Computing resources.\\\\ During the LHC Run I a significant development effort has been invested in standardization of the monitoring and accounting applications in order to provide extensive monitoring and accounting suite. ADC Monitoring applications separate the data layer and the visualization layer. The data layer exposes data in a predefined format. The visualization layer is designed bearing in mind visual identity of the provided graphical elements, and re-usability of the visua...

  15. ATLAS Distributed Computing Monitoring tools during the LHC Run I

    CERN Document Server

    Schovancova, J; The ATLAS collaboration; Di Girolamo, A; Jezequel, S; Ueda, I; Wenaus, T

    2014-01-01

    This contribution summarizes evolution of the ATLAS Distributed Computing (ADC) Monitoring project during the LHC Run I. The ADC Monitoring targets at the three groups of customers: ADC Operations team to early identify malfunctions and escalate issues to an activity or a service expert, ATLAS national contacts and sites for the real-time monitoring and long-term measurement of the performance of the provided computing resources, and the ATLAS Management for long-term trends and accounting information about the ATLAS Distributed Computing resources.\\\\ During the LHC Run I a significant development effort has been invested in standardization of the monitoring and accounting applications in order to provide extensive monitoring and accounting suite. ADC Monitoring applications separate the data layer and the visualization layer. The data layer exposes data in a predefined format. The visualization layer is designed bearing in mind visual identity of the provided graphical elements, and re-usability of the visua...

  16. Brain transcriptome atlases : A computational perspective

    NARCIS (Netherlands)

    Mahfouz, A.M.E.T.A.; Huisman, S.M.H.; Lelieveldt, B.P.F.; Reinders, M.J.T.

    2017-01-01

    The immense complexity of the mammalian brain is largely reflected in the underlying molecular signatures of its billions of cells. Brain transcriptome atlases provide valuable insights into gene expression patterns across different brain areas throughout the course of development. Such atlases

  17. ATLAS@Home: Harnessing Volunteer Computing for HEP

    CERN Document Server

    Cameron, David; The ATLAS collaboration

    2015-01-01

    The ATLAS collaboration has setup a volunteer computing project called ATLAS@home. Volunteers running Monte-Carlo simulation on their personal computer provide significant computing resources, but also belong to a community potentially interested in HEP. Four types of contributors have been identified, whose questions range from advanced technical details to the reason why simulation is needed, how Computing is organized and how it relates to society. The creation of relevant outreach material for simulation, event visualization and distributed production will be described, as well as lessons learned while interacting with the BOINC volunteers community.

  18. Computing shifts to monitor ATLAS distributed computing infrastructure and operations

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00068610; The ATLAS collaboration; Barberis, Dario; Crepe-Renaudin, Sabine Chrystel; De, Kaushik; Fassi, Farida; Stradling, Alden; Svatos, Michal; Vartapetian, Armen; Wolters, Helmut

    2017-01-01

    The ATLAS Distributed Computing (ADC) group established a new Computing Run Coordinator (CRC) shift at the start of LHC Run 2 in 2015. The main goal was to rely on a person with a good overview of the ADC activities to ease the ADC experts’ workload. The CRC shifter keeps track of ADC tasks related to their fields of expertise and responsibility. At the same time, the shifter maintains a global view of the day-to-day operations of the ADC system. During Run 1, this task was accomplished by a person of the expert team called the ADC Manager on Duty (AMOD), a position that was removed during the shutdown period due to the reduced number and availability of ADC experts foreseen for Run 2. The CRC position was proposed to cover some of the AMODs former functions, while allowing more people involved in computing to participate. In this way, CRC shifters help with the training of future ADC experts. The CRC shifters coordinate daily ADC shift operations, including tracking open issues, reporting, and representing...

  19. Computing shifts to monitor ATLAS distributed computing infrastructure and operations

    CERN Document Server

    Adam Bourdarios, Claire; The ATLAS collaboration

    2016-01-01

    The ATLAS Distributed Computing (ADC) group established a new Computing Run Coordinator (CRC) shift at the start of LHC Run2 in 2015. The main goal was to rely on a person with a good overview of the ADC activities to ease the ADC experts' workload. The CRC shifter keeps track of ADC tasks related to their fields of expertise and responsibility. At the same time, the shifter maintains a global view of the day-to-day operations of the ADC system. During Run1, this task was accomplished by the ADC Manager on Duty (AMOD), a position that was removed during the shutdown period due to the reduced number and availability of ADC experts foreseen for Run2. The CRC position was proposed to cover some of the AMOD’s former functions, while allowing more people involved in computing to participate. In this way, CRC shifters help train future ADC experts. The CRC shifters coordinate daily ADC shift operations, including tracking open issues, reporting, and representing ADC in relevant meetings. The CRC also facilitates ...

  20. ATLAS grid compute cluster with virtualized service nodes

    International Nuclear Information System (INIS)

    Mejia, J; Stonjek, S; Kluth, S

    2010-01-01

    The ATLAS Computing Grid consists of several hundred compute clusters distributed around the world as part of the Worldwide LHC Computing Grid (WLCG). The Grid middleware and the ATLAS software which has to be installed on each site, often require a certain Linux distribution and sometimes even specific version thereof. On the other hand, mostly due to maintenance reasons, computer centres install the same operating system and version on all computers. This might lead to problems with the Grid middleware if the local version is different from the one for which it has been developed. At RZG we partly solved this conflict by using virtualization technology for the service nodes. We will present the setup used at RZG and show how it helped to solve the problems described above. In addition we will illustrate the additional advantages gained by the above setup.

  1. Backfilling the Grid with Containerized BOINC in the ATLAS computing

    CERN Document Server

    Wu, Wenjing; The ATLAS collaboration

    2018-01-01

    Virtualization is a commonly used solution for utilizing the opportunistic computing resources in the HEP field, as it provides a unified software and OS layer that the HEP computing tasks require over the heterogeneous opportunistic computing resources. However there is always performance penalty with virtualization, especially for short jobs which are always the case for volunteer computing tasks, the overhead of virtualization becomes a big portion in the wall time, hence it leads to low CPU efficiency of the jobs. With the wide usage of containers in HEP computing, we explore the possibility of adopting the container technology into the ATLAS BOINC project, hence we implemented a Native version in BOINC, which uses the singularity container or direct usage of the target OS to replace VirtualBox. In this paper, we will discuss 1) the implementation and workflow of the Native version in the ATLAS BOINC; 2) the performance measurement of the Native version comparing to the previous Virtualization version. 3)...

  2. Extending ATLAS Computing to Commercial Clouds and Supercomputers

    CERN Document Server

    Nilsson, P; The ATLAS collaboration; Filipcic, A; Klimentov, A; Maeno, T; Oleynik, D; Panitkin, S; Wenaus, T; Wu, W

    2014-01-01

    The Large Hadron Collider will resume data collection in 2015 with substantially increased computing requirements relative to its first 2009-2013 run. A near doubling of the energy and the data rate, high level of event pile-up, and detector upgrades will mean the number and complexity of events to be analyzed will increase dramatically. A naive extrapolation of the Run 1 experience would suggest that a 5-6 fold increase in computing resources are needed - impossible within the anticipated flat computing budgets in the near future. Consequently ATLAS is engaged in an ambitious program to expand its computing to all available resources, notably including opportunistic use of commercial clouds and supercomputers. Such resources present new challenges in managing heterogeneity, supporting data flows, parallelizing workflows, provisioning software, and other aspects of distributed computing, all while minimizing operational load. We will present the ATLAS experience to date with clouds and supercomputers, and des...

  3. ATLAS Distributed Computing Monitoring tools during the LHC Run I

    Science.gov (United States)

    Schovancová, J.; Campana, S.; Di Girolamo, A.; Jézéquel, S.; Ueda, I.; Wenaus, T.; Atlas Collaboration

    2014-06-01

    This contribution summarizes evolution of the ATLAS Distributed Computing (ADC) Monitoring project during the LHC Run I. The ADC Monitoring targets at the three groups of customers: ADC Operations team to early identify malfunctions and escalate issues to an activity or a service expert, ATLAS national contacts and sites for the real-time monitoring and long-term measurement of the performance of the provided computing resources, and the ATLAS Management for long-term trends and accounting information about the ATLAS Distributed Computing resources. During the LHC Run I a significant development effort has been invested in standardization of the monitoring and accounting applications in order to provide extensive monitoring and accounting suite. ADC Monitoring applications separate the data layer and the visualization layer. The data layer exposes data in a predefined format. The visualization layer is designed bearing in mind visual identity of the provided graphical elements, and re-usability of the visualization bits across the different tools. A rich family of various filtering and searching options enhancing available user interfaces comes naturally with the data and visualization layer separation. With a variety of reliable monitoring data accessible through standardized interfaces, the possibility of automating actions under well defined conditions correlating multiple data sources has become feasible. In this contribution we discuss also about the automated exclusion of degraded resources and their automated recovery in various activities.

  4. Improving ATLAS computing resource utilization with HammerCloud

    CERN Document Server

    Schovancova, Jaroslava; The ATLAS collaboration

    2018-01-01

    HammerCloud is a framework to commission, test, and benchmark ATLAS computing resources and components of various distributed systems with realistic full-chain experiment workflows. HammerCloud contributes to ATLAS Distributed Computing (ADC) Operations and automation efforts, providing the automated resource exclusion and recovery tools, that help re-focus operational manpower to areas which have yet to be automated, and improve utilization of available computing resources. We present recent evolution of the auto-exclusion/recovery tools: faster inclusion of new resources in testing machinery, machine learning algorithms for anomaly detection, categorized resources as master vs. slave for the purpose of blacklisting, and a tool for auto-exclusion/recovery of resources triggered by Event Service job failures that is being extended to other workflows besides the Event Service. We describe how HammerCloud helped commissioning various concepts and components of distributed systems: simplified configuration of qu...

  5. The Next Generation ARC Middleware and ATLAS Computing Model

    International Nuclear Information System (INIS)

    Filipčič, Andrej; Cameron, David; Konstantinov, Aleksandr; Karpenko, Dmytro; Smirnova, Oxana

    2012-01-01

    The distributed NDGF Tier-1 and associated NorduGrid clusters are well integrated into the ATLAS computing environment but follow a slightly different paradigm than other ATLAS resources. The current paradigm does not divide the sites as in the commonly used hierarchical model, but rather treats them as a single storage endpoint and a pool of distributed computing nodes. The next generation ARC middleware with its several new technologies provides new possibilities in development of the ATLAS computing model, such as pilot jobs with pre-cached input files, automatic job migration between the sites, integration of remote sites without connected storage elements, and automatic brokering for jobs with non-standard resource requirements. ARC's data transfer model provides an automatic way for the computing sites to participate in ATLAS’ global task management system without requiring centralised brokering or data transfer services. The powerful API combined with Python and Java bindings can easily be used to build new services for job control and data transfer. Integration of the ARC core into the EMI middleware provides a natural way to implement the new services using the ARC components

  6. What Data to Co-register for Computing Atlases

    Science.gov (United States)

    Yeo, B.T. Thomas; Sabuncu, Mert; Mohlberg, Hartmut; Amunts, Katrin; Zilles, Karl; Golland, Polina; Fischl, Bruce

    2015-01-01

    We argue that registration should be thought of as a means to an end, and not as a goal by itself. In particular, we consider the problem of predicting the locations of hidden labels of a test image using observable features, given a training set with both the hidden labels and observable features. For example, the hidden labels could be segmentation labels or activation regions in fMRI, while the observable features could be sulcal geometry or MR intensity. We analyze a probabilistic framework for computing an optimal atlas, and the subsequent registration of a new subject using only the observable features to optimize the hidden label alignment to the training set. We compare two approaches for co-registering training images for the atlas construction: the traditional approach of only using observable features and a novel approach of only using hidden labels. We argue that the alternative approach is superior particularly when the relationship between the hidden labels and observable features is complex and unknown. As an application, we consider the task of registering cortical folds to optimize Brodmann area localization. We show that the alignment of the Brodmann areas improves by up to 25% when using the alternative atlas compared with the traditional atlas. To the best of our knowledge, these are the most accurate Brodmann area localization results (achieved via cortical fold registration) reported to date. PMID:26082678

  7. Integration of the Chinese HPC Grid in ATLAS Distributed Computing

    Science.gov (United States)

    Filipčič, A.; ATLAS Collaboration

    2017-10-01

    Fifteen Chinese High-Performance Computing sites, many of them on the TOP500 list of most powerful supercomputers, are integrated into a common infrastructure providing coherent access to a user through an interface based on a RESTful interface called SCEAPI. These resources have been integrated into the ATLAS Grid production system using a bridge between ATLAS and SCEAPI which translates the authorization and job submission protocols between the two environments. The ARC Computing Element (ARC-CE) forms the bridge using an extended batch system interface to allow job submission to SCEAPI. The ARC-CE was setup at the Institute for High Energy Physics, Beijing, in order to be as close as possible to the SCEAPI front-end interface at the Computing Network Information Center, also in Beijing. This paper describes the technical details of the integration between ARC-CE and SCEAPI and presents results so far with two supercomputer centers, Tianhe-IA and ERA. These two centers have been the pilots for ATLAS Monte Carlo Simulation in SCEAPI and have been providing CPU power since fall 2015.

  8. Integration of the Chinese HPC Grid in ATLAS Distributed Computing

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00081160; The ATLAS collaboration

    2016-01-01

    Fifteen Chinese High Performance Computing sites, many of them on the TOP500 list of most powerful supercomputers, are integrated into a common infrastructure providing coherent access to a user through an interface based on a RESTful interface called SCEAPI. These resources have been integrated into the ATLAS Grid production system using a bridge between ATLAS and SCEAPI which translates the authorization and job submission protocols between the two environments. The ARC Computing Element (ARC CE) forms the bridge using an extended batch system interface to allow job submission to SCEAPI. The ARC CE was setup at the Institute for High Energy Physics, Beijing, in order to be as close as possible to the SCEAPI front-end interface at the Computing Network Information Center, also in Beijing. This paper describes the technical details of the integration between ARC CE and SCEAPI and presents results so far with two supercomputer centers, Tianhe-IA and ERA. These two centers have been the pilots for ATLAS Monte C...

  9. Integration of the Chinese HPC Grid in ATLAS Distributed Computing

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00081160

    2017-01-01

    Fifteen Chinese High-Performance Computing sites, many of them on the TOP500 list of most powerful supercomputers, are integrated into a common infrastructure providing coherent access to a user through an interface based on a RESTful interface called SCEAPI. These resources have been integrated into the ATLAS Grid production system using a bridge between ATLAS and SCEAPI which translates the authorization and job submission protocols between the two environments. The ARC Computing Element (ARC-CE) forms the bridge using an extended batch system interface to allow job submission to SCEAPI. The ARC-CE was setup at the Institute for High Energy Physics, Beijing, in order to be as close as possible to the SCEAPI front-end interface at the Computing Network Information Center, also in Beijing. This paper describes the technical details of the integration between ARC-CE and SCEAPI and presents results so far with two supercomputer centers, Tianhe-IA and ERA. These two centers have been the pilots for ATLAS Monte C...

  10. Validation and computing and performance studies for the ATLAS simulation

    CERN Document Server

    Marshall, Z; The ATLAS collaboration

    2009-01-01

    We present the validation of the ATLAS simulation software pro ject. Software development is controlled by nightly builds and several levels of automatic tests to ensure stability. Computing validation, including CPU time, memory, and disk space required per event, is benchmarked for all software releases. Several different physics processes and event types are checked to thoroughly test all aspects of the detector simulation. The robustness of the simulation software is demonstrated by the production of 500 million events on the World-wide LHC Computing Grid in the last year.

  11. The Future of PanDA in ATLAS Distributed Computing

    CERN Document Server

    De, Kaushik; The ATLAS collaboration; Maeno, Tadashi; Nilsson, Paul; Oleynik, Danila; Panitkin, Sergey; Petrosyan, Artem; Schovancova, Jaroslava; Vaniachine, Alexandre; Wenaus, Torre

    2015-01-01

    Experiments at the Large Hadron Collider (LHC) face unprecedented computing challenges. Heterogeneous resources are distributed worldwide at hundreds of sites, thousands of physicists analyze the data remotely, the volume of processed data is beyond the exabyte scale, while data processing requires more than a few billion hours of computing usage per year. The PanDA (Production and Distributed Analysis) system was developed to meet the scale and complexity of LHC distributed computing for the ATLAS experiment. In the process, the old batch job paradigm of locally managed computing in HEP was discarded in favor of a far more automated, flexible and scalable model. The success of PanDA in ATLAS is leading to widespread adoption and testing by other experiments. PanDA is the first exascale workload management system in HEP, already operating at more than a million computing jobs per day, and processing over an exabyte of data in 2013. There are many new challenges that PanDA will face in the near future, in addi...

  12. ATLAS Distributed Computing Shift Operation in the first 2 full years of LHC data taking

    CERN Document Server

    Schovancová, J; The ATLAS collaboration; Elmsheuser, J; Jézéquel, S; Negri, G; Ozturk, N; Sakamoto, H; Slater, M; Smirnov, Y; Ueda, I; Van Der Ster, D C

    2012-01-01

    ATLAS Distributed Computing organized 3 teams to support data processing at Tier-0 facility at CERN, data reprocessing, data management operations, Monte Carlo simulation production, and physics analysis at the ATLAS computing centers located world-wide. In this paper we describe how these teams ensure that the ATLAS experiment data is delivered to the ATLAS physicists in a timely manner in the glamorous era of the LHC data taking. We describe experience with ways how to improve degraded service performance, we detail on the Distributed Analysis support over the exciting period of the computing model evolution.

  13. The future of PanDA in ATLAS distributed computing

    Science.gov (United States)

    De, K.; Klimentov, A.; Maeno, T.; Nilsson, P.; Oleynik, D.; Panitkin, S.; Petrosyan, A.; Schovancova, J.; Vaniachine, A.; Wenaus, T.

    2015-12-01

    Experiments at the Large Hadron Collider (LHC) face unprecedented computing challenges. Heterogeneous resources are distributed worldwide at hundreds of sites, thousands of physicists analyse the data remotely, the volume of processed data is beyond the exabyte scale, while data processing requires more than a few billion hours of computing usage per year. The PanDA (Production and Distributed Analysis) system was developed to meet the scale and complexity of LHC distributed computing for the ATLAS experiment. In the process, the old batch job paradigm of locally managed computing in HEP was discarded in favour of a far more automated, flexible and scalable model. The success of PanDA in ATLAS is leading to widespread adoption and testing by other experiments. PanDA is the first exascale workload management system in HEP, already operating at more than a million computing jobs per day, and processing over an exabyte of data in 2013. There are many new challenges that PanDA will face in the near future, in addition to new challenges of scale, heterogeneity and increasing user base. PanDA will need to handle rapidly changing computing infrastructure, will require factorization of code for easier deployment, will need to incorporate additional information sources including network metrics in decision making, be able to control network circuits, handle dynamically sized workload processing, provide improved visualization, and face many other challenges. In this talk we will focus on the new features, planned or recently implemented, that are relevant to the next decade of distributed computing workload management using PanDA.

  14. ATLAS experience with HEP software at the Argonne leadership computing facility

    International Nuclear Information System (INIS)

    Uram, Thomas D; LeCompte, Thomas J; Benjamin, D

    2014-01-01

    A number of HEP software packages used by the ATLAS experiment, including GEANT4, ROOT and ALPGEN, have been adapted to run on the IBM Blue Gene supercomputers at the Argonne Leadership Computing Facility. These computers use a non-x86 architecture and have a considerably less rich operating environment than in common use in HEP, but also represent a computing capacity an order of magnitude beyond what ATLAS is presently using via the LCG. The status and potential for making use of leadership-class computing, including the status of integration with the ATLAS production system, is discussed.

  15. ATLAS Experience with HEP Software at the Argonne Leadership Computing Facility

    CERN Document Server

    LeCompte, T; The ATLAS collaboration; Benjamin, D

    2014-01-01

    A number of HEP software packages used by the ATLAS experiment, including GEANT4, ROOT and ALPGEN, have been adapted to run on the IBM Blue Gene supercomputers at the Argonne Leadership Computing Facility. These computers use a non-x86 architecture and have a considerably less rich operating environment than in common use in HEP, but also represent a computing capacity an order of magnitude beyond what ATLAS is presently using via the LCG. The status and potential for making use of leadership-class computing, including the status of integration with the ATLAS production system, is discussed.

  16. An ATLAS distributed computing architecture for HL-LHC

    CERN Document Server

    Campana, Simone; The ATLAS collaboration

    2017-01-01

    The ATLAS collaboration started a process to understand the computing needs for the High Luminosity LHC era. Based on our best understanding of the computing model input parameters for the HL-LHC data taking conditions, results indicate the need for a larger amount of computational and storage resources with respect of the projection of constant yearly budget for computing in 2026. Filling the gap between the projection and the needs will be one of the challenges in preparation for LHC Run-4. While the gains from improvements in offline software will play a crucial role in this process, a different model for data processing, management, access and bookkeeping should also be envisaged to optimise resource usage. In this contribution we will describe a straw man of this model, founded on basic principles such as single event level granularity for data processing and virtual data. We will explain how the current architecture will evolve adiabatically into the future distributed computing system, through the prot...

  17. The ATLAS computing challenge for HL-LHC

    CERN Document Server

    Campana, Simone; The ATLAS collaboration

    2016-01-01

    The ATLAS experiment successfully commissioned a software and computing infrastructure to support the physics program during LHC Run 2. The next phases of the accelerator upgrade will present new challenges in the offline area. In particular, at High Luminosity LHC (also known as Run 4) the data taking conditions will be very demanding in terms of computing resources: between 5 and 10 KHz of event rate from the HLT to be reconstructed (and possibly further reprocessed) with an average pile-up of up to 200 events per collision and an equivalent number of simulated samples to be produced. The same parameters for the current run are lower by up to an order of magnitude. While processing and storage resources would need to scale accordingly, the funding situation allows one at best to consider a flat budget over the next few years for offline computing needs. In this paper we present a study quantifying the challenge in terms of computing resources for HL-LHC and present ideas about the possible evolution of the ...

  18. The Architecture and Administration of the ATLAS Online Computing System

    CERN Document Server

    Dobson, M; Ertorer, E; Garitaonandia, H; Leahu, L; Leahu, M; Malciu, I M; Panikashvili, E; Topurov, A; Ünel, G; Computing In High Energy and Nuclear Physics

    2006-01-01

    The needs of ATLAS experiment at the upcoming LHC accelerator, CERN, in terms of data transmission rates and processing power require a large cluster of computers (of the order of thousands) administrated and exploited in a coherent and optimal manner. Requirements like stability, robustness and fast recovery in case of failure impose a server-client system architecture with servers distributed in a tree like structure and clients booted from the network. For security reasons, the system should be accessible only through an application gateway and, also to ensure the autonomy of the system, the network services should be provided internally by dedicated machines in synchronization with CERN IT department's central services. The paper describes a small scale implementation of the system architecture that fits the given requirements and constraints. Emphasis will be put on the mechanisms and tools used to net boot the clients via the "Boot With Me" project and to synchronize information within the cluster via t...

  19. Analysis of Craniofacial Images using Computational Atlases and Deformation Fields

    DEFF Research Database (Denmark)

    Ólafsdóttir, Hildur

    2008-01-01

    purposes. The basis for most of the applications is non-rigid image registration. This approach brings one image into the coordinate system of another resulting in a deformation field describing the anatomical correspondence between the two images. A computational atlas representing the average anatomy...... of asymmetry. The analyses are applied to the study of three different craniofacial anomalies. The craniofacial applications include studies of Crouzon syndrome (in mice), unicoronal synostosis plagiocephaly and deformational plagiocephaly. Using the proposed methods, the thesis reveals novel findings about...... the craniofacial morphology and asymmetry of Crouzon mice. Moreover, a method to plan and evaluate treatment of children with deformational plagiocephaly, based on asymmetry assessment, is established. Finally, asymmetry in children with unicoronal synostosis is automatically assessed, confirming previous results...

  20. ATLAS

    Data.gov (United States)

    Federal Laboratory Consortium — ATLAS is a particle physics experiment at the Large Hadron Collider at CERN, the European Organization for Nuclear Research. Scientists from Brookhaven have played...

  1. Spanish ATLAS Tier-1 &Tier-2 perspective on computing over the next years

    CERN Document Server

    Gonzalez de la Hoz, Santiago; The ATLAS collaboration

    2018-01-01

    Since the beginning of the WLCG Project the Spanish ATLAS computer centres have contributed with reliable and stable resources as well as personnel for the ATLAS Collaboration. Our contribution to the ATLAS Tier2s and Tier1s computing resources (disk and CPUs) in the last 10 years has been around 5%, even though the Spanish contribution to the ATLAS detector construction as well as the number of authors are both close to 3%. In 2015 an international advisory committee recommended to revise our contribution according to the participation in the ATLAS experiment. With this scenario, we are optimising the federation of three sites located in Barcelona, Madrid and Valencia, taking into account that the ATLAS collaboration has developed workflows and tools to flexibly use all the resources available to the collaboration, where the Tiered structure is somehow vanishing. In this contribution, we would like to show the evolution and technical updates in the ATLAS Spanish Federated Tier2 and Tier1. Some developments w...

  2. Evolution of the ATLAS Distributed Computing during the LHC long shutdown

    CERN Document Server

    Campana, S; The ATLAS collaboration

    2013-01-01

    The ATLAS Distributed Computing project (ADC) was established in 2007 to develop and operate a framework, following the ATLAS computing model, to enable data storage, processing and bookkeeping on top of the WLCG distributed infrastructure. ADC development has always been driven by operations and this contributed to its success. The system has fulfilled the demanding requirements of ATLAS, daily consolidating worldwide up to 1PB of data and running more than 1.5 million payloads distributed globally, supporting almost one thousand concurrent distributed analysis users. Comprehensive automation and monitoring minimized the operational manpower required. The flexibility of the system to adjust to operational needs has been important to the success of the ATLAS physics program. The LHC shutdown in 2013-2015 affords an opportunity to improve the system in light of operational experience and scale it to cope with the demanding requirements of 2015 and beyond, most notably a much higher trigger rate and event pileu...

  3. Evolution of the ATLAS Distributed Computing system during the LHC Long shutdown

    CERN Document Server

    Campana, S; The ATLAS collaboration

    2014-01-01

    The ATLAS Distributed Computing project (ADC) was established in 2007 to develop and operate a framework, following the ATLAS computing model, to enable data storage, processing and bookkeeping on top of the WLCG distributed infrastructure. ADC development has always been driven by operations and this contributed to its success. The system has fulfilled the demanding requirements of ATLAS, daily consolidating worldwide up to 1PB of data and running more than 1.5 million payloads distributed globally, supporting almost one thousand concurrent distributed analysis users. Comprehensive automation and monitoring minimized the operational manpower required. The flexibility of the system to adjust to operational needs has been important to the success of the ATLAS physics program. The LHC shutdown in 2013-2015 affords an opportunity to improve the system in light of operational experience and scale it to cope with the demanding requirements of 2015 and beyond, most notably a much higher trigger rate and event pileu...

  4. ATLAS Distributed Computing Operations: Experience and improvements after 2 full years of data-taking

    International Nuclear Information System (INIS)

    Jézéquel, S; Stewart, G

    2012-01-01

    This paper summarizes operational experience and improvements in ATLAS computing infrastructure in 2010 and 2011. ATLAS has had 2 periods of data taking, with many more events recorded in 2011 than in 2010. It ran 3 major reprocessing campaigns. The activity in 2011 was similar to 2010, but scalability issues had to be addressed due to the increase in luminosity and trigger rate. Based on improved monitoring of ATLAS Grid computing, the evolution of computing activities (data/group production, their distribution and grid analysis) over time is presented. The main changes in the implementation of the computing model that will be shown are: the optimization of data distribution over the Grid, according to effective transfer rate and site readiness for analysis; the progressive dismantling of the cloud model, for data distribution and data processing; software installation migration to cvmfs; changing database access to a Frontier/squid infrastructure.

  5. The ATLAS Computing Agora: a resource web site for citizen science projects

    CERN Document Server

    Bourdarios, Claire; The ATLAS collaboration

    2016-01-01

    The ATLAS collaboration has recently setup a number of citizen science projects which have a strong IT component and could not have been envisaged without the growth of general public computing resources and network connectivity: event simulation through volunteer computing, algorithms improvement via Machine Learning challenges, event display analysis on citizen science platforms, use of open data, etc. Most of the interactions with volunteers are handled through message boards, but specific outreach material was also developed, giving an enhanced visibility to the ATLAS software and computing techniques, challenges and community. In this talk the Atlas Computing Agora (ACA) web platform will be presented as well as some of the specific material developed for some of the projects.

  6. The ATLAS Distributed Computing project for LHC Run-2 and beyond.

    CERN Document Server

    Di Girolamo, Alessandro; The ATLAS collaboration

    2015-01-01

    The ATLAS Distributed Computing infrastructure has evolved after the first period of LHC data taking in order to cope with the challenges of the upcoming LHC Run2. An increased data rate and computing demands of the Monte-Carlo simulation, as well as new approaches to ATLAS analysis, dictated a more dynamic workload management system (ProdSys2) and data management system (Rucio), overcoming the boundaries imposed by the design of the old computing model. In particular, the commissioning of new central computing system components was the core part of the migration toward the flexible computing model. The flexible computing utilization exploring the opportunistic resources such as HPC, cloud, and volunteer computing is embedded in the new computing model, the data access mechanisms have been enhanced with the remote access, and the network topology and performance is deeply integrated into the core of the system. Moreover a new data management strategy, based on defined lifetime for each dataset, has been defin...

  7. ATLAS computing operations within the GridKa Cloud

    International Nuclear Information System (INIS)

    Kennedy, J; Walker, R; Olszewski, A; Nderitu, S; Serfon, C; Duckeck, G

    2010-01-01

    The organisation and operations model of the ATLAS T1-T2 federation/Cloud associated to the GridKa T1 in Karlsruhe is described. Attention is paid to Cloud level services and the experience gained during the last years of operation. The ATLAS GridKa Cloud is large and divers spanning 5 countries, 2 ROC's and is currently comprised of 13 core sites. A well defined and tested operations model in such a Cloud is of the utmost importance. We have defined the core Cloud services required by the ATLAS experiment and ensured that they are performed in a managed and sustainable manner. Services such as Distributed Data Management involving data replication,deletion and consistency checks, Monte Carlo Production, software installation and data reprocessing are described in greater detail. In addition to providing these central services we have undertaken several Cloud level stress tests and developed monitoring tools to aid with Cloud diagnostics. Furthermore we have defined good channels of communication between ATLAS, the T1 and the T2's and have pro-active contributions from the T2 manpower. A brief introduction to the GridKa Cloud is provided followed by a more detailed discussion of the operations model and ATLAS services within the Cloud.

  8. Atlas-based delineation of lymph node levels in head and neck computed tomography images

    International Nuclear Information System (INIS)

    Commowick, Olivier; Gregoire, Vincent; Malandain, Gregoire

    2008-01-01

    Purpose: Radiotherapy planning requires accurate delineations of the tumor and of the critical structures. Atlas-based segmentation has been shown to be very efficient to automatically delineate brain critical structures. We therefore propose to construct an anatomical atlas of the head and neck region. Methods and materials: Due to the high anatomical variability of this region, an atlas built from a single image as for the brain is not adequate. We address this issue by building a symmetric atlas from a database of manually segmented images. First, we develop an atlas construction method and apply it to a database of 45 Computed Tomography (CT) images from patients with node-negative pharyngo-laryngeal squamous cell carcinoma manually delineated for radiotherapy. Then, we qualitatively and quantitatively evaluate the results generated by the built atlas based on Leave-One-Out framework on the database. Results: We present qualitative and quantitative results using this atlas construction method. The evaluation was performed on a subset of 12 patients among the original CT database of 45 patients. Qualitative results depict visually well delineated structures. The quantitative results are also good, with an error with respect to the best achievable results ranging from 0.196 to 0.404 with a mean of 0.253. Conclusions: These results show the feasibility of using such an atlas for radiotherapy planning. Many perspectives are raised from this work ranging from extensive validation to the construction of several atlases representing sub-populations, to account for large inter-patient variabilities, and populations with node-positive tumors

  9. Complete distributed computing environment for a HEP experiment: experience with ARC-connected infrastructure for ATLAS

    International Nuclear Information System (INIS)

    Read, A; Taga, A; O-Saada, F; Pajchel, K; Samset, B H; Cameron, D

    2008-01-01

    Computing and storage resources connected by the Nordugrid ARC middleware in the Nordic countries, Switzerland and Slovenia are a part of the ATLAS computing Grid. This infrastructure is being commissioned with the ongoing ATLAS Monte Carlo simulation production in preparation for the commencement of data taking in 2008. The unique non-intrusive architecture of ARC, its straightforward interplay with the ATLAS Production System via the Dulcinea executor, and its performance during the commissioning exercise is described. ARC support for flexible and powerful end-user analysis within the GANGA distributed analysis framework is also shown. Whereas the storage solution for this Grid was earlier based on a large, distributed collection of GridFTP-servers, the ATLAS computing design includes a structured SRM-based system with a limited number of storage endpoints. The characteristics, integration and performance of the old and new storage solutions are presented. Although the hardware resources in this Grid are quite modest, it has provided more than double the agreed contribution to the ATLAS production with an efficiency above 95% during long periods of stable operation

  10. Complete distributed computing environment for a HEP experiment: experience with ARC-connected infrastructure for ATLAS

    Energy Technology Data Exchange (ETDEWEB)

    Read, A; Taga, A; O-Saada, F; Pajchel, K; Samset, B H; Cameron, D [Department of Physics, University of Oslo, P.b. 1048 Blindern, N-0316 Oslo (Norway)], E-mail: a.l.read@fys.uio.no

    2008-07-15

    Computing and storage resources connected by the Nordugrid ARC middleware in the Nordic countries, Switzerland and Slovenia are a part of the ATLAS computing Grid. This infrastructure is being commissioned with the ongoing ATLAS Monte Carlo simulation production in preparation for the commencement of data taking in 2008. The unique non-intrusive architecture of ARC, its straightforward interplay with the ATLAS Production System via the Dulcinea executor, and its performance during the commissioning exercise is described. ARC support for flexible and powerful end-user analysis within the GANGA distributed analysis framework is also shown. Whereas the storage solution for this Grid was earlier based on a large, distributed collection of GridFTP-servers, the ATLAS computing design includes a structured SRM-based system with a limited number of storage endpoints. The characteristics, integration and performance of the old and new storage solutions are presented. Although the hardware resources in this Grid are quite modest, it has provided more than double the agreed contribution to the ATLAS production with an efficiency above 95% during long periods of stable operation.

  11. Evolution of the Atlas data and computing model for a Tier-2 in the EGI infrastructure

    CERN Document Server

    Fernandez, A; The ATLAS collaboration; AMOROS, G; VILLAPLANA, M; FASSI, F; KACI, M; LAMAS, A; OLIVER, E; SALT, J; SANCHEZ, J; SANCHEZ, V

    2012-01-01

    ABSTRAC ISCG 2012 Evolution of the Atlas data and computing model for a Tier2 in the EGI infrastructure During last years the Atlas computing model has moved from a more strict design, where every Tier2 had a liaison and a network dependence from a Tier1, to a more meshed approach where every cloud could be connected. Evolution of ATLAS data models requires changes in ATLAS Tier2s policy for the data replication, dynamic data caching and remote data access. It also requires rethinking the network infrastructure to enable any Tier2 and associated Tier3 to easily connect to any Tier1 or Tier2. Tier2s are becoming more and more important in the ATLAS computing model as it allows more data to be readily accessible for analysis jobs to all users, independently of their geographical location. The Tier2s disk space has been reserved for real, simulated, calibration and alignment, group, and user data. A buffer disk space is needed for input and output data for simulations jobs. Tier2s are going to be used more effic...

  12. ATLAS

    CERN Multimedia

    Akhnazarov, V; Canepa, A; Bremer, J; Burckhart, H; Cattai, A; Voss, R; Hervas, L; Kaplon, J; Nessi, M; Werner, P; Ten kate, H; Tyrvainen, H; Vandelli, W; Krasznahorkay, A; Gray, H; Alvarez gonzalez, B; Eifert, T F; Rolando, G; Oide, H; Barak, L; Glatzer, J; Backhaus, M; Schaefer, D M; Maciejewski, J P; Milic, A; Jin, S; Von torne, E; Limbach, C; Medinnis, M J; Gregor, I; Levonian, S; Schmitt, S; Waananen, A; Monnier, E; Muanza, S G; Pralavorio, P; Talby, M; Tiouchichine, E; Tocut, V M; Rybkin, G; Wang, S; Lacour, D; Laforge, B; Ocariz, J H; Bertoli, W; Malaescu, B; Sbarra, C; Yamamoto, A; Sasaki, O; Koriki, T; Hara, K; Da silva gomes, A; Carvalho maneira, J; Marcalo da palma, A; Chekulaev, S; Tikhomirov, V; Snesarev, A; Buzykaev, A; Maslennikov, A; Peleganchuk, S; Sukharev, A; Kaplan, B E; Swiatlowski, M J; Nef, P D; Schnoor, U; Oakham, G F; Ueno, R; Orr, R S; Abouzeid, O; Haug, S; Peng, H; Kus, V; Vitek, M; Temming, K K; Dang, N P; Meier, K; Schultz-coulon, H; Geisler, M P; Sander, H; Schaefer, U; Ellinghaus, F; Rieke, S; Nussbaumer, A; Liu, Y; Richter, R; Kortner, S; Fernandez-bosman, M; Ullan comes, M; Espinal curull, J; Chiriotti alvarez, S; Caubet serrabou, M; Valladolid gallego, E; Kaci, M; Carrasco vela, N; Lancon, E C; Besson, N E; Gautard, V; Bracinik, J; Bartsch, V C; Potter, C J; Lester, C G; Moeller, V A; Rosten, J; Crooks, D; Mathieson, K; Houston, S C; Wright, M; Jones, T W; Harris, O B; Byatt, T J; Dobson, E; Hodgson, P; Hodgkinson, M C; Dris, M; Karakostas, K; Ntekas, K; Oren, D; Duchovni, E; Etzion, E; Oren, Y; Ferrer, L M; Testa, M; Doria, A; Merola, L; Sekhniaidze, G; Giordano, R; Ricciardi, S; Milazzo, A; Falciano, S; De pedis, D; Dionisi, C; Veneziano, S; Cardarelli, R; Verzegnassi, C; Soualah, R; Ochi, A; Ohshima, T; Kishiki, S; Linde, F L; Vreeswijk, M; Werneke, P; Muijs, A; Vankov, P H; Jansweijer, P P M; Dale, O; Lund, E; Bruckman de renstrom, P; Dabrowski, W; Adamek, J D; Wolters, H; Micu, L; Pantea, D; Tudorache, V; Mjoernmark, J; Klimek, P J; Ferrari, A; Abdinov, O; Akhoundov, A; Hashimov, R; Shelkov, G; Khubua, J; Ladygin, E; Lazarev, A; Glagolev, V; Dedovich, D; Lykasov, G; Zhemchugov, A; Zolnikov, Y; Ryabenko, M; Sivoklokov, S; Vasilyev, I; Shalimov, A; Lobanov, M; Paramoshkina, E; Mosidze, M; Bingul, A; Nodulman, L J; Guarino, V J; Yoshida, R; Drake, G R; Calafiura, P; Haber, C; Quarrie, D R; Alonso, J R; Anderson, C; Evans, H; Lammers, S W; Baubock, M; Anderson, K; Petti, R; Suhr, C A; Linnemann, J T; Richards, R A; Tollefson, K A; Holzbauer, J L; Stoker, D P; Pier, S; Nelson, A J; Isakov, V; Martin, A J; Adelman, J A; Paganini, M; Gutierrez, P; Snow, J M; Pearson, B L; Cleland, W E; Savinov, V; Wong, W; Goodson, J J; Li, H; Lacey, R A; Gordeev, A; Gordon, H; Lanni, F; Nevski, P; Rescia, S; Kierstead, J A; Liu, Z; Yu, W W H; Bensinger, J; Hashemi, K S; Bogavac, D; Cindro, V; Hoeferkamp, M R; Coelli, S; Iodice, M; Piegaia, R N; Alonso, F; Wahlberg, H P; Barberio, E L; Limosani, A; Rodd, N L; Jennens, D T; Hill, E C; Pospisil, S; Smolek, K; Schaile, D A; Rauscher, F G; Adomeit, S; Mattig, P M; Wahlen, H; Volkmer, F; Calvente lopez, S; Sanchis peris, E J; Pallin, D; Podlyski, F; Says, L; Boumediene, D E; Scott, W; Phillips, P W; Greenall, A; Turner, P; Gwilliam, C B; Kluge, T; Wrona, B; Sellers, G J; Millward, G; Adragna, P; Hartin, A; Alpigiani, C; Piccaro, E; Bret cano, M; Hughes jones, R E; Mercer, D; Oh, A; Chavda, V S; Carminati, L; Cavasinni, V; Fedin, O; Patrichev, S; Ryabov, Y; Nesterov, S; Grebenyuk, O; Sasso, J; Mahmood, H; Polsdofer, E; Dai, T; Ferretti, C; Liu, H; Hegazy, K H; Benjamin, D P; Zobernig, G; Ban, J; Brooijmans, G H; Keener, P; Williams, H H; Le geyt, B C; Hines, E J; Fadeyev, V; Schumm, B A; Law, A T; Kuhl, A D; Neubauer, M S; Shang, R; Gagliardi, G; Calabro, D; Conta, C; Zinna, M; Jones, G; Li, J; Stradling, A R; Hadavand, H K; Mcguigan, P; Chiu, P; Baldelomar, E; Stroynowski, R A; Kehoe, R L; De groot, N; Timmermans, C; Lach-heb, F; Addy, T N; Nakano, I; Moreno lopez, D; Grosse-knetter, J; 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Wickens, F J; Martin, V J; Jackson, J N; Prichard, P; Kretzschmar, J; Martin, A J; Walker, C J; Potter, K M; Kourkoumelis, C; Tzamarias, S; Houiris, A G; Iliadis, D; Fanti, M; Bertolucci, F; Maleev, V; Sultanov, S; Rosenberg, E I; Krumnack, N E; Bieganek, C; Diehl, E B; Mc kee, S P; Eppig, A P; Harper, D R; Liu, C; Schwarz, T A; Mazor, B; Looper, K A; Wiedenmann, W; Huang, P; Stahlman, J M; Battaglia, M; Nielsen, J A; Zhao, T; Khanov, A; Kaushik, V S; Vichou, E; Liss, A M; Gemme, C; Morettini, P; Parodi, F; Passaggio, S; Rossi, L; Kuzhir, P; Ignatenko, A; Ferrari, R; Spairani, M; Pianori, E; Sekula, S J; Firan, A I; Cao, T; Hetherly, J W; Gouighri, M; Vassilakopoulos, V; Long, M C; Shimojima, M; Sawyer, L H; Brummett, R E; Losada, M A; Schorlemmer, A L; Mantoani, M; Bawa, H S; Mornacchi, G; Nicquevert, B; Palestini, S; Stapnes, S; Veness, R; Kotamaki, M J; Sorde, C; Iengo, P; Campana, S; Goossens, L; Zajacova, Z; Pribyl, L; Poveda torres, J; Marzin, A; Conti, G; Carrillo montoya, G D; Kroseberg, J; Gonella, L; Velz, T; Schmitt, S; Lobodzinska, E M; Lovschall-jensen, A E; Galster, G; Perrot, G; Cailles, M; Berger, N; Barnovska, Z; Delsart, P; Lleres, A; Tisserant, S; Grivaz, J; Matricon, P; Bellagamba, L; Bertin, A; Bruschi, M; De castro, S; Semprini cesari, N; Fabbri, L; Rinaldi, L; Quayle, W B; Truong, T N L; Kondo, T; Haruyama, T; Ng, C; Do valle wemans, A; Almeida veloso, F M; Konovalov, S; Ziegler, J M; Su, D; Lukas, W; Prince, S; Ortega urrego, E J; Teuscher, R J; Knecht, N; Pretzl, K; Borer, C; Gadomski, S; Koch, B; Kuleshov, S; Brooks, W K; Antos, J; Kulkova, I; Chudoba, J; Chyla, J; Tomasek, L; Bazalova, M; Messmer, I; Tobias, J; Sundermann, J E; Kuehn, S S; Kluge, E; Scharf, V L; Barillari, T; Kluth, S; Menke, S; Weigell, P; Schwegler, P; Ziolkowski, M; Casado lechuga, P M; Garcia, C; Sanchez, J; Costa mezquita, M J; Valero biot, J A; Laporte, J; Nikolaidou, R; Virchaux, M; Nguyen, V T H; Charlton, D; Harrison, K; Slater, M W; Newman, P R; Parker, A M; Ward, P; Mcgarvie, S A; Kilvington, G J; D'auria, S; O'shea, V; Mcglone, H M; Fox, H; Henderson, R; Kartvelishvili, V; Davies, B; Sherwood, P; Fraser, J T; Lancaster, M A; Tseng, J C; Hays, C P; Apolle, R; Dixon, S D; Parker, K A; Gazis, E; Papadopoulou, T; Panagiotopoulou, E; Karastathis, N; Hershenhorn, A D; Milov, A; Groth-jensen, J; Bilokon, H; Miscetti, S; Canale, V; Rebuzzi, D M; Capua, M; Bagnaia, P; De salvo, A; Gentile, S; Safai tehrani, F; Solfaroli camillocci, E; Sasao, N; Tsunada, K; Massaro, G; Magrath, C A; Van kesteren, Z; Beker, M G; Van den wollenberg, W; Bugge, L; Buran, T; Read, A L; Gjelsten, B K; Banas, E A; Turnau, J; Derendarz, D K; Kisielewska, D; Chesneanu, D; Rotaru, M; Maurer, J B; Wong, M L; Lund-jensen, B; Asman, B; Jon-and, K B; Silverstein, S B; Johansen, M; Alexandrov, I; Iatsounenko, I; Krumshteyn, Z; Peshekhonov, V; Rybaltchenko, K; Samoylov, V; Cheplakov, A; Kekelidze, G; Lyablin, M; Teterine, V; Bednyakov, V; Kruchonak, U; Shiyakova, M M; Demichev, M; Denisov, S P; Fenyuk, A; Djobava, T; Salukvadze, G; Cetin, S A; Brau, B P; Pais, P R; Proudfoot, J; Van gemmeren, P; Zhang, Q; Beringer, J A; Ely, R; Leggett, C; Pengg, F X; Barnett, M R; Quick, R E; Williams, S; Gardner jr, R W; Huston, J; Brock, R; Wanotayaroj, C; Unel, G N; Taffard, A C; Frate, M; Baker, K O; Tipton, P L; Hutchison, A; Walsh, B J; Norberg, S R; Su, J; Tsybyshev, D; Caballero bejar, J; Ernst, M U; Wellenstein, H; Vudragovic, D; Vidic, I; Gorelov, I V; Toms, K; Alimonti, G; Petrucci, F; Kolanoski, H; Smith, J; Jeng, G; Watson, I J; Guimaraes ferreira, F; Miranda vieira xavier, F; Araujo pereira, R; Poffenberger, P; Sopko, V; Elmsheuser, J; Wittkowski, J; Glitza, K; Gorfine, G W; Ferrer soria, A; Fuster verdu, J A; Sanchis lozano, A; Reinmuth, G; Busato, E; Haywood, S J; Mcmahon, S J; Qian, W; Villani, E G; Laycock, P J; Poll, A J; Rizvi, E S; Foster, J M; Loebinger, F; Forti, A; Plano, W G; Brown, G J A; Kordas, K; Vegni, G; Ohsugi, T; Iwata, Y; Cherkaoui el moursli, R; Sahin, M; Akyazi, E; Carlsen, A; Kanwal, B; Cochran jr, J H; Aronnax, M V; Lockner, M J; Zhou, B; Levin, D S; Weaverdyck, C J; Grom, G F; Rudge, A; Ebenstein, W L; Jia, B; Yamaoka, J; Jared, R C; Wu, S L; Banerjee, S; Lu, Q; Hughes, E W; Alkire, S P; Degenhardt, J D; Lipeles, E D; Spencer, E N; Savine, A; Cheu, E C; Lampl, W; Veatch, J R; Roberts, K; Atkinson, M J; Odino, G A; Polesello, G; Martin, T; White, A P; Stephens, R; Grinbaum sarkisyan, E; Vartapetian, A; Yu, J; Sosebee, M; Thilagar, P A; Spurlock, B; Bonde, R; Filthaut, F; Klok, P; Hoummada, A; Ouchrif, M; Pellegrini, G; Rafi tatjer, J M; Navarro, G A; Blumenschein, U; Weingarten, J C; Mueller, D; Graber, L; Gao, Y; Bode, A; Capeans garrido, M D M; Carli, T; Wells, P; Beltramello, O; Vuillermet, R; Dudarev, A; Salzburger, A; Torchiani, C I; Serfon, C L G; Sloper, J E; Duperrier, G; Lilova, P T; Knecht, M O; Lassnig, M; Anders, G; Deviveiros, P; Young, C; Sforza, F; Shaochen, C; Lu, F; Wermes, N; Wienemann, P; Schwindt, T; Hansen, P H; Hansen, J B; Pingel, A M; Massol, N; Elles, S L; Hallewell, G D; Rozanov, A; Vacavant, L; Fournier, D A; Poggioli, L; Puzo, P M; Tanaka, R; Escalier, M A; Makovec, N; Rezynkina, K; De cecco, S; Cavalleri, P G; Massa, I; Zoccoli, A; Tanaka, S; Odaka, S; Mitsui, S; Tomasio pina, J A; Santos, H F; Satsounkevitch, I; Harkusha, S; Baranov, S; Nechaeva, P; Kayumov, F; Kazanin, V; Asai, M; Mount, R P; Nelson, T K; Smith, D; Kenney, C J; Malone, C M; Kobel, M; Friedrich, F; Grohs, J P; Jais, W J; O'neil, D C; Warburton, A T; Vincter, M; Mccarthy, T G; Groer, L S; Pham, Q T; Taylor, W J; La marra, D; Perrin, E; Wu, X; Bell, W H; Delitzsch, C M; Feng, C; Zhu, C; Tokar, S; Bruncko, D; Kupco, A; Marcisovsky, M; Jakoubek, T; Bruneliere, R; Aktas, A; Narrias villar, D I; Tapprogge, S; Mattmann, J; Kroha, H; Crespo, J; Korolkov, I; Cavallaro, E; Cabrera urban, S; Mitsou, V; Kozanecki, W; Mansoulie, B; Pabot, Y; Etienvre, A; Bauer, F; Chevallier, F; Bouty, A R; Watkins, P; Watson, A; Faulkner, P J W; Curtis, C J; Murillo quijada, J A; Grout, Z J; Chapman, J D; Cowan, G D; George, S; Boisvert, V; Mcmahon, T R; Doyle, A T; Thompson, S A; Britton, D; Smizanska, M; Campanelli, M; Butterworth, J M; Loken, J; Renton, P; Barr, A J; Issever, C; Short, D; Crispin ortuzar, M; Tovey, D R; French, R; Rozen, Y; Alexander, G; Kreisel, A; Conventi, F; Raulo, A; Schioppa, M; Susinno, G; Tassi, E; Giagu, S; Luci, C; Nisati, A; Cobal, M; Ishikawa, A; Jinnouchi, O; Bos, K; Verkerke, W; Vermeulen, J; Van vulpen, I B; Kieft, G; Mora, K D; Olsen, F; Rohne, O M; Pajchel, K; Nilsen, J K; Wosiek, B K; Wozniak, K W; Badescu, E; Jinaru, A; Bohm, C; Johansson, E K; Sjoelin, J B R; Clement, C; Buszello, C P; Huseynova, D; Boyko, I; Popov, B; Poukhov, O; Vinogradov, V; Tsiareshka, P; Skvorodnev, N; Soldatov, A; Chuguev, A; Gushchin, V; Yazici, E; Lutz, M S; Malon, D; Vanyashin, A; Lavrijsen, W; Spieler, H; Biesiada, J L; Bahr, M; Kong, J; Tatarkhanov, M; Ogren, H; Van kooten, R J; Cwetanski, P; Butler, J M; Shank, J T; Chakraborty, D; Ermoline, I; Sinev, N; Whiteson, D O; Corso radu, A; Huang, J; Werth, M P; Kastoryano, M; Meirose da silva costa, B; Namasivayam, H; Hobbs, J D; Schamberger jr, R D; Guo, F; Potekhin, M; Popovic, D; Gorisek, A; Sokhrannyi, G; Hofsajer, I W; Mandelli, L; Ceradini, F; Graziani, E; Giorgi, F; Zur nedden, M E G; Grancagnolo, S; Volpi, M; Nunes hanninger, G; Rados, P K; Milesi, M; Cuthbert, C J; Black, C W; Fink grael, F; Fincke-keeler, M; Keeler, R; Kowalewski, R V; Berghaus, F O; Qi, M; Davidek, T; Tas, P; Jakubek, J; Duckeck, G; Walker, R; Mitterer, C A; Harenberg, T; Sandvoss, S A; Del peso, J; Llorente merino, J; Gonzalez millan, V; Irles quiles, A; Crouau, M; Gris, P L Y; Liauzu, S; Romano saez, S M; Gallop, B J; Jones, T J; Austin, N C; Morris, J; Duerdoth, I; Thompson, R J; Kelly, M P; Leisos, A; Garas, A; Pizio, C; Venda pinto, B A; Kudin, L; Qian, J; Wilson, A W; Mietlicki, D; Long, J D; Sang, Z; Arms, K E; Rahimi, A M; Moss, J J; Oh, S H; Parker, S I; Parsons, J; Cunitz, H; Vanguri, R S; Sadrozinski, H; Lockman, W S; Martinez-mc kinney, G; Goussiou, A; Jones, A; Lie, K; Hasegawa, Y; Olcese, M; Gilewsky, V; Harrison, P F; Janus, M; Spangenberg, M; De, K; Ozturk, N; Pal, A K; Darmora, S; Bullock, D J; Oviawe, O; Derkaoui, J E; Rahal, G; Sircar, A; Frey, A S; Stolte, P; Rosien, N; Zoch, K; Li, L; Schouten, D W; Catinaccio, A; Ciapetti, M; Delruelle, N; Ellis, N; Farthouat, P; Hoecker, A; Klioutchnikova, T; Macina, D; Malyukov, S; Spiwoks, R D; Unal, G P; Vandoni, G; Petersen, B A; Pommes, K; Nairz, A M; Wengler, T; Mladenov, D; Solans sanchez, C A; Lantzsch, K; Schmieden, K; Jakobsen, S; Ritsch, E; Sciuccati, A; Alves dos santos, A M; Ouyang, Q; Zhou, M; Brock, I C; Janssen, J; Katzy, J; Anders, C F; Nilsson, B S; Bazan, A; Di ciaccio, L; Yildizkaya, T; Collot, J; Malek, F; Trocme, B S; Breugnon, P; Godiot, S; Adam bourdarios, C; Coulon, J; Duflot, L; Petroff, P G; Zerwas, D; Lieuvin, M; Calderini, G; Laporte, D; Ocariz, J; Gabrielli, A; Ohska, T K; Kurochkin, Y; Kantserov, V; Vasilyeva, L; Speransky, M; Smirnov, S; Antonov, A; Bulekov, O; Tikhonov, Y; Sargsyan, L; Vardanyan, G; Budick, B; Kocian, M L; Luitz, S; Young, C C; Grenier, P J; Kelsey, M; Black, J E; Kneringer, E; Jussel, P; Horton, A J; Beaudry, J; Chandra, A; Ereditato, A; Topfel, C M; Mathieu, R; Bucci, F; Muenstermann, D; White, R M; He, M; Urban, J; Straka, M; Vrba, V; Schumacher, M; Parzefall, U; Mahboubi, K; Sommer, P O; Koepke, L H; Bethke, S; Moser, H; Wiesmann, M; Walkowiak, W A; Fleck, I J; Martinez-perez, M; Sanchez sanchez, C A; Jorgensen roca, S; Accion garcia, E; Sainz ruiz, C A; Valls ferrer, J A; Amoros vicente, G; Vives torrescasana, R; Ouraou, A; Formica, A; Hassani, S; Watson, M F; Cottin buracchio, G F; Bussey, P J; Saxon, D; Ferrando, J E; Collins-tooth, C L; Hall, D C; Cuhadar donszelmann, T; Dawson, I; Duxfield, R; Argyropoulos, T; Brodet, E; Livneh, R; Shougaev, K; Reinherz, E I; Guttman, N; Beretta, M M; Vilucchi, E; Aloisio, A; Patricelli, S; Caprio, M; Cevenini, F; De vecchi, C; 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Protopopescu, S D; Snyder, S S; Undrus, A; Popescu, R N; Begel, M A; Blocker, C A; Amelung, C; Mandic, I; Macek, B; Tucker, B H; Citterio, M; Troncon, C; Orestano, D; Taccini, C; Romeo, G L; Dova, M T; Taylor, G N; Gesualdi manhaes, A; Mcpherson, R A; Sobie, R; Taylor, R P; Dolezal, Z; Kodys, P; Slovak, R; Sopko, B; Vacek, V; Sanders, M P; Hertenberger, R; Meineck, C; Becks, K; Kind, P; Sandhoff, M; Cantero garcia, J; De la torre perez, H; Castillo gimenez, V; Ros, E; Hernandez jimenez, Y; Chadelas, R; Santoni, C; Washbrook, A J; O'brien, B J; Wynne, B M; Mehta, A; Vossebeld, J H; Landon, M; Teixeira dias castanheira, M; Cerrito, L; Keates, J R; Fassouliotis, D; Chardalas, M; Manousos, A; Grachev, V; Seliverstov, D; Sedykh, E; Cakir, O; Ciftci, R; Edson, W; Prell, S A; Rosati, M; Stroman, T; Jiang, H; Neal, H A; Li, X; Gan, K K; Smith, D S; Kruse, M C; Ko, B R; Leung fook cheong, A M; Cole, B; Angerami, A R; Greene, Z S; Kroll, J I; Van berg, R P; Forbush, D A; Lubatti, H; Raisher, J; Shupe, M A; Wolin, S; Oshita, H; Gaudio, G; Das, R; Konig, A C; Croft, V A; Harvey, A; Maaroufi, F; Melo, I; Greenwood jr, Z D; Shabalina, E; Mchedlidze, G; Drechsler, E; Rieger, J K; Blackston, M; Colombo, T

    2002-01-01

    % ATLAS \\\\ \\\\ ATLAS is a general-purpose experiment for recording proton-proton collisions at LHC. The ATLAS collaboration consists of 144 participating institutions (June 1998) with more than 1750~physicists and engineers (700 from non-Member States). The detector design has been optimized to cover the largest possible range of LHC physics: searches for Higgs bosons and alternative schemes for the spontaneous symmetry-breaking mechanism; searches for supersymmetric particles, new gauge bosons, leptoquarks, and quark and lepton compositeness indicating extensions to the Standard Model and new physics beyond it; studies of the origin of CP violation via high-precision measurements of CP-violating B-decays; high-precision measurements of the third quark family such as the top-quark mass and decay properties, rare decays of B-hadrons, spectroscopy of rare B-hadrons, and $ B ^0 _{s} $-mixing. \\\\ \\\\The ATLAS dectector, shown in the Figure includes an inner tracking detector inside a 2~T~solenoid providing an axial...

  13. Evolution of the ATLAS distributed computing system during the LHC long shutdown

    Science.gov (United States)

    Campana, S.; Atlas Collaboration

    2014-06-01

    The ATLAS Distributed Computing project (ADC) was established in 2007 to develop and operate a framework, following the ATLAS computing model, to enable data storage, processing and bookkeeping on top of the Worldwide LHC Computing Grid (WLCG) distributed infrastructure. ADC development has always been driven by operations and this contributed to its success. The system has fulfilled the demanding requirements of ATLAS, daily consolidating worldwide up to 1 PB of data and running more than 1.5 million payloads distributed globally, supporting almost one thousand concurrent distributed analysis users. Comprehensive automation and monitoring minimized the operational manpower required. The flexibility of the system to adjust to operational needs has been important to the success of the ATLAS physics program. The LHC shutdown in 2013-2015 affords an opportunity to improve the system in light of operational experience and scale it to cope with the demanding requirements of 2015 and beyond, most notably a much higher trigger rate and event pileup. We will describe the evolution of the ADC software foreseen during this period. This includes consolidating the existing Production and Distributed Analysis framework (PanDA) and ATLAS Grid Information System (AGIS), together with the development and commissioning of next generation systems for distributed data management (DDM/Rucio) and production (Prodsys-2). We will explain how new technologies such as Cloud Computing and NoSQL databases, which ATLAS investigated as R&D projects in past years, will be integrated in production. Finally, we will describe more fundamental developments such as breaking job-to-data locality by exploiting storage federations and caches, and event level (rather than file or dataset level) workload engines.

  14. Evolution of the ATLAS distributed computing system during the LHC long shutdown

    International Nuclear Information System (INIS)

    Campana, S

    2014-01-01

    The ATLAS Distributed Computing project (ADC) was established in 2007 to develop and operate a framework, following the ATLAS computing model, to enable data storage, processing and bookkeeping on top of the Worldwide LHC Computing Grid (WLCG) distributed infrastructure. ADC development has always been driven by operations and this contributed to its success. The system has fulfilled the demanding requirements of ATLAS, daily consolidating worldwide up to 1 PB of data and running more than 1.5 million payloads distributed globally, supporting almost one thousand concurrent distributed analysis users. Comprehensive automation and monitoring minimized the operational manpower required. The flexibility of the system to adjust to operational needs has been important to the success of the ATLAS physics program. The LHC shutdown in 2013-2015 affords an opportunity to improve the system in light of operational experience and scale it to cope with the demanding requirements of 2015 and beyond, most notably a much higher trigger rate and event pileup. We will describe the evolution of the ADC software foreseen during this period. This includes consolidating the existing Production and Distributed Analysis framework (PanDA) and ATLAS Grid Information System (AGIS), together with the development and commissioning of next generation systems for distributed data management (DDM/Rucio) and production (Prodsys-2). We will explain how new technologies such as Cloud Computing and NoSQL databases, which ATLAS investigated as R and D projects in past years, will be integrated in production. Finally, we will describe more fundamental developments such as breaking job-to-data locality by exploiting storage federations and caches, and event level (rather than file or dataset level) workload engines.

  15. ATLAS FTK a – very complex – custom super computer

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00008600; The ATLAS collaboration

    2016-01-01

    In the ever increasing pile-up LHC environment advanced techniques of analyzing the data are implemented in order to increase the rate of relevant physics processes with respect to background processes. The Fast TracKer (FTK) is a track finding implementation at hardware level that is designed to deliver full-scan tracks with PT above 1GeV to the ATLAS trigger system for every L1 accept (at a maximum rate of 100kHz). In order to achieve this performance a highly parallel system was designed and now it is under installation in ATLAS. In the beginning of 2016 it will provide tracks for the trigger system in a region covering the central part of the ATLAS detector, and during the year it's coverage will be extended to the full detector coverage. The system relies on matching hits coming from the silicon tracking detectors against 1 billion patterns stored in specially designed ASICS chips (Associative memory - AM06). In a first stage coarse resolution hits are matched against the patterns and the accepted hits u...

  16. Enabling the ATLAS Experiment at the LHC for High Performance Computing

    CERN Document Server

    AUTHOR|(CDS)2091107; Ereditato, Antonio

    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 com...

  17. Evolution of the ATLAS PanDA Workload Management System for Exascale Computational Science

    OpenAIRE

    Maeno, T; De, K; Klimentov, A; Nilsson, P; Oleynik, D; Panitkin, S; Petrosyan, A; Schovancova, J; Vaniachine, A; Wenaus, T; Yu, D

    2013-01-01

    An important foundation underlying the impressive success of data processing and analysis in the ATLAS experiment [1] at the LHC [2] is the Production and Distributed Analysis (PanDA) workload management system [3]. PanDA was designed specifically for ATLAS and proved to be highly successful in meeting all the distributed computing needs of the experiment. However, the core design of PanDA is not experiment specific. The PanDA workload management system is capable of meeting the needs of othe...

  18. The Future of Distributed Computing Systems in ATLAS: Boldly Venturing Beyond Grids

    CERN Document Server

    Barreiro Megino, Fernando Harald; The ATLAS collaboration

    2018-01-01

    The Production and Distributed Analysis system (PanDA) for the ATLAS experiment at the Large Hadron Collider has seen big changes over the past couple of years to accommodate new types of distributed computing resources: clouds, HPCs, volunteer computers and other external resources. While PanDA was originally designed for fairly homogeneous resources available through the Worldwide LHC Computing Grid, the new resources are heterogeneous, at diverse scales and with diverse interfaces. Up to a fifth of the resources available to ATLAS are of such new types and require special techniques for integration into PanDA. In this talk, we present the nature and scale of these resources. We provide an overview of the various challenges faced, spanning infrastructure, software distribution, workload requirements, scaling requirements, workflow management, data management, network provisioning, and associated software and computing facilities. We describe the strategies for integrating these heterogeneous resources into ...

  19. Getting the Most from Distributed Resources With an Analytics Platform for ATLAS Computing Services

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00225336; The ATLAS collaboration; Gardner, Robert; Bryant, Lincoln

    2016-01-01

    To meet a sharply increasing demand for computing resources for LHC Run 2, ATLAS distributed computing systems reach far and wide to gather CPU resources and storage capacity to execute an evolving ecosystem of production and analysis workflow tools. Indeed more than a hundred computing sites from the Worldwide LHC Computing Grid, plus many “opportunistic” facilities at HPC centers, universities, national laboratories, and public clouds, combine to meet these requirements. These resources have characteristics (such as local queuing availability, proximity to data sources and target destinations, network latency and bandwidth capacity, etc.) affecting the overall processing efficiency and throughput. To quantitatively understand and in some instances predict behavior, we have developed a platform to aggregate, index (for user queries), and analyze the more important information streams affecting performance. These data streams come from the ATLAS production system (PanDA), the distributed data management s...

  20. ATLAS FTK a - very complex - custom super computer

    International Nuclear Information System (INIS)

    Kimura, N

    2016-01-01

    In the LHC environment for high interaction pile-up, advanced techniques of analysing the data in real time are required in order to maximize the rate of physics processes of interest with respect to background processes. The Fast TracKer (FTK) is a track finding implementation at the hardware level that is designed to deliver full-scan tracks with p T above 1 GeV to the ATLAS trigger system for events passing the Level-1 accept (at a maximum rate of 100 kHz). In order to achieve this performance, a highly parallel system was designed and currently it is being commissioned within in ATLAS. Starting in 2016 it will provide tracks for the trigger system in a region covering the central part of the ATLAS detector, and will be extended to the full detector coverage. The system relies on matching hits coming from the silicon tracking detectors against one billion patterns stored in custom ASIC chips (Associative memory chip - AM06). In a first stage, coarse resolution hits are matched against the patterns and the accepted hits undergo track fitting implemented in FPGAs. Tracks with p T > 1GeV are delivered to the High Level Trigger within about 100 ps. Resolution of the tracks coming from FTK is close to the offline tracking and it will allow for reliable detection of primary and secondary vertexes at trigger level and improved trigger performance for b-jets and tau leptons. This contribution will give an overview of the FTK system and present the status of commissioning of the system. Additionally, the expected FTK performance will be briefly described. (paper)

  1. Evolution of the ATLAS data and computing model for a Tier2 in the EGI infrastructure

    CERN Document Server

    Fernández Casaní, A; The ATLAS collaboration; González de la Hoz, S; Salt Cairols, J; Fassi, F; Kaci, M; Lamas, A; Oliver, E; Sánchez, J; Sánchez, V

    2012-01-01

    Since the start of the LHC pp collisions in 2010, the ATLAS computing model has moved from a more strict design, where every Tier2 had a liaison and a network dependence from a Tier1, to a more meshed approach where every cloud could be connected. Evolution of ATLAS data models requires changes in ATLAS Tier2s policy for the data replication, dynamic data caching and remote data access. It also requires rethinking the network infrastructure to enable any Tier2 and associated Tier3 to easily connect to any Tier1 or Tier2. Tier2s are becoming more and more important in the ATLAS computing model as it allows more data to be readily accessible for analysis jobs to all users, independently of their geographical location. The Tier2s disk space has been reserved for real, simulated, calibration and alignment, group, and user data. A buffer disk space is needed for input and output data for simulations jobs. Tier2s are going to be used more efficiently. In this way Tier1s and Tier2s are becoming more equivalent for t...

  2. ATLAS Distributed Computing Experience and Performance During the LHC Run-2

    Science.gov (United States)

    Filipčič, A.; ATLAS Collaboration

    2017-10-01

    ATLAS Distributed Computing during LHC Run-1 was challenged by steadily increasing computing, storage and network requirements. In addition, the complexity of processing task workflows and their associated data management requirements led to a new paradigm in the ATLAS computing model for Run-2, accompanied by extensive evolution and redesign of the workflow and data management systems. The new systems were put into production at the end of 2014, and gained robustness and maturity during 2015 data taking. ProdSys2, the new request and task interface; JEDI, the dynamic job execution engine developed as an extension to PanDA; and Rucio, the new data management system, form the core of Run-2 ATLAS distributed computing engine. One of the big changes for Run-2 was the adoption of the Derivation Framework, which moves the chaotic CPU and data intensive part of the user analysis into the centrally organized train production, delivering derived AOD datasets to user groups for final analysis. The effectiveness of the new model was demonstrated through the delivery of analysis datasets to users just one week after data taking, by completing the calibration loop, Tier-0 processing and train production steps promptly. The great flexibility of the new system also makes it possible to execute part of the Tier-0 processing on the grid when Tier-0 resources experience a backlog during high data-taking periods. The introduction of the data lifetime model, where each dataset is assigned a finite lifetime (with extensions possible for frequently accessed data), was made possible by Rucio. Thanks to this the storage crises experienced in Run-1 have not reappeared during Run-2. In addition, the distinction between Tier-1 and Tier-2 disk storage, now largely artificial given the quality of Tier-2 resources and their networking, has been removed through the introduction of dynamic ATLAS clouds that group the storage endpoint nucleus and its close-by execution satellite sites. All stable

  3. Monitoring of computing resource utilization of the ATLAS experiment

    International Nuclear Information System (INIS)

    Rousseau, David; Vukotic, Ilija; Schaffer, RD; Dimitrov, Gancho; Aidel, Osman; Albrand, Solveig

    2012-01-01

    Due to the good performance of the LHC accelerator, the ATLAS experiment has seen higher than anticipated levels for both the event rate and the average number of interactions per bunch crossing. In order to respond to these changing requirements, the current and future usage of CPU, memory and disk resources has to be monitored, understood and acted upon. This requires data collection at a fairly fine level of granularity: the performance of each object written and each algorithm run, as well as a dozen per-job variables, are gathered for the different processing steps of Monte Carlo generation and simulation and the reconstruction of both data and Monte Carlo. We present a system to collect and visualize the data from both the online Tier-0 system and distributed grid production jobs. Around 40 GB of performance data are expected from up to 200k jobs per day, thus making performance optimization of the underlying Oracle database of utmost importance.

  4. ATLAS Distributed Computing experience and performance during the LHC Run-2

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00081160; The ATLAS collaboration

    2016-01-01

    ATLAS Distributed Computing during LHC Run-1 was challenged by steadily increasing computing, storage and network requirements. In addition, the complexity of processing task workflows and their associated data management requirements led to a new paradigm in the ATLAS computing model for Run-2, accompanied by extensive evolution and redesign of the workflow and data management systems. The new systems were put into production at the end of 2014, and gained robustness and maturity during 2015 data taking. ProdSys2, the new request and task interface; JEDI, the dynamic job execution engine developed as an extension to PanDA; and Rucio, the new data management system, form the core of the Run-2 ATLAS distributed computing engine. One of the big changes for Run-2 was the adoption of the Derivation Framework, which moves the chaotic CPU and data intensive part of the user analysis into the centrally organized train production, delivering derived AOD datasets to user groups for final analysis. The effectiveness of...

  5. Design and performance of the virtualization platform for offline computing on the ATLAS TDAQ Farm

    International Nuclear Information System (INIS)

    Ballestrero, S; Lee, C J; Batraneanu, S M; Scannicchio, D A; Brasolin, F; Contescu, C; Girolamo, A Di; Astigarraga, M E Pozo; Twomey, M S; Zaytsev, A

    2014-01-01

    With the LHC collider at CERN currently going through the period of Long Shutdown 1 there is an opportunity to use the computing resources of the experiments' large trigger farms for other data processing activities. In the case of the ATLAS experiment, the TDAQ farm, consisting of more than 1500 compute nodes, is suitable for running Monte Carlo (MC) production jobs that are mostly CPU and not I/O bound. This contribution gives a thorough review of the design and deployment of a virtualized platform running on this computing resource and of its use to run large groups of CernVM based virtual machines operating as a single CERN-P1 WLCG site. This platform has been designed to guarantee the security and the usability of the ATLAS private network, and to minimize interference with TDAQ's usage of the farm. Openstack has been chosen to provide a cloud management layer. The experience gained in the last 3.5 months shows that the use of the TDAQ farm for the MC simulation contributes to the ATLAS data processing at the level of a large Tier-1 WLCG site, despite the opportunistic nature of the underlying computing resources being used.

  6. Design and performance of the virtualization platform for offline computing on the ATLAS TDAQ Farm

    Science.gov (United States)

    Ballestrero, S.; Batraneanu, S. M.; Brasolin, F.; Contescu, C.; Di Girolamo, A.; Lee, C. J.; Pozo Astigarraga, M. E.; Scannicchio, D. A.; Twomey, M. S.; Zaytsev, A.

    2014-06-01

    With the LHC collider at CERN currently going through the period of Long Shutdown 1 there is an opportunity to use the computing resources of the experiments' large trigger farms for other data processing activities. In the case of the ATLAS experiment, the TDAQ farm, consisting of more than 1500 compute nodes, is suitable for running Monte Carlo (MC) production jobs that are mostly CPU and not I/O bound. This contribution gives a thorough review of the design and deployment of a virtualized platform running on this computing resource and of its use to run large groups of CernVM based virtual machines operating as a single CERN-P1 WLCG site. This platform has been designed to guarantee the security and the usability of the ATLAS private network, and to minimize interference with TDAQ's usage of the farm. Openstack has been chosen to provide a cloud management layer. The experience gained in the last 3.5 months shows that the use of the TDAQ farm for the MC simulation contributes to the ATLAS data processing at the level of a large Tier-1 WLCG site, despite the opportunistic nature of the underlying computing resources being used.

  7. ATLAS Distributed Computing experience and performance during the LHC Run-2

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00081160; The ATLAS collaboration

    2017-01-01

    ATLAS Distributed Computing during LHC Run-1 was challenged by steadily increasing computing, storage and network requirements. In addition, the complexity of processing task workflows and their associated data management requirements led to a new paradigm in the ATLAS computing model for Run-2, accompanied by extensive evolution and redesign of the workflow and data management systems. The new systems were put into production at the end of 2014, and gained robustness and maturity during 2015 data taking. ProdSys2, the new request and task interface; JEDI, the dynamic job execution engine developed as an extension to PanDA; and Rucio, the new data management system, form the core of Run-2 ATLAS distributed computing engine. One of the big changes for Run-2 was the adoption of the Derivation Framework, which moves the chaotic CPU and data intensive part of the user analysis into the centrally organized train production, delivering derived AOD datasets to user groups for final analysis. The effectiveness of the...

  8. PanDA for ATLAS Distributed Computing in the Next Decade

    CERN Document Server

    Barreiro Megino, Fernando Harald; The ATLAS collaboration

    2016-01-01

    The Production and Distributed Analysis (PanDA) system has been developed to meet ATLAS production and analysis requirements for a data-driven workload management system capable of operating at the Large Hadron Collider (LHC) data processing scale. Heterogeneous resources used by the ATLAS experiment are distributed worldwide at hundreds of sites, thousands of physicists analyse the data remotely, the volume of processed data is beyond the exabyte scale, dozens of scientific applications are supported, while data processing requires more than a few billion hours of computing usage per year. PanDA performed very well over the last decade including the LHC Run 1 data taking period. However, it was decided to upgrade the whole system concurrently with the LHC’s first long shutdown in order to cope with rapidly changing computing infrastructure. After two years of reengineering efforts, PanDA has embedded capabilities for fully dynamic and flexible workload management. The static batch job paradigm was discarde...

  9. PanDA for ATLAS distributed computing in the next decade

    CERN Document Server

    AUTHOR|(SzGeCERN)643806; The ATLAS collaboration; De, Kaushik; Klimentov, Alexei; Maeno, Tadashi; Nilsson, Paul; Oleynik, Danila; Padolski, Siarhei; Panitkin, Sergey; Wenaus, Torre

    2017-01-01

    The Production and Distributed Analysis (PanDA) system has been developed to meet ATLAS production and analysis requirements for a data-driven workload management system capable of operating at the Large Hadron Collider (LHC) data processing scale. Heterogeneous resources used by the ATLAS experiment are distributed worldwide at hundreds of sites, thousands of physicists analyse the data remotely, the volume of processed data is beyond the exabyte scale, dozens of scientific applications are supported, while data processing requires more than a few billion hours of computing usage per year. PanDA performed very well over the last decade including the LHC Run 1 data taking period. However, it was decided to upgrade the whole system concurrently with the LHC’s first long shutdown in order to cope with rapidly changing computing infrastructure. After two years of reengineering efforts, PanDA has embedded capabilities for fully dynamic and flexible workload management. The static batch job paradigm was discarde...

  10. Design and Performance of the Virtualization Platform for Offline computing on the ATLAS TDAQ Farm

    CERN Document Server

    Ballestrero, S; The ATLAS collaboration; Brasolin, F; Contescu, C; Di Girolamo, A; Lee, C J; Pozo Astigarraga, M E; Scannicchio, D A; Twomey, M S; Zaytsev, A

    2013-01-01

    With the LHC collider at CERN currently going through the period of Long Shutdown 1 (LS1) there is a remarkable opportunity to use the computing resources of the large trigger farms of the experiments for other data processing activities. In the case of ATLAS experiment the TDAQ farm, consisting of more than 1500 compute nodes, is particularly suitable for running Monte Carlo production jobs that are mostly CPU and not I/O bound. This contribution gives a thorough review of all the stages of Sim@P1 project dedicated to the design and deployment of a virtualized platform running on the ATLAS TDAQ computing resources and using it to run the large groups of CernVM based virtual machines operating as a single CERN-P1 WLCG site. This platform has been designed to avoid interference with TDAQ usage of the farm and to guarantee the security and the usability of the ATLAS private network; Openstack has been chosen to provide a cloud management layer. The approaches to organizing support for the sustained operation of...

  11. Design and Performance of the Virtualization Platform for Offline computing on the ATLAS TDAQ Farm

    CERN Document Server

    Ballestrero, S; The ATLAS collaboration; Brasolin, F; Contescu, C; Di Girolamo, A; Lee, C J; Pozo Astigarraga, M E; Scannicchio, D A; Twomey, M S; Zaytsev, A

    2014-01-01

    With the LHC collider at CERN currently going through the period of Long Shutdown 1 (LS1) there is a remarkable opportunity to use the computing resources of the large trigger farms of the experiments for other data processing activities. In the case of ATLAS experiment the TDAQ farm, consisting of more than 1500 compute nodes, is particularly suitable for running Monte Carlo production jobs that are mostly CPU and not I/O bound. This contribution gives a thorough review of all the stages of Sim@P1 project dedicated to the design and deployment of a virtualized platform running on the ATLAS TDAQ computing resources and using it to run the large groups of CernVM based virtual machines operating as a single CERN-P1 WLCG site. This platform has been designed to avoid interference with TDAQ usage of the farm and to guarantee the security and the usability of the ATLAS private network; Openstack has been chosen to provide a cloud management layer. The approaches to organizing support for the sustained operation of...

  12. Evolution of the ATLAS PanDA workload management system for exascale computational science

    International Nuclear Information System (INIS)

    Maeno, T; Klimentov, A; Panitkin, S; Schovancova, J; Wenaus, T; Yu, D; De, K; Nilsson, P; Oleynik, D; Petrosyan, A; Vaniachine, A

    2014-01-01

    An important foundation underlying the impressive success of data processing and analysis in the ATLAS experiment [1] at the LHC [2] is the Production and Distributed Analysis (PanDA) workload management system [3]. PanDA was designed specifically for ATLAS and proved to be highly successful in meeting all the distributed computing needs of the experiment. However, the core design of PanDA is not experiment specific. The PanDA workload management system is capable of meeting the needs of other data intensive scientific applications. Alpha-Magnetic Spectrometer [4], an astro-particle experiment on the International Space Station, and the Compact Muon Solenoid [5], an LHC experiment, have successfully evaluated PanDA and are pursuing its adoption. In this paper, a description of the new program of work to develop a generic version of PanDA will be given, as well as the progress in extending PanDA's capabilities to support supercomputers and clouds and to leverage intelligent networking. PanDA has demonstrated at a very large scale the value of automated dynamic brokering of diverse workloads across distributed computing resources. The next generation of PanDA will allow other data-intensive sciences and a wider exascale community employing a variety of computing platforms to benefit from ATLAS' experience and proven tools.

  13. Integrated monitoring of the ATLAS online computing farm

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00389536; The ATLAS collaboration; Brasolin, Franco; Fazio, Daniel; Gament, Costin-Eugen; Lee, Christopher; Scannicchio, Diana; Twomey, Matthew Shaun

    2017-01-01

    The online farm of the ATLAS experiment at the LHC, consisting of nearly 4100 PCs with various characteristics, provides configuration and control of the detector and performs the collection, processing, selection and conveyance of event data from the front-end electronics to mass storage. The status and health of every host must be constantly monitored to ensure the correct and reliable operation of the whole online system. This is the first line of defense, which should not only promptly provide alerts in case of failure but, whenever possible, warn of impending issues. The monitoring system should be able to check up to 100000 health parameters and provide alerts on a selected subset. In this paper we present the implementation and validation of our new monitoring and alerting system based on Icinga 2 and Ganglia. We describe how the load distribution and high availability features of Icinga 2 allowed us to have a centralised but scalable system, with a configuration model that allows full flexibility whil...

  14. Integrated monitoring of the ATLAS online computing farm

    CERN Document Server

    Ballestrero, Sergio; The ATLAS collaboration; Fazio, Daniel; Gament, Costin-Eugen; Lee, Christopher; Scannicchio, Diana; Twomey, Matthew Shaun

    2016-01-01

    The online farm of the ATLAS experiment at the LHC, consisting of nearly 4000 PCs with various characteristics, provides configuration and control of the detector and performs the collection, processing, selection and conveyance of event data from the front-end electronics to mass storage. The status and health of every host must be constantly monitored to ensure the correct and reliable operation of the whole online system. This is the first line of defense, which should not only promptly provide alerts in case of failure but, whenever possible, warn of impending issues. The monitoring system should be able to check up to 100000 health parameters and provide alerts on a selected subset. In this paper we present the implementation and validation of our new monitoring and alerting system based on Icinga 2 and Ganglia. We describe how the load distribution and high availability features of Icinga 2 allowed us to have a centralised but scalable system, with a configuration model that allows full flexibility whil...

  15. Monitoring of computing resource use of active software releases at ATLAS

    Science.gov (United States)

    Limosani, Antonio; ATLAS Collaboration

    2017-10-01

    The LHC is the world’s most powerful particle accelerator, colliding protons at centre of mass energy of 13 TeV. As the energy and frequency of collisions has grown in the search for new physics, so too has demand for computing resources needed for event reconstruction. We will report on the evolution of resource usage in terms of CPU and RAM in key ATLAS offline reconstruction workflows at the TierO at CERN and on the WLCG. Monitoring of workflows is achieved using the ATLAS PerfMon package, which is the standard ATLAS performance monitoring system running inside Athena jobs. Systematic daily monitoring has recently been expanded to include all workflows beginning at Monte Carlo generation through to end-user physics analysis, beyond that of event reconstruction. Moreover, the move to a multiprocessor mode in production jobs has facilitated the use of tools, such as “MemoryMonitor”, to measure the memory shared across processors in jobs. Resource consumption is broken down into software domains and displayed in plots generated using Python visualization libraries and collected into pre-formatted auto-generated Web pages, which allow the ATLAS developer community to track the performance of their algorithms. This information is however preferentially filtered to domain leaders and developers through the use of JIRA and via reports given at ATLAS software meetings. Finally, we take a glimpse of the future by reporting on the expected CPU and RAM usage in benchmark workflows associated with the High Luminosity LHC and anticipate the ways performance monitoring will evolve to understand and benchmark future workflows.

  16. Computation of a high-resolution MRI 3D stereotaxic atlas of the sheep brain.

    Science.gov (United States)

    Ella, Arsène; Delgadillo, José A; Chemineau, Philippe; Keller, Matthieu

    2017-02-15

    The sheep model was first used in the fields of animal reproduction and veterinary sciences and then was utilized in fundamental and preclinical studies. For more than a decade, magnetic resonance (MR) studies performed on this model have been increasingly reported, especially in the field of neuroscience. To contribute to MR translational neuroscience research, a brain template and an atlas are necessary. We have recently generated the first complete T1-weighted (T1W) and T2W MR population average images (or templates) of in vivo sheep brains. In this study, we 1) defined a 3D stereotaxic coordinate system for previously established in vivo population average templates; 2) used deformation fields obtained during optimized nonlinear registrations to compute nonlinear tissues or prior probability maps (nlTPMs) of cerebrospinal fluid (CSF), gray matter (GM), and white matter (WM) tissues; 3) delineated 25 external and 28 internal sheep brain structures by segmenting both templates and nlTPMs; and 4) annotated and labeled these structures using an existing histological atlas. We built a quality high-resolution 3D atlas of average in vivo sheep brains linked to a reference stereotaxic space. The atlas and nlTPMs, associated with previously computed T1W and T2W in vivo sheep brain templates and nlTPMs, provide a complete set of imaging space that are able to be imported into other imaging software programs and could be used as standardized tools for neuroimaging studies or other neuroscience methods, such as image registration, image segmentation, identification of brain structures, implementation of recording devices, or neuronavigation. J. Comp. Neurol. 525:676-692, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  17. Monitoring of Computing Resource Use of Active Software Releases in ATLAS

    CERN Document Server

    Limosani, Antonio; The ATLAS collaboration

    2016-01-01

    The LHC is the world's most powerful particle accelerator, colliding protons at centre of mass energy of 13 TeV. As the energy and frequency of collisions has grown in the search for new physics, so too has demand for computing resources needed for event reconstruction. We will report on the evolution of resource usage in terms of CPU and RAM in key ATLAS offline reconstruction workflows at the Tier0 at CERN and on the WLCG. Monitoring of workflows is achieved using the ATLAS PerfMon package, which is the standard ATLAS performance monitoring system running inside Athena jobs. Systematic daily monitoring has recently been expanded to include all workflows beginning at Monte Carlo generation through to end user physics analysis, beyond that of event reconstruction. Moreover, the move to a multiprocessor mode in production jobs has facilitated the use of tools, such as "MemoryMonitor", to measure the memory shared across processors in jobs. Resource consumption is broken down into software domains and displayed...

  18. Monitoring of computing resource use of active software releases at ATLAS

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00219183; The ATLAS collaboration

    2017-01-01

    The LHC is the world’s most powerful particle accelerator, colliding protons at centre of mass energy of 13 TeV. As the energy and frequency of collisions has grown in the search for new physics, so too has demand for computing resources needed for event reconstruction. We will report on the evolution of resource usage in terms of CPU and RAM in key ATLAS offline reconstruction workflows at the TierO at CERN and on the WLCG. Monitoring of workflows is achieved using the ATLAS PerfMon package, which is the standard ATLAS performance monitoring system running inside Athena jobs. Systematic daily monitoring has recently been expanded to include all workflows beginning at Monte Carlo generation through to end-user physics analysis, beyond that of event reconstruction. Moreover, the move to a multiprocessor mode in production jobs has facilitated the use of tools, such as “MemoryMonitor”, to measure the memory shared across processors in jobs. Resource consumption is broken down into software domains and dis...

  19. The evolving role of Tier2s in ATLAS with the new Computing and Data Distribution model

    International Nuclear Information System (INIS)

    González de la Hoz, S

    2012-01-01

    Originally the ATLAS Computing and Data Distribution model assumed that the Tier-2s should keep on disk collectively at least one copy of all “active” AOD and DPD datasets. Evolution of ATLAS Computing and Data model requires changes in ATLAS Tier-2s policy for the data replication, dynamic data caching and remote data access. Tier-2 operations take place completely asynchronously with respect to data taking. Tier-2s do simulation and user analysis. Large-scale reprocessing jobs on real data are at first taking place mostly at Tier-1s but will progressively be shared with Tier-2s as well. The availability of disk space at Tier-2s is extremely important in the ATLAS Computing model as it allows more data to be readily accessible for analysis jobs to all users, independently of their geographical location. The Tier-2s disk space has been reserved for real, simulated, calibration and alignment, group, and user data. A buffer disk space is needed for input and output data for simulations jobs. Tier-2s are going to be used more efficiently. In this way Tier-1s and Tier-2s are becoming more equivalent for the network and the hierarchy of Tier-1, 2 is less strict. This paper presents the usage of Tier-2s resources in different Grid activities, caching of data at Tier-2s, and their role in the analysis in the new ATLAS Computing and Data model.

  20. ATLAS Tier-2 at the Compute Resource Center GoeGrid in Göttingen

    Science.gov (United States)

    Meyer, Jörg; Quadt, Arnulf; Weber, Pavel; ATLAS Collaboration

    2011-12-01

    GoeGrid is a grid resource center located in Göttingen, Germany. The resources are commonly used, funded, and maintained by communities doing research in the fields of grid development, computer science, biomedicine, high energy physics, theoretical physics, astrophysics, and the humanities. For the high energy physics community, GoeGrid serves as a Tier-2 center for the ATLAS experiment as part of the world-wide LHC computing grid (WLCG). The status and performance of the Tier-2 center is presented with a focus on the interdisciplinary setup and administration of the cluster. Given the various requirements of the different communities on the hardware and software setup the challenge of the common operation of the cluster is detailed. The benefits are an efficient use of computer and personpower resources.

  1. ATLAS distributed computing operation shift teams experience during the discovery year and beginning of the long shutdown 1

    International Nuclear Information System (INIS)

    Sedov, Alexey; Girolamo, Alessandro Di; Negri, Guidone; Sakamoto, Hiroshi; Schovancová, Jaroslava; Smirnov, Iouri; Vartapetian, Armen; Yu, Jaehoon

    2014-01-01

    ATLAS Distributed Computing Operation Shifts evolve to meet new requirements. New monitoring tools as well as operational changes lead to modifications in organization of shifts. In this paper we describe the structure of shifts, the roles of different shifts in ATLAS computing grid operation, the influence of a Higgs-like particle discovery on shift operation, the achievements in monitoring and automation that allowed extra focus on the experiment priority tasks, and the influence of the Long Shutdown 1 and operational changes related to the no beam period.

  2. ATLAS off-Grid sites (Tier 3) monitoring. From local fabric monitoring to global overview of the VO computing activities

    CERN Document Server

    PETROSYAN, A; The ATLAS collaboration; BELOV, S; ANDREEVA, J; KADOCHNIKOV, I

    2012-01-01

    The ATLAS Distributed Computing activities have so far concentrated in the "central" part of the experiment computing system, namely the first 3 tiers (the CERN Tier0, 10 Tier1 centers and over 60 Tier2 sites). Many ATLAS Institutes and National Communities have deployed (or intend to) deploy Tier-3 facilities. Tier-3 centers consist of non-pledged resources, which are usually dedicated to data analysis tasks by the geographically close or local scientific groups, and which usually comprise a range of architectures without Grid middleware. Therefore a substantial part of the ATLAS monitoring tools which make use of Grid middleware, cannot be used for a large fraction of Tier3 sites. The presentation will describe the T3mon project, which aims to develop a software suite for monitoring the Tier3 sites, both from the perspective of the local site administrator and that of the ATLAS VO, thereby enabling the global view of the contribution from Tier3 sites to the ATLAS computing activities. Special attention in p...

  3. Reconstruction and identification of electrons in the Atlas experiment. Setup of a Tier 2 of the computing grid

    International Nuclear Information System (INIS)

    Derue, F.

    2008-03-01

    The origin of the mass of elementary particles is linked to the electroweak symmetry breaking mechanism. Its study will be one of the main efforts of the Atlas experiment at the Large Hadron Collider of CERN, starting in 2008. In most cases, studies will be limited by our knowledge of the detector performances, as the precision of the energy reconstruction or the efficiency to identify particles. This manuscript presents a work dedicated to the reconstruction of electrons in the Atlas experiment with simulated data and data taken during the combined test beam of 2004. The analysis of the Atlas data implies the use of a huge amount of computing and storage resources which brought to the development of a world computing grid. (author)

  4. ATLAS OpenData and OpenKey: using low tech computational tools for students training in High Energy Physics

    CERN Document Server

    Sanchez Pineda, Arturos; The ATLAS collaboration

    2018-01-01

    One of the big challenges in High Energy Physics development is the fact that many potential -and very valuable- students and young researchers live in countries where internet access and computational infrastructure are poor compared to institutions already participating. In order to accelerate the process, the ATLAS Open Data project releases useful and meaningful data and tools using standard and easy-to-deploy computational means, such as custom and light Linux Virtual Machines, open source technologies, web and desktop applications. The ATLAS Open Key, a simple USB pen, allows transporting all those resources around the globe. As simple as it sounds, this approach is helping to train students that are now PhD candidates and to integrate HEP educational programs at Master level in universities where did not exist before. The software tools and resources used will be presented, as well as results and stories, ideas and next steps of the ATLAS Open Data project.

  5. Integrating Network Awareness in ATLAS Distributed Computing Using the ANSE Project

    CERN Document Server

    Klimentov, Alexei; The ATLAS collaboration; Petrosyan, Artem; Batista, Jorge Horacio; Mc Kee, Shawn Patrick

    2015-01-01

    A crucial contributor to the success of the massively scaled global computing system that delivers the analysis needs of the LHC experiments is the networking infrastructure upon which the system is built. The experiments have been able to exploit excellent high-bandwidth networking in adapting their computing models for the most efficient utilization of resources. New advanced networking technologies now becoming available such as software defined networking hold the potential of further leveraging the network to optimize workflows and dataflows, through proactive control of the network fabric on the part of high level applications such as experiment workload management and data management systems. End to end monitoring of networks using perfSONAR combined with data flow performance metrics further allows applications to adapt based on real time conditions. We will describe efforts underway in ATLAS on integrating network awareness at the application level, particularly in workload management, building upon ...

  6. Remote data access in computational jobs on the ATLAS data grid

    CERN Document Server

    Begy, Volodimir; The ATLAS collaboration; Lassnig, Mario

    2018-01-01

    This work describes the technique of remote data access from computational jobs on the ATLAS data grid. In comparison to traditional data movement and stage-in approaches it is well suited for data transfers which are asynchronous with respect to the job execution. Hence, it can be used for optimization of data access patterns based on various policies. In this study, remote data access is realized with the HTTP and WebDAV protocols, and is investigated in the context of intra- and inter-computing site data transfers. In both cases, the typical scenarios for application of remote data access are identified. The paper also presents an analysis of parameters influencing the data goodput between heterogeneous storage element - worker node pairs on the grid.

  7. AGIS: The ATLAS Grid Information System

    CERN Document Server

    Anisenkov, A; The ATLAS collaboration; Klimentov, A; Senchenko, A

    2012-01-01

    The ATLAS Computing model embraces the Grid paradigm and a high degree of decentralization and computing resources able to meet ATLAS requirements of petabytes scale data operations. In this paper we present ATLAS Grid Information System (AGIS) designed to integrate configuration and status information about resources, services and topology of whole ATLAS Grid needed by ATLAS Distributed Computing applications and services.

  8. Evolution of the ATLAS PanDA Workload Management System for Exascale Computational Science

    CERN Document Server

    Maeno, T; The ATLAS collaboration; Klimentov, A; Nilsson, P; Oleynik, D; Panitkin, S; Petrosyan, A; Schovancova, J; Vaniachine, A; Wenaus, T; Yu, D

    2013-01-01

    An important foundation underlying the impressive success of data processing and analysis in the ATLAS experiment [1] at the LHC [2] is the Production and Distributed Analysis (PanDA) workload management system [3]. PanDA was designed specifically for ATLAS and proved to be highly successful in meeting all the distributed computing needs of the experiment. However, the core design of PanDA is not experiment specific. The PanDA workload management system is capable of meeting the needs of other data intensive scientific applications. Alpha-Magnetic Spectrometer [4], an astro-particle experiment on the International Space Station, and the Compact Muon Solenoid [5], an LHC experiment, have successfully evaluated PanDA and are pursuing its adoption. In this paper, a description of the new program of work to develop a generic version of PanDA will be given, as well as the progress in extending PanDA's capabilities to support supercomputers and clouds and to leverage intelligent networking. PanDA has demonstrated a...

  9. Evolution of the ATLAS PanDA Workload Management System for Exascale Computational Science

    CERN Document Server

    Maeno, T; The ATLAS collaboration; Klimentov, A; Nilsson, P; Oleynik, D; Panitkin, S; Petrosyan, A; Schovancova, J; Vaniachine, A; Wenaus, T; Yu, D

    2014-01-01

    An important foundation underlying the impressive success of data processing and analysis in the ATLAS experiment [1] at the LHC [2] is the Production and Distributed Analysis (PanDA) workload management system [3]. PanDA was designed specifically for ATLAS and proved to be highly successful in meeting all the distributed computing needs of the experiment. However, the core design of PanDA is not experiment specific. The PanDA workload management system is capable of meeting the needs of other data intensive scientific applications. Alpha-Magnetic Spectrometer [4], an astro-particle experiment on the International Space Station, and the Compact Muon Solenoid [5], an LHC experiment, have successfully evaluated PanDA and are pursuing its adoption. In this paper, a description of the new program of work to develop a generic version of PanDA will be given, as well as the progress in extending PanDA's capabilities to support supercomputers and clouds and to leverage intelligent networking. PanDA has demonstrated a...

  10. The Evolving role of Tier2s in ATLAS with the new Computing and Data Distribution Model

    CERN Document Server

    Gonzalez de la Hoz, S; The ATLAS collaboration

    2012-01-01

    Originally the ATLAS computing model assumed that the Tier2s of each of the 10 clouds should keep on disk collectively at least one copy of all "active" AOD and DPD datasets. Evolution of ATLAS computing and data models requires changes in ATLAS Tier2s policy for the data replication, dynamic data caching and remote data access. Tier2 operations take place completely asynchronously with respect to data taking. Tier2s do simulation and user analysis. Large-scale reprocessing jobs on real data are at first taking place mostly at Tier1s but will progressively move to Tier2s as well. The availability of disk space at Tier2s is extremely important in the ATLAS computing model as it allows more data to be readily accessible for analysis jobs to all users, independently of their geographical location. The Tier2s disk space has been reserved for real, simulated, calibration and alignment, group, and user data. A buffer disk space is needed for input and output data for simulations jobs. Tier2s are going to be used mo...

  11. The evolving role of Tier2s in ATLAS with the new Computing and Data Distribution model

    CERN Document Server

    Gonzalez de la Hoz, S

    2012-01-01

    Originally the ATLAS computing model assumed that the Tier2s of each of the 10 clouds should keep on disk collectively at least one copy of all "active" AOD and DPD datasets. Evolution of ATLAS computing and data models requires changes in ATLAS Tier2s policy for the data replication, dynamic data caching and remote data access. Tier2 operations take place completely asynchronously with respect to data taking. Tier2s do simulation and user analysis. Large-scale reprocessing jobs on real data are at first taking place mostly at Tier1s but will progressively move to Tier2s as well. The availability of disk space at Tier2s is extremely important in the ATLAS computing model as it allows more data to be readily accessible for analysis jobs to all users, independently of their geographical location. The Tier2s disk space has been reserved for real, simulated, calibration and alignment, group, and user data. A buffer disk space is needed for input and output data for simulations jobs. Tier2s are going to be used mo...

  12. PanDA for ATLAS distributed computing in the next decade

    Science.gov (United States)

    Barreiro Megino, F. H.; De, K.; Klimentov, A.; Maeno, T.; Nilsson, P.; Oleynik, D.; Padolski, S.; Panitkin, S.; Wenaus, T.; ATLAS Collaboration

    2017-10-01

    The Production and Distributed Analysis (PanDA) system has been developed to meet ATLAS production and analysis requirements for a data-driven workload management system capable of operating at the Large Hadron Collider (LHC) data processing scale. Heterogeneous resources used by the ATLAS experiment are distributed worldwide at hundreds of sites, thousands of physicists analyse the data remotely, the volume of processed data is beyond the exabyte scale, dozens of scientific applications are supported, while data processing requires more than a few billion hours of computing usage per year. PanDA performed very well over the last decade including the LHC Run 1 data taking period. However, it was decided to upgrade the whole system concurrently with the LHC’s first long shutdown in order to cope with rapidly changing computing infrastructure. After two years of reengineering efforts, PanDA has embedded capabilities for fully dynamic and flexible workload management. The static batch job paradigm was discarded in favor of a more automated and scalable model. Workloads are dynamically tailored for optimal usage of resources, with the brokerage taking network traffic and forecasts into account. Computing resources are partitioned based on dynamic knowledge of their status and characteristics. The pilot has been re-factored around a plugin structure for easier development and deployment. Bookkeeping is handled with both coarse and fine granularities for efficient utilization of pledged or opportunistic resources. An in-house security mechanism authenticates the pilot and data management services in off-grid environments such as volunteer computing and private local clusters. The PanDA monitor has been extensively optimized for performance and extended with analytics to provide aggregated summaries of the system as well as drill-down to operational details. There are as well many other challenges planned or recently implemented, and adoption by non-LHC experiments such

  13. Using Puppet to contextualize computing resources for ATLAS analysis on Google Compute Engine

    International Nuclear Information System (INIS)

    Öhman, Henrik; Panitkin, Sergey; Hendrix, Valerie

    2014-01-01

    With the advent of commercial as well as institutional and national clouds, new opportunities for on-demand computing resources for the HEP community become available. The new cloud technologies also come with new challenges, and one such is the contextualization of computing resources with regard to requirements of the user and his experiment. In particular on Google's new cloud platform Google Compute Engine (GCE) upload of user's virtual machine images is not possible. This precludes application of ready to use technologies like CernVM and forces users to build and contextualize their own VM images from scratch. We investigate the use of Puppet to facilitate contextualization of cloud resources on GCE, with particular regard to ease of configuration and dynamic resource scaling.

  14. A Step Towards A Computing Grid For The LHC Experiments ATLAS Data Challenge 1

    CERN Document Server

    Sturrock, R; Epp, B; Ghete, V M; Kuhn, D; Mello, A G; Caron, B; Vetterli, M C; Karapetian, G V; Martens, K; Agarwal, A; Poffenberger, P R; McPherson, R A; Sobie, R J; Amstrong, S; Benekos, N C; Boisvert, V; Boonekamp, M; Brandt, S; Casado, M P; Elsing, M; Gianotti, F; Goossens, L; Grote, M; Hansen, J B; Mair, K; Nairz, A; Padilla, C; Poppleton, A; Poulard, G; Richter-Was, Elzbieta; Rosati, S; Schörner-Sadenius, T; Wengler, T; Xu, G F; Ping, J L; Chudoba, J; Kosina, J; Lokajícek, M; Svec, J; Tas, P; Hansen, J R; Lytken, E; Nielsen, J L; Wäänänen, A; Tapprogge, Stefan; Calvet, D; Albrand, S; Collot, J; Fulachier, J; Ledroit-Guillon, F; Ohlsson-Malek, F; Viret, S; Wielers, M; Bernardet, K; Corréard, S; Rozanov, A; De Vivie de Régie, J B; Arnault, C; Bourdarios, C; Hrivnác, J; Lechowski, M; Parrour, G; Perus, A; Rousseau, D; Schaffer, A; Unal, G; Derue, F; Chevalier, L; Hassani, S; Laporte, J F; Nicolaidou, R; Pomarède, D; Virchaux, M; Nesvadba, N; Baranov, S; Putzer, A; Khonich, A; Duckeck, G; Schieferdecker, P; Kiryunin, A E; Schieck, J; Lagouri, T; Duchovni, E; Levinson, L; Schrager, D; Negri, G; Bilokon, H; Spogli, L; Barberis, D; Parodi, F; Cataldi, G; Gorini, E; Primavera, M; Spagnolo, S; Cavalli, D; Heldmann, M; Lari, T; Perini, L; Rebatto, D; Resconi, S; Tatarelli, F; Vaccarossa, L; Biglietti, M; Carlino, G; Conventi, F; Doria, A; Merola, L; Polesello, G; Vercesi, V; De Salvo, A; Di Mattia, A; Luminari, L; Nisati, A; Reale, M; Testa, M; Farilla, A; Verducci, M; Cobal, M; Santi, L; Hasegawa, Y; Ishino, M; Mashimo, T; Matsumoto, H; Sakamoto, H; Tanaka, J; Ueda, I; Bentvelsen, Stanislaus Cornelius Maria; Fornaini, A; Gorfine, G; Groep, D; Templon, J; Köster, L J; Konstantinov, A; Myklebust, T; Ould-Saada, F; Bold, T; Kaczmarska, A; Malecki, P; Szymocha, T; Turala, M; Kulchitskii, Yu A; Khoreauli, G; Gromova, N; Tsulaia, V; Minaenko, A A; Rudenko, R; Slabospitskaya, E; Solodkov, A; Gavrilenko, I; Nikitine, N; Sivoklokov, S Yu; Toms, K; Zalite, A; Zalite, Yu; Kervesan, B; Bosman, M; González, S; Sánchez, J; Salt, J; Andersson, N; Nixon, L; Eerola, Paule Anna Mari; Kónya, B; Smirnova, O G; Sandgren, A; Ekelöf, T J C; Ellert, M; Gollub, N; Hellman, S; Lipniacka, A; Corso-Radu, A; Pérez-Réale, V; Lee, S C; CLin, S C; Ren, Z L; Teng, P K; Faulkner, P J W; O'Neale, S W; Watson, A; Brochu, F; Lester, C; Thompson, S; Kennedy, J; Bouhova-Thacker, E; Henderson, R; Jones, R; Kartvelishvili, V G; Smizanska, M; Washbrook, A J; Drohan, J; Konstantinidis, N P; Moyse, E; Salih, S; Loken, J; Baines, J T M; Candlin, D; Candlin, R; Clifft, R; Li, W; McCubbin, N A; George, S; Lowe, A; Buttar, C; Dawson, I; Moraes, A; Tovey, Daniel R; Gieraltowski, J; Malon, D; May, E; LeCompte, T J; Vaniachine, A; Adams, D L; Assamagan, Ketevi A; Baker, R; Deng, W; Fine, V; Fisyak, Yu; Gibbard, B; Ma, H; Nevski, P; Paige, F; Rajagopalan, S; Smith, J; Undrus, A; Wenaus, T; Yu, D; Calafiura, P; Canon, S; Costanzo, D; Hinchliffe, Ian; Lavrijsen, W; Leggett, C; Marino, M; Quarrie, D R; Sakrejda, I; Stravopoulos, G; Tull, C; Loch, P; Youssef, S; Shank, J T; Engh, D; Frank, E; Sen-Gupta, A; Gardner, R; Meritt, F; Smirnov, Y; Huth, J; Grundhoefer, L; Luehring, F C; Goldfarb, S; Severini, H; Skubic, P L; Gao, Y; Ryan, T; De, K; Sosebee, M; McGuigan, P; Ozturk, N

    2004-01-01

    The ATLAS Collaboration at CERN is preparing for the data taking and analysis at the LHC that will start in 2007. Therefore, a series of Data Challenges was started in 2002 whose goals are the validation of the Computing Model, of the complete software suite, of the data model, and to ensure the correctness of the technical choices to be made for the final offline computing environment. A major feature of the first Data Challenge (DC1) was the preparation and the deployment of the software required for the production of large event samples as a worldwide distributed activity. It should be noted that it was not an option to "run the complete production at CERN" even if we had wanted to; the resources were not available at CERN to carry out the production on a reasonable time-scale. The great challenge of organising and carrying out this large-scale production at a significant number of sites around the world had therefore to be faced. However, the benefits of this are manifold: apart from realising the require...

  15. CASTp 3.0: computed atlas of surface topography of proteins.

    Science.gov (United States)

    Tian, Wei; Chen, Chang; Lei, Xue; Zhao, Jieling; Liang, Jie

    2018-06-01

    Geometric and topological properties of protein structures, including surface pockets, interior cavities and cross channels, are of fundamental importance for proteins to carry out their functions. Computed Atlas of Surface Topography of proteins (CASTp) is a web server that provides online services for locating, delineating and measuring these geometric and topological properties of protein structures. It has been widely used since its inception in 2003. In this article, we present the latest version of the web server, CASTp 3.0. CASTp 3.0 continues to provide reliable and comprehensive identifications and quantifications of protein topography. In addition, it now provides: (i) imprints of the negative volumes of pockets, cavities and channels, (ii) topographic features of biological assemblies in the Protein Data Bank, (iii) improved visualization of protein structures and pockets, and (iv) more intuitive structural and annotated information, including information of secondary structure, functional sites, variant sites and other annotations of protein residues. The CASTp 3.0 web server is freely accessible at http://sts.bioe.uic.edu/castp/.

  16. PanDA: A New Paradigm for Distributed Computing in HEP Through the Lens of ATLAS and other Experiments

    CERN Document Server

    De, K; The ATLAS collaboration; Maeno, T; Nilsson, P; Wenaus, T

    2014-01-01

    Experiments at the Large Hadron Collider (LHC) face unprecedented computing challenges. Heterogeneous resources are distributed worldwide, thousands of physicists analyzing the data need remote access to hundreds of computing sites, the volume of processed data is beyond the exabyte scale, and data processing requires more than a billion hours of computing usage per year. The PanDA (Production and Distributed Analysis) system was developed to meet the scale and complexity of LHC distributed computing for the ATLAS experiment. In the process, the old batch job paradigm of computing in HEP was discarded in favor of a far more flexible and scalable model. The success of PanDA in ATLAS is leading to widespread adoption and testing by other experiments. PanDA is the first exascale workload management system in HEP, already operating at a million computing jobs per day, and processing over an exabyte of data in 2013. We will describe the design and implementation of PanDA, present data on the performance of PanDA a...

  17. Scaling up ATLAS Event Service to production levels on opportunistic computing platforms

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00066086; The ATLAS collaboration; Caballero, Jose; Ernst, Michael; Guan, Wen; Hover, John; Lesny, David; Maeno, Tadashi; Nilsson, Paul; Tsulaia, Vakhtang; van Gemmeren, Peter; Vaniachine, Alexandre; Wang, Fuquan; Wenaus, Torre

    2016-01-01

    Continued growth in public cloud and HPC resources is on track to exceed the dedicated resources available for ATLAS on the WLCG. Examples of such platforms are Amazon AWS EC2 Spot Instances, Edison Cray XC30 supercomputer, backfill at Tier 2 and Tier 3 sites, opportunistic resources at the Open Science Grid (OSG), and ATLAS High Level Trigger farm between the data taking periods. Because of specific aspects of opportunistic resources such as preemptive job scheduling and data I/O, their efficient usage requires workflow innovations provided by the ATLAS Event Service. Thanks to the finer granularity of the Event Service data processing workflow, the opportunistic resources are used more efficiently. We report on our progress in scaling opportunistic resource usage to double-digit levels in ATLAS production.

  18. Scaling up ATLAS Event Service to production levels on opportunistic computing platforms

    CERN Document Server

    Benjamin, Douglas; The ATLAS collaboration; Ernst, Michael; Guan, Wen; Hover, John; Lesny, David; Maeno, Tadashi; Nilsson, Paul; Tsulaia, Vakhtang; van Gemmeren, Peter; Vaniachine, Alexandre; Wang, Fuquan; Wenaus, Torre

    2016-01-01

    Continued growth in public cloud and HPC resources is on track to overcome the dedicated resources available for ATLAS on the WLCG. Example of such platforms are Amazon AWS EC2 Spot Instances, Edison Cray XC30 supercomputer, backfill at the Tier-2 and Tier-3 sites, opportunistic resources at the Open Science Grid, and ATLAS High Level Trigger farm between the data taking periods. Because of opportunistic resources specifics such as preemptive job scheduling and data I/O, their efficient usage requires workflow innovations provided by the ATLAS Event Service. Thanks to the finer granularity of the Event Service data processing workflow, the opportunistic resources are used more efficiently. We report on our progress in scaling opportunistic resource usage to double-digit levels in ATLAS production.

  19. An automated meta-monitoring mobile application and front-end interface for the ATLAS computing model

    Energy Technology Data Exchange (ETDEWEB)

    Kawamura, Gen; Quadt, Arnulf [II. Physikalisches Institut, Georg-August-Universitaet Goettingen (Germany)

    2016-07-01

    Efficient administration of computing centres requires advanced tools for the monitoring and front-end interface of the infrastructure. Providing the large-scale distributed systems as a global grid infrastructure, like the Worldwide LHC Computing Grid (WLCG) and ATLAS computing, is offering many existing web pages and information sources indicating the status of the services, systems and user jobs at grid sites. A meta-monitoring mobile application which automatically collects the information could give every administrator a sophisticated and flexible interface of the infrastructure. We describe such a solution; the MadFace mobile application developed at Goettingen. It is a HappyFace compatible mobile application which has a user-friendly interface. It also becomes very feasible to automatically investigate the status and problem from different sources and provides access of the administration roles for non-experts.

  20. The Japan Lung Cancer Society–Japanese Society for Radiation Oncology consensus-based computed tomographic atlas for defining regional lymph node stations in radiotherapy for lung cancer

    International Nuclear Information System (INIS)

    Itazawa, Tomoko; Tamaki, Yukihisa; Komiyama, Takafumi; Nishimura, Yasumasa; Nakayama, Yuko; Ito, Hiroyuki; Ohde, Yasuhisa; Kusumoto, Masahiko; Sakai, Shuji; Suzuki, Kenji; Watanabe, Hirokazu; Asamura, Hisao

    2017-01-01

    The purpose of this study was to develop a consensus-based computed tomographic (CT) atlas that defines lymph node stations in radiotherapy for lung cancer based on the lymph node map of the International Association for the Study of Lung Cancer (IASLC). A project group in the Japanese Radiation Oncology Study Group (JROSG) initially prepared a draft of the atlas in which lymph node Stations 1–11 were illustrated on axial CT images. Subsequently, a joint committee of the Japan Lung Cancer Society (JLCS) and the Japanese Society for Radiation Oncology (JASTRO) was formulated to revise this draft. The committee consisted of four radiation oncologists, four thoracic surgeons and three thoracic radiologists. The draft prepared by the JROSG project group was intensively reviewed and discussed at four meetings of the committee over several months. Finally, we proposed definitions for the regional lymph node stations and the consensus-based CT atlas. This atlas was approved by the Board of Directors of JLCS and JASTRO. This resulted in the first official CT atlas for defining regional lymph node stations in radiotherapy for lung cancer authorized by the JLCS and JASTRO. In conclusion, the JLCS–JASTRO consensus-based CT atlas, which conforms to the IASLC lymph node map, was established.

  1. The ATLAS Analysis Model

    CERN Multimedia

    Amir Farbin

    The ATLAS Analysis Model is a continually developing vision of how to reconcile physics analysis requirements with the ATLAS offline software and computing model constraints. In the past year this vision has influenced the evolution of the ATLAS Event Data Model, the Athena software framework, and physics analysis tools. These developments, along with the October Analysis Model Workshop and the planning for CSC analyses have led to a rapid refinement of the ATLAS Analysis Model in the past few months. This article introduces some of the relevant issues and presents the current vision of the future ATLAS Analysis Model. Event Data Model The ATLAS Event Data Model (EDM) consists of several levels of details, each targeted for a specific set of tasks. For example the Event Summary Data (ESD) stores calorimeter cells and tracking system hits thereby permitting many calibration and alignment tasks, but will be only accessible at particular computing sites with potentially large latency. In contrast, the Analysis...

  2. The ATLAS distributed analysis system

    OpenAIRE

    Legger, F.

    2014-01-01

    In the LHC operations era, analysis of the multi-petabyte ATLAS data sample by globally distributed physicists is a challenging task. To attain the required scale the ATLAS Computing Model was designed around the concept of grid computing, realized in the Worldwide LHC Computing Grid (WLCG), the largest distributed computational resource existing in the sciences. The ATLAS experiment currently stores over 140 PB of data and runs about 140,000 concurrent jobs continuously at WLCG sites. During...

  3. Computational neuroanatomy: mapping cell-type densities in the mouse brain, simulations from the Allen Brain Atlas

    Science.gov (United States)

    Grange, Pascal

    2015-09-01

    The Allen Brain Atlas of the adult mouse (ABA) consists of digitized expression profiles of thousands of genes in the mouse brain, co-registered to a common three-dimensional template (the Allen Reference Atlas).This brain-wide, genome-wide data set has triggered a renaissance in neuroanatomy. Its voxelized version (with cubic voxels of side 200 microns) is available for desktop computation in MATLAB. On the other hand, brain cells exhibit a great phenotypic diversity (in terms of size, shape and electrophysiological activity), which has inspired the names of some well-studied cell types, such as granule cells and medium spiny neurons. However, no exhaustive taxonomy of brain cell is available. A genetic classification of brain cells is being undertaken, and some cell types have been chraracterized by their transcriptome profiles. However, given a cell type characterized by its transcriptome, it is not clear where else in the brain similar cells can be found. The ABA can been used to solve this region-specificity problem in a data-driven way: rewriting the brain-wide expression profiles of all genes in the atlas as a sum of cell-type-specific transcriptome profiles is equivalent to solving a quadratic optimization problem at each voxel in the brain. However, the estimated brain-wide densities of 64 cell types published recently were based on one series of co-registered coronal in situ hybridization (ISH) images per gene, whereas the online ABA contains several image series per gene, including sagittal ones. In the presented work, we simulate the variability of cell-type densities in a Monte Carlo way by repeatedly drawing a random image series for each gene and solving the optimization problem. This yields error bars on the region-specificity of cell types.

  4. Computing infrastructure for ATLAS data analysis in the Italian Grid cloud

    International Nuclear Information System (INIS)

    Andreazza, A; Annovi, A; Martini, A; Barberis, D; Brunengo, A; Corosu, M; Campana, S; Girolamo, A Di; Carlino, G; Doria, A; Merola, L; Musto, E; Ciocca, C; Jha, M K; Cobal, M; Pascolo, F; Salvo, A De; Luminari, L; Sanctis, U De; Galeazzi, F

    2011-01-01

    ATLAS data are distributed centrally to Tier-1 and Tier-2 sites. The first stages of data selection and analysis take place mainly at Tier-2 centres, with the final, iterative and interactive, stages taking place mostly at Tier-3 clusters. The Italian ATLAS cloud consists of a Tier-1, four Tier-2s, and Tier-3 sites at each institute. Tier-3s that are grid-enabled are used to test code that will then be run on a larger scale at Tier-2s. All Tier-3s offer interactive data access to their users and the possibility to run PROOF. This paper describes the hardware and software infrastructure choices taken, the operational experience after 10 months of LHC data, and discusses site performances.

  5. Computed tomography of the retroperitoneum: an anatomical and pathological atlas with emphasis on the fascial planes

    International Nuclear Information System (INIS)

    Feldberg, M.A.M.

    1983-01-01

    The aim of this thesis is to provide a descriptive clinical pathological CT atlas of a range of conditions involving retroperitoneum and neighbouring organs and structures (excluding the pelvic part of the retroperitoneum). Chapter 1 describes the patient material studied, some aspects of CT techniques and patient handling. Chapter 2 describes the anatomy of the renal fascia based upon reports derived from the literature and is followed by our CT observations in more than 5000 abdominal CT examinations. In short it is an anatomical CT atlas. Chapters 3, 4 and 5 deal with reactions of the fascial structures in different pathological conditions caused by major disease entities. The patients were scanned for these diseases, of which anatomical topographical appearances and spread are described in the general considerations, followed by CT findings and illustrative cases, combined with abstracted experience from other workers. (Auth.)

  6. AGIS: The ATLAS Grid Information System

    CERN Document Server

    Anisenkov, A; The ATLAS collaboration; Klimentov, A; Oleynik, D; Petrosyan, A

    2014-01-01

    In this paper we describe ATLAS Grid Information System (AGIS), the system designed to integrate configuration and status information about resources, services and topology of the computing infrastructure used by ATLAS Distributed Computing applications and services.

  7. AGIS: The ATLAS Grid Information System

    OpenAIRE

    Anisenkov, A; Di Girolamo, A; Klimentov, A; Oleynik, D; Petrosyan, A

    2013-01-01

    In this paper we describe ATLAS Grid Information System (AGIS), the system designed to integrate configuration and status information about resources, services and topology of the computing infrastructure used by ATLAS Distributed Computing applications and services.

  8. Computation of an MRI brain atlas from a population of Parkinson’s disease patients

    Science.gov (United States)

    Angelidakis, L.; Papageorgiou, I. E.; Damianou, C.; Psychogios, M. N.; Lingor, P.; von Eckardstein, K.; Hadjidemetriou, S.

    2017-11-01

    Parkinson’s Disease (PD) is a degenerative disorder of the brain. This study presents an MRI-based brain atlas of PD to characterize associated alterations for diagnostic and interventional purposes. The atlas standardizes primarily the implicated subcortical regions such as the globus pallidus (GP), substantia nigra (SN), subthalamic nucleus (STN), caudate nucleus (CN), thalamus (TH), putamen (PUT), and red nucleus (RN). The data were 3.0 T MRI brain images from 16 PD patients and 10 matched controls. The images used were T1-weighted (T 1 w), T2-weighted (T 2 w) images, and Susceptibility Weighted Images (SWI). The T1w images were the reference for the inter-subject non-rigid registration available from 3DSlicer. Anatomic labeling was achieved with BrainSuite and regions were refined with the level sets segmentation of ITK-Snap. The subcortical centers were analyzed for their volume and signal intensity. Comparison with an age-matched control group unravels a significant PD-related T1w signal loss in the striatum (CN and PUT) centers, but approximately a constant volume. The results in this study improve MRI based PD localization and can lead to the development of novel biomarkers.

  9. Pocket atlas of sectional anatomy: computed tomography and magnetic resonance imaging. Vol. 3. Spine, extremities, joints

    Energy Technology Data Exchange (ETDEWEB)

    Moeller, T.B.; Reif, E. [Caritas Hospital, Dillingen (Germany). Dept. of Radiology

    2007-07-01

    Magnetic resonance imaging (MRI) of the musculoskeletal system is an established and important component in the diagnosis of diseases of the joints, soft tissues, bones, and bone marrow. We are therefore pleased to collect together images of the joints and the spinal column in a separate volume on the musculoskeletal system. Demonstrating the growing importance of new developments in MRI in recent years, with ever-increasing resolution, many images were acquired with 3-tesla units. We are deeply grateful to the manufacturers, Siemens and Philips, for making this possible. We believe that colored atlases are the ideal medium to represent the highly detailed images achieved nowadays with improved resolution techniques. Volume 3 of the Pocket Atlas of Sectional Anatomay provides a color illustration facing each magnetic resonance image, as in the preceding volumes on the skull, thorax, and abdomen. To ensure the greatest possible precision in details, we still produce these illustrations ourselves. Each is accompanied by a sectional image and an orientation aid. Uniform color schemes ensure optimal clarity, as similar structures, such as arteries, veins, nerves, tendons, etc., are consistently represented in the same color. Individual muscle groups are represented uniformly, but differentiated from other muscle groups, so that classification is possible even when numerous groups of muscles are shown in the same image. Maximal lucidity prevails even in highly detailed representations. This is made possible by the high quality of the production and printing process that are characteristic of Thieme International. (orig.)

  10. AGIS: The ATLAS Grid Information System

    CERN Document Server

    Anisenkov, Alexey; Di Girolamo, Alessandro; Gayazov, Stavro; Klimentov, Alexei; Oleynik, Danila; Senchenko, Alexander

    2012-01-01

    ATLAS is a particle physics experiment at the Large Hadron Collider at CERN. The experiment produces petabytes of data annually through simulation production and tens petabytes of data per year from the detector itself. The ATLAS Computing model embraces the Grid paradigm and a high degree of decentralization and computing resources able to meet ATLAS requirements of petabytes scale data operations. In this paper we present ATLAS Grid Information System (AGIS) designed to integrate configuration and status information about resources, services and topology of whole ATLAS Grid needed by ATLAS Distributed Computing applications and services.

  11. A computational atlas of the hippocampal formation using ex vivo, ultra-high resolution MRI: Application to adaptive segmentation of in vivo MRI.

    Science.gov (United States)

    Iglesias, Juan Eugenio; Augustinack, Jean C; Nguyen, Khoa; Player, Christopher M; Player, Allison; Wright, Michelle; Roy, Nicole; Frosch, Matthew P; McKee, Ann C; Wald, Lawrence L; Fischl, Bruce; Van Leemput, Koen

    2015-07-15

    Automated analysis of MRI data of the subregions of the hippocampus requires computational atlases built at a higher resolution than those that are typically used in current neuroimaging studies. Here we describe the construction of a statistical atlas of the hippocampal formation at the subregion level using ultra-high resolution, ex vivo MRI. Fifteen autopsy samples were scanned at 0.13 mm isotropic resolution (on average) using customized hardware. The images were manually segmented into 13 different hippocampal substructures using a protocol specifically designed for this study; precise delineations were made possible by the extraordinary resolution of the scans. In addition to the subregions, manual annotations for neighboring structures (e.g., amygdala, cortex) were obtained from a separate dataset of in vivo, T1-weighted MRI scans of the whole brain (1mm resolution). The manual labels from the in vivo and ex vivo data were combined into a single computational atlas of the hippocampal formation with a novel atlas building algorithm based on Bayesian inference. The resulting atlas can be used to automatically segment the hippocampal subregions in structural MRI images, using an algorithm that can analyze multimodal data and adapt to variations in MRI contrast due to differences in acquisition hardware or pulse sequences. The applicability of the atlas, which we are releasing as part of FreeSurfer (version 6.0), is demonstrated with experiments on three different publicly available datasets with different types of MRI contrast. The results show that the atlas and companion segmentation method: 1) can segment T1 and T2 images, as well as their combination, 2) replicate findings on mild cognitive impairment based on high-resolution T2 data, and 3) can discriminate between Alzheimer's disease subjects and elderly controls with 88% accuracy in standard resolution (1mm) T1 data, significantly outperforming the atlas in FreeSurfer version 5.3 (86% accuracy) and

  12. An atlas of the (near) future: cognitive computing applications for medical imaging (Conference Presentation)

    Science.gov (United States)

    LeGrand, Anne

    2017-02-01

    The role of medical imaging in global health systems is literally fundamental. Like labs, medical images are used at one point or another in almost every high cost, high value episode of care. CT scans, mammograms, and x-rays, for example, "atlas" the body and help chart a course forward for a patient's care team. Imaging precision has improved as a result of technological advancements and breakthroughs in related medical research. Those advancements also bring with them exponential growth in medical imaging data. As IBM trains Watson to "see" medical images, Ms. Le Grand will discuss recent advances made by Watson Health and explore the potential value of "augmented intelligence" to assist healthcare providers like radiologists and cardiologists, as well as the patients they serve.

  13. AGIS: The ATLAS Grid Information System

    Science.gov (United States)

    Anisenkov, A.; Di Girolamo, A.; Klimentov, A.; Oleynik, D.; Petrosyan, A.; Atlas Collaboration

    2014-06-01

    ATLAS, a particle physics experiment at the Large Hadron Collider at CERN, produced petabytes of data annually through simulation production and tens of petabytes of data per year from the detector itself. The ATLAS computing model embraces the Grid paradigm and a high degree of decentralization and computing resources able to meet ATLAS requirements of petabytes scale data operations. In this paper we describe the ATLAS Grid Information System (AGIS), designed to integrate configuration and status information about resources, services and topology of the computing infrastructure used by the ATLAS Distributed Computing applications and services.

  14. ATLAS Open Data project

    CERN Document Server

    The ATLAS collaboration

    2018-01-01

    The current ATLAS model of Open Access to recorded and simulated data offers the opportunity to access datasets with a focus on education, training and outreach. This mandate supports the creation of platforms, projects, software, and educational products used all over the planet. We describe the overall status of ATLAS Open Data (http://opendata.atlas.cern) activities, from core ATLAS activities and releases to individual and group efforts, as well as educational programs, and final web or software-based (and hard-copy) products that have been produced or are under development. The relatively large number and heterogeneous use cases currently documented is driving an upcoming release of more data and resources for the ATLAS Community and anyone interested to explore the world of experimental particle physics and the computer sciences through data analysis.

  15. A GRID-type computation for the tile calorimeter of the ATLAS experiment at CERN

    International Nuclear Information System (INIS)

    Maidantchik, Carmen; Seixas, Jose Manoel de; Lanza, Marcelo Luiz Drumond; Santelli, Rafael

    2002-01-01

    For the hadronic calorimeter of ATLAS, the tile transfer has been developed as a Web system to facilitate the transferring of data to that are produced during calibration test beam periods. It automatically searches, stages and provides a link to download the selected data stored at a remote file center. The system has an interface with the Run Info Database, which contains the description of all test beam runs. It is also possible to receive a link to the files by e-mail, avoiding waiting time until the process is finished. In order to optimize the file transmission, the system is connected to a central repository that stores information of the latest accesses. Once a user connects to the tile transfer, he/she can become a file server to other users. Thus, at different servers, the selected file is split into several pieces. Each piece is sent from one server in parallel and built up together in the final destination. We are currently working in the 2.0 version, dealing with security and efficiency requirements. The whole system runs under the Web and it was developed in C language, Php and Java Script. Tile Transfer allows that the file administration be geographically distributed, avoiding an overloaded at the central repository. We also foresee the integration with analysis tools by remote Web access and the publication of the results to the whole community. Among the benefits of this proposal, one can underline an effective management of data across the Net of users. (author)

  16. Anatomic atlas for computed tomography in the mesaticephalic dog: head and neck

    International Nuclear Information System (INIS)

    George, T.F. II; Smallwood, J.E.

    1992-01-01

    The purpose of this study was to produce a comprehensive anatomic atlas of CT anatomy of the dog for use by veterinary radiologists, clinicians, and surgeons. Whole-body CT images of two mature beagle dogs were made with the dogs supported in sternal recumbency and using a slice thickness of 13 mm. The head was scanned using high-resolution imaging with a slice thickness of 8 mm. At the end of the CT session, each dog was euthanized, and while carefully maintaining the same position, the body was placed in a walk-in freezer until completely frozen. The body was then sectioned at 13-mm (head at 8-mm) intervals, with the cuts matched as closely as possible to the CT slices. The forzen sections were cleaned, photographed, and radiographed using xeroradiography. Each CT image was studied and compared with its corresponding xeroradiograph and anatomic section to assist in the accurate identification of specific structures. Intact, sagittally sectioned, and disarticulated dog skulls were used as reference models. Clinically relevant anatomic structures were identified and labeled in the three corresponding photographs (CT image, xeroradiograph, and anatomic section). In this paper, the CT anatomy of the head and neck of the mesaticephalic dog is presented

  17. Anatomic atlas for computed tomography in the mesaticephalic dog: caudal abdomen and pelvis

    International Nuclear Information System (INIS)

    Smallwood, J.E.; George, T. II.

    1993-01-01

    The purpose of this study was to produce a comprehensive anatomic atlas of CT anatomy of the dog for use by veterinary radiologists, clinicians, and surgeons. Whole-body CT images of two mature beagle dogs were made with the dogs supported in sternal recumbency and using a slice thickness of 13 mm. At the end of the CT session, each dog was euthanized, and while carefully maintaining the same position, the body was frozen. The body was then sectioned at 13-mm intervals, with the cuts matched as closely as possible to the CT slices. The frozen sections were cleaned, photographed, and radiographed using xeroradiography. Each CT image was studied and compared with its corresponding xeroradiograph and anatomic section to assist in the accurate identification of specific structures. Clinically relevant anatomic structures were identified and labeled in the three corresponding photographs (CT image, xeroradiograph, and anatomic section). In previous papers, the head and neck, and the thorax and cranial abdomen of the mesaticephalic (beagle) dog were presented. In this paper, the caudal part of the abdomen and pelvis of the bitch and male dog are presented

  18. A GRID-like computing proposal for the Tile calorimeter of the ATLAS experiment

    CERN Document Server

    Maidantchik, C; Lanza, M L D; Santelli, R; Damazio, D O

    2004-01-01

    For the hadronic calorimeter of the ATLAS detector, the TileTransfer has been developed as a Web system to facilitate the transferring of data that are produced during calibration testbeam periods. It automatically searches, stages and provides a link to download the selected data stored at a remote file center. The system has an interface with the Run Info Database, which contains the description of all test beam runs. In order to optimize the file transmission, the system is connected to a central repository that stores information of the latest accesses. Once a client host connects to the TileTransfer, it can become a file server to other users. At the servers, the selected file is split into several pieces and each piece is sent in parallel and built up together in the final destination. TileTransfer allows that the rile administration be geographically distributed, avoiding an overloaded at the central repository. We also foresee the integration with analysis tools by remote Web access and the publicatio...

  19. AGIS: The ATLAS Grid Information System

    OpenAIRE

    Anisenkov, Alexey; Belov, Sergey; Di Girolamo, Alessandro; Gayazov, Stavro; Klimentov, Alexei; Oleynik, Danila; Senchenko, Alexander

    2012-01-01

    ATLAS is a particle physics experiment at the Large Hadron Collider at CERN. The experiment produces petabytes of data annually through simulation production and tens petabytes of data per year from the detector itself. The ATLAS Computing model embraces the Grid paradigm and a high degree of decentralization and computing resources able to meet ATLAS requirements of petabytes scale data operations. In this paper we present ATLAS Grid Information System (AGIS) designed to integrate configurat...

  20. Visual Cluster Analysis for Computing Tasks at Workflow Management System of the ATLAS Experiment

    CERN Document Server

    Grigoryeva, Maria; The ATLAS collaboration

    2018-01-01

    Hundreds of petabytes of experimental data in high energy and nuclear physics (HENP) have already been obtained by unique scientific facilities such as LHC, RHIC, KEK. As the accelerators are being modernized (energy and luminosity were increased), data volumes are rapidly growing and have reached the exabyte scale, that also affects the increasing the number of analysis and data processing tasks, that are competing continuously for computational resources. The increase of processing tasks causes an increase in the performance of the computing environment by the involvement of high-performance computing resources, and forming a heterogeneous distributed computing environment (hundreds of distributed computing centers). In addition, errors happen to occur while executing tasks for data analysis and processing, which are caused by software and hardware failures. With a distributed model of data processing and analysis, the optimization of data management and workload systems becomes a fundamental task, and the ...

  1. Computer Vision Evidence Supporting Craniometric Alignment of Rat Brain Atlases to Streamline Expert-Guided, First-Order Migration of Hypothalamic Spatial Datasets Related to Behavioral Control

    Science.gov (United States)

    Khan, Arshad M.; Perez, Jose G.; Wells, Claire E.; Fuentes, Olac

    2018-01-01

    The rat has arguably the most widely studied brain among all animals, with numerous reference atlases for rat brain having been published since 1946. For example, many neuroscientists have used the atlases of Paxinos and Watson (PW, first published in 1982) or Swanson (S, first published in 1992) as guides to probe or map specific rat brain structures and their connections. Despite nearly three decades of contemporaneous publication, no independent attempt has been made to establish a basic framework that allows data mapped in PW to be placed in register with S, or vice versa. Such data migration would allow scientists to accurately contextualize neuroanatomical data mapped exclusively in only one atlas with data mapped in the other. Here, we provide a tool that allows levels from any of the seven published editions of atlases comprising three distinct PW reference spaces to be aligned to atlas levels from any of the four published editions representing S reference space. This alignment is based on registration of the anteroposterior stereotaxic coordinate (z) measured from the skull landmark, Bregma (β). Atlas level alignments performed along the z axis using one-dimensional Cleveland dot plots were in general agreement with alignments obtained independently using a custom-made computer vision application that utilized the scale-invariant feature transform (SIFT) and Random Sample Consensus (RANSAC) operation to compare regions of interest in photomicrographs of Nissl-stained tissue sections from the PW and S reference spaces. We show that z-aligned point source data (unpublished hypothalamic microinjection sites) can be migrated from PW to S space to a first-order approximation in the mediolateral and dorsoventral dimensions using anisotropic scaling of the vector-formatted atlas templates, together with expert-guided relocation of obvious outliers in the migrated datasets. The migrated data can be contextualized with other datasets mapped in S space, including

  2. Computer Vision Evidence Supporting Craniometric Alignment of Rat Brain Atlases to Streamline Expert-Guided, First-Order Migration of Hypothalamic Spatial Datasets Related to Behavioral Control

    Directory of Open Access Journals (Sweden)

    Arshad M. Khan

    2018-05-01

    Full Text Available The rat has arguably the most widely studied brain among all animals, with numerous reference atlases for rat brain having been published since 1946. For example, many neuroscientists have used the atlases of Paxinos and Watson (PW, first published in 1982 or Swanson (S, first published in 1992 as guides to probe or map specific rat brain structures and their connections. Despite nearly three decades of contemporaneous publication, no independent attempt has been made to establish a basic framework that allows data mapped in PW to be placed in register with S, or vice versa. Such data migration would allow scientists to accurately contextualize neuroanatomical data mapped exclusively in only one atlas with data mapped in the other. Here, we provide a tool that allows levels from any of the seven published editions of atlases comprising three distinct PW reference spaces to be aligned to atlas levels from any of the four published editions representing S reference space. This alignment is based on registration of the anteroposterior stereotaxic coordinate (z measured from the skull landmark, Bregma (β. Atlas level alignments performed along the z axis using one-dimensional Cleveland dot plots were in general agreement with alignments obtained independently using a custom-made computer vision application that utilized the scale-invariant feature transform (SIFT and Random Sample Consensus (RANSAC operation to compare regions of interest in photomicrographs of Nissl-stained tissue sections from the PW and S reference spaces. We show that z-aligned point source data (unpublished hypothalamic microinjection sites can be migrated from PW to S space to a first-order approximation in the mediolateral and dorsoventral dimensions using anisotropic scaling of the vector-formatted atlas templates, together with expert-guided relocation of obvious outliers in the migrated datasets. The migrated data can be contextualized with other datasets mapped in S

  3. A novel computed method to reconstruct the bilateral digital interarticular channel of atlas and its use on the anterior upper cervical screw fixation

    Directory of Open Access Journals (Sweden)

    Ai-Min Wu

    2016-02-01

    Full Text Available Purpose. To investigate a novel computed method to reconstruct the bilateral digital interarticular channel of atlas and its potential use on the anterior upper cervical screw fixation. Methods. We have used the reverse engineering software (image-processing software and computer-aided design software to create the approximate and optimal digital interarticular channel of atlas for 60 participants. Angles of channels, diameters of inscribed circles, long and short axes of ellipses were measured and recorded, and gender-specific analysis was also performed. Results. The channels provided sufficient space for one or two screws, and the parameters of channels are described. While the channels of females were smaller than that of males, no significant difference of angles between males and females were observed. Conclusion. Our study demonstrates the radiological features of approximate digital interarticular channels, optimal digital interarticular channels of atlas, and provides the reference trajectory of anterior transarticular screws and anterior occiput-to-axis screws. Additionally, we provide a protocol that can help make a pre-operative plan for accurate placement of anterior transarticular screws and anterior occiput-to-axis screws.

  4. An experimental and computational framework to build a dynamic protein atlas of human cell division

    OpenAIRE

    Kavur, Marina; Kavur, Marina; Kavur, Marina; Ellenberg, Jan; Peters, Jan-Michael; Ladurner, Rene; Martinic, Marina; Kueblbeck, Moritz; Nijmeijer, Bianca; Wachsmuth, Malte; Koch, Birgit; Walther, Nike; Politi, Antonio; Heriche, Jean-Karim; Hossain, M.

    2017-01-01

    Essential biological functions of human cells, such as division, require the tight coordination of the activity of hundreds of proteins in space and time. While live cell imaging is a powerful tool to study the distribution and dynamics of individual proteins after fluorescence tagging, it has not yet been used to map protein networks due to the lack of systematic and quantitative experimental and computational approaches. Using the cell and nuclear boundaries as landmarks, we generated a 4D ...

  5. ATLAS-Canada Network

    Energy Technology Data Exchange (ETDEWEB)

    Gable, I; Sobie, R J [HEPnet/Canada, Victoria, BC (Canada); Bedinelli, M; Butterworth, S; Groer, L; Kupchinsky, V [University of Toronto, Toronto, ON (Canada); Caron, B; McDonald, S; Payne, C [TRIUMF Laboratory, Vancouver, BC (Canada); Chambers, R [University of Alberta, Edmonton, AB (Canada); Fitzgerald, B [University of Victoria, Victoria, BC (Canada); Hatem, R; Marshall, P; Pobric, D [CANARIE Inc., Ottawa, ON (Canada); Maddalena, P; Mercure, P; Robertson, S; Rochefort, M [McGill University, Montreal, QC (Canada); McWilliam, D [BCNet, Vancouver, BC (Canada); Siegert, M [Simon Fraser University, Burnaby, BC (Canada)], E-mail: igable@uvic.ca (and others)

    2008-12-15

    The ATLAS-Canada computing model consists of a WLCG Tier-1 computing centre located at the TRIUMF Laboratory in Vancouver, Canada, and two distributed Tier-2 computing centres in eastern and western Canadian universities. The TRIUMF Tier-1 is connected to the CERN Tier-0 via a 10G dedicated circuit provided by CANARIE. The Canadian institutions hosting Tier-2 facilities are connected to TRIUMF via 1G lightpaths, and routing between Tier-2s occurs through TRIUMF. This paper discusses the architecture of the ATLAS-Canada network, the challenges of building the network, and the future plans.

  6. 26th February 2009 - US Google Vice President and Chief Internet Evangelist V. Cerf signing the guest book with Director for research and Computing S. Bertolucci; visiting ATLAS control room and experimental area with Collaboration Spokesperson P. Jenni.

    CERN Multimedia

    Maximilien Brice

    2009-01-01

    HI-0902038 05: IT Department Head, F. Hemmer; US Google Vice President and Chief Internet Evangelist V. Cerf; Computing Security Officer and Colloquium Convenor D. R. Myers; Member of the Internet Society Advisory Council F. Flückiger; Director for Research and Scientific Computing, S. Bertolucci ; Honorary Staff Member, B. Segal. HI-0902038 16: Computing Security Officer and Colloquium Convenor D. R. Myers; UC Irvine, ATLAS Deputy Spokesperson elect A. J. Lankford; US Google Vice President and Chief Internet Evangelist V. Cerf; ATLAS Collaboration Spokesperson P. Jenni; IT Department Head, F. Hemmer.

  7. ATLAS DDM integration in ARC

    DEFF Research Database (Denmark)

    Behrmann, Gerd; Cameron, David; Ellert, Mattias

    by the DQ2 software. Managing ATLAS data within NDGF and between NDGF and other Grids used by ATLAS (the LHC Computing Grid and the Open Science Grid) presents a unique challenge for several reasons. Firstly, the entry point for data, the Tier 1 centre, is physically distributed among heterogeneous...

  8. ATLAS cloud R and D

    International Nuclear Information System (INIS)

    Panitkin, Sergey; Bejar, Jose Caballero; Hover, John; Zaytsev, Alexander; Megino, Fernando Barreiro; Girolamo, Alessandro Di; Kucharczyk, Katarzyna; Llamas, Ramon Medrano; Benjamin, Doug; Gable, Ian; Paterson, Michael; Sobie, Randall; Taylor, Ryan; Hendrix, Val; Love, Peter; Ohman, Henrik; Walker, Rodney

    2014-01-01

    The computing model of the ATLAS experiment was designed around the concept of grid computing and, since the start of data taking, this model has proven very successful. However, new cloud computing technologies bring attractive features to improve the operations and elasticity of scientific distributed computing. ATLAS sees grid and cloud computing as complementary technologies that will coexist at different levels of resource abstraction, and two years ago created an R and D working group to investigate the different integration scenarios. The ATLAS Cloud Computing R and D has been able to demonstrate the feasibility of offloading work from grid to cloud sites and, as of today, is able to integrate transparently various cloud resources into the PanDA workload management system. The ATLAS Cloud Computing R and D is operating various PanDA queues on private and public resources and has provided several hundred thousand CPU days to the experiment. As a result, the ATLAS Cloud Computing R and D group has gained a significant insight into the cloud computing landscape and has identified points that still need to be addressed in order to fully utilize this technology. This contribution will explain the cloud integration models that are being evaluated and will discuss ATLAS' learning during the collaboration with leading commercial and academic cloud providers.

  9. ATLAS Cloud R&D

    Science.gov (United States)

    Panitkin, Sergey; Barreiro Megino, Fernando; Caballero Bejar, Jose; Benjamin, Doug; Di Girolamo, Alessandro; Gable, Ian; Hendrix, Val; Hover, John; Kucharczyk, Katarzyna; Medrano Llamas, Ramon; Love, Peter; Ohman, Henrik; Paterson, Michael; Sobie, Randall; Taylor, Ryan; Walker, Rodney; Zaytsev, Alexander; Atlas Collaboration

    2014-06-01

    The computing model of the ATLAS experiment was designed around the concept of grid computing and, since the start of data taking, this model has proven very successful. However, new cloud computing technologies bring attractive features to improve the operations and elasticity of scientific distributed computing. ATLAS sees grid and cloud computing as complementary technologies that will coexist at different levels of resource abstraction, and two years ago created an R&D working group to investigate the different integration scenarios. The ATLAS Cloud Computing R&D has been able to demonstrate the feasibility of offloading work from grid to cloud sites and, as of today, is able to integrate transparently various cloud resources into the PanDA workload management system. The ATLAS Cloud Computing R&D is operating various PanDA queues on private and public resources and has provided several hundred thousand CPU days to the experiment. As a result, the ATLAS Cloud Computing R&D group has gained a significant insight into the cloud computing landscape and has identified points that still need to be addressed in order to fully utilize this technology. This contribution will explain the cloud integration models that are being evaluated and will discuss ATLAS' learning during the collaboration with leading commercial and academic cloud providers.

  10. Characterizing the human hippocampus in aging and Alzheimer's disease using a computational atlas derived from ex vivo MRI and histology.

    Science.gov (United States)

    Adler, Daniel H; Wisse, Laura E M; Ittyerah, Ranjit; Pluta, John B; Ding, Song-Lin; Xie, Long; Wang, Jiancong; Kadivar, Salmon; Robinson, John L; Schuck, Theresa; Trojanowski, John Q; Grossman, Murray; Detre, John A; Elliott, Mark A; Toledo, Jon B; Liu, Weixia; Pickup, Stephen; Miller, Michael I; Das, Sandhitsu R; Wolk, David A; Yushkevich, Paul A

    2018-04-17

    Although the hippocampus is one of the most studied structures in the human brain, limited quantitative data exist on its 3D organization, anatomical variability, and effects of disease on its subregions. Histological studies provide restricted reference information due to their 2D nature. In this paper, high-resolution (∼200 × 200 × 200 μm 3 ) ex vivo MRI scans of 31 human hippocampal specimens are combined using a groupwise diffeomorphic registration approach into a 3D probabilistic atlas that captures average anatomy and anatomic variability of hippocampal subfields. Serial histological imaging in 9 of the 31 specimens was used to label hippocampal subfields in the atlas based on cytoarchitecture. Specimens were obtained from autopsies in patients with a clinical diagnosis of Alzheimer's disease (AD; 9 subjects, 13 hemispheres), of other dementia (nine subjects, nine hemispheres), and in subjects without dementia (seven subjects, nine hemispheres), and morphometric analysis was performed in atlas space to measure effects of age and AD on hippocampal subfields. Disproportional involvement of the cornu ammonis (CA) 1 subfield and stratum radiatum lacunosum moleculare was found in AD, with lesser involvement of the dentate gyrus and CA2/3 subfields. An association with age was found for the dentate gyrus and, to a lesser extent, for CA1. Three-dimensional patterns of variability and disease and aging effects discovered via the ex vivo hippocampus atlas provide information highly relevant to the active field of in vivo hippocampal subfield imaging.

  11. Reconstruction and identification of electrons in the Atlas experiment. Setup of a Tier 2 of the computing grid; Reconstruction et identification des electrons dans l'experience Atlas. Participation a la mise en place d'un Tier 2 de la grille de calcul

    Energy Technology Data Exchange (ETDEWEB)

    Derue, F

    2008-03-15

    The origin of the mass of elementary particles is linked to the electroweak symmetry breaking mechanism. Its study will be one of the main efforts of the Atlas experiment at the Large Hadron Collider of CERN, starting in 2008. In most cases, studies will be limited by our knowledge of the detector performances, as the precision of the energy reconstruction or the efficiency to identify particles. This manuscript presents a work dedicated to the reconstruction of electrons in the Atlas experiment with simulated data and data taken during the combined test beam of 2004. The analysis of the Atlas data implies the use of a huge amount of computing and storage resources which brought to the development of a world computing grid. (author)

  12. ATLAS-AWS

    International Nuclear Information System (INIS)

    Gehrcke, Jan-Philip; Stonjek, Stefan; Kluth, Stefan

    2010-01-01

    We show how the ATLAS offline software is ported on the Amazon Elastic Compute Cloud (EC2). We prepare an Amazon Machine Image (AMI) on the basis of the standard ATLAS platform Scientific Linux 4 (SL4). Then an instance of the SLC4 AMI is started on EC2 and we install and validate a recent release of the ATLAS offline software distribution kit. The installed software is archived as an image on the Amazon Simple Storage Service (S3) and can be quickly retrieved and connected to new SL4 AMI instances using the Amazon Elastic Block Store (EBS). ATLAS jobs can then configure against the release kit using the ATLAS configuration management tool (cmt) in the standard way. The output of jobs is exported to S3 before the SL4 AMI is terminated. Job status information is transferred to the Amazon SimpleDB service. The whole process of launching instances of our AMI, starting, monitoring and stopping jobs and retrieving job output from S3 is controlled from a client machine using python scripts implementing the Amazon EC2/S3 API via the boto library working together with small scripts embedded in the SL4 AMI. We report our experience with setting up and operating the system using standard ATLAS job transforms.

  13. ATLAS & Google - The Data Ocean Project

    CERN Document Server

    Lassnig, Mario; The ATLAS collaboration

    2018-01-01

    With the LHC High Luminosity upgrade the workload and data management systems are facing new major challenges. To address those challenges ATLAS and Google agreed to cooperate on a project to connect Google Cloud Storage and Compute Engine to the ATLAS computing environment. The idea is to allow ATLAS to explore the use of different computing models, to allow ATLAS user analysis to benefit from the Google infrastructure, and to give Google real science use cases to improve their cloud platform. Making the output of a distributed analysis from the grid quickly available to the analyst is a difficult problem. Redirecting the analysis output to Google Cloud Storage can provide an alternative, faster solution for the analyst. First, Google's Cloud Storage will be connected to the ATLAS Data Management System Rucio. The second part aims to let jobs run on Google Compute Engine, accessing data from either ATLAS storage or Google Cloud Storage. The third part involves Google implementing a global redirection between...

  14. ATLAS production system

    CERN Document Server

    Borodin, Mikhail; The ATLAS collaboration; De, Kaushik; Klimentov, Alexei; Golubkov, Dmitry; Maeno, Tadashi; Mashinistov, Ruslan; Wenaus, Torre; Padolski, Siarhei

    2016-01-01

    The second generation of the ATLAS production system called ProdSys2 is a distributed workload manager which used by thousands of physicists to analyze the data remotely, with the volume of processed data is beyond the exabyte scale, across a more than hundred heterogeneous sites. It achieves high utilization by combining dynamic job definition based on many criterias, such as input and output size, memory requirements and CPU consumption with manageable scheduling policies and by supporting different kind of computational resources, such as GRID, clouds, supercomputers and volunteering computers. Besides jobs definition Production System also includes flexible web user interface, which implements user-friendly environment for main ATLAS workflows, e.g. simple way of combining different data flows, and real-time monitoring, optimised for using with huge amount of information to present. We present an overview of the ATLAS Production System major components: job and task definition, workflow manager web user i...

  15. The ATLAS Distributed Data Management project: Past and Future

    CERN Document Server

    Garonne, V; The ATLAS collaboration; Lassnig, M; Molfetas, A; Barisits, M; Beermann, T; Nairz, A; Goossens, L; Barreiro Megino, F; Serfon, C; Oleynik, D; Petrosyan, A

    2012-01-01

    ATLAS has recorded almost 8PB of RAW data since the LHC started running at the end of 2009. Many more derived data products and complimentary simulation data have also been produced by the collaboration and, in total, 90PB is currently stored in the Worldwide LHC Computing Grid by ATLAS. All this data is managed by the ATLAS Distributed Data Management system, called Don Quijote 2 (DQ2). DQ2 has evolved rapidly to help ATLAS Computing operations manage these large quantities of data across the many grid sites at which ATLAS runs, and to help ATLAS physicists get access to this data. In this paper, we describe new and improved DQ2 services, and the experience of data management operation in ATLAS computing, showing how these services enable the management of petabyte scale computing operations. We also present the concepts of the new version of the ATLAS Distributed Data Management (DDM) system, Rucio.

  16. The ATLAS Distributed Data Management project: Past and Future

    International Nuclear Information System (INIS)

    Garonne, Vincent; Stewart, Graeme A; Lassnig, Mario; Molfetas, Angelos; Barisits, Martin; Beermann, Thomas; Nairz, Armin; Goossens, Luc; Barreiro Megino, Fernando; Serfon, Cedric; Oleynik, Danila; Petrosyan, Artem

    2012-01-01

    ATLAS has recorded more than 8 petabyte(PB) of RAW data since the LHC started running at the end of 2009. Many more derived data products and complimentary simulation data have also been produced by the collaboration and, in total, 90PB are currently stored in the Worldwide LHC Computing Grid by ATLAS. All these data are managed by the ATLAS Distributed Data Management system, called Don Quijote 2 (DQ2). DQ2 has evolved rapidly to help ATLAS Computing operations manage these large quantities of data across the many grid sites at which ATLAS runs, and to help ATLAS physicists get access to these data. In this paper, we describe new and improved DQ2 services, and the experience of data management operation in ATLAS computing, showing how these services enable the management of PB scale computing operations. We also present the concepts of the new version of the ATLAS Distributed Data Management (DDM) system, Rucio.

  17. The ATLAS Distributed Data Management project: Past and Future

    Science.gov (United States)

    Garonne, Vincent; Stewart, Graeme A.; Lassnig, Mario; Molfetas, Angelos; Barisits, Martin; Beermann, Thomas; Nairz, Armin; Goossens, Luc; Barreiro Megino, Fernando; Serfon, Cedric; Oleynik, Danila; Petrosyan, Artem

    2012-12-01

    ATLAS has recorded more than 8 petabyte(PB) of RAW data since the LHC started running at the end of 2009. Many more derived data products and complimentary simulation data have also been produced by the collaboration and, in total, 90PB are currently stored in the Worldwide LHC Computing Grid by ATLAS. All these data are managed by the ATLAS Distributed Data Management system, called Don Quijote 2 (DQ2). DQ2 has evolved rapidly to help ATLAS Computing operations manage these large quantities of data across the many grid sites at which ATLAS runs, and to help ATLAS physicists get access to these data. In this paper, we describe new and improved DQ2 services, and the experience of data management operation in ATLAS computing, showing how these services enable the management of PB scale computing operations. We also present the concepts of the new version of the ATLAS Distributed Data Management (DDM) system, Rucio.

  18. ATLAS Software Installation on Supercomputers

    CERN Document Server

    Undrus, Alexander; The ATLAS collaboration

    2018-01-01

    PowerPC and high performance computers (HPC) are important resources for computing in the ATLAS experiment. The future LHC data processing will require more resources than Grid computing, currently using approximately 100,000 cores at well over 100 sites, can provide. Supercomputers are extremely powerful as they use resources of hundreds of thousands CPUs joined together. However their architectures have different instruction sets. ATLAS binary software distributions for x86 chipsets do not fit these architectures, as emulation of these chipsets results in huge performance loss. This presentation describes the methodology of ATLAS software installation from source code on supercomputers. The installation procedure includes downloading the ATLAS code base as well as the source of about 50 external packages, such as ROOT and Geant4, followed by compilation, and rigorous unit and integration testing. The presentation reports the application of this procedure at Titan HPC and Summit PowerPC at Oak Ridge Computin...

  19. Methods and computing challenges of the realistic simulation of physics events in the presence of pile-up in the ATLAS experiment

    CERN Document Server

    Chapman, J D; The ATLAS collaboration

    2014-01-01

    We are now in a regime where we observe substantial multiple proton-proton collisions within each filled LHC bunch-crossing and also multiple filled bunch-crossings within the sensitive time window of the ATLAS detector. This will increase with increased luminosity in the near future. Including these effects in Monte Carlo simulation poses significant computing challenges. We present a description of the standard approach used by the ATLAS experiment and details of how we manage the conflicting demands of keeping the background dataset size as small as possible while minimizing the effect of background event re-use. We also present details of the methods used to minimize the memory footprint of these digitization jobs, to keep them within the grid limit, despite combining the information from thousands of simulated events at once. We also describe an alternative approach, known as Overlay. Here, the actual detector conditions are sampled from raw data using a special zero-bias trigger, and the simulated physi...

  20. ATLAS Grid Workflow Performance Optimization

    CERN Document Server

    Elmsheuser, Johannes; The ATLAS collaboration

    2018-01-01

    The CERN ATLAS experiment grid workflow system manages routinely 250 to 500 thousand concurrently running production and analysis jobs to process simulation and detector data. In total more than 300 PB of data is distributed over more than 150 sites in the WLCG. At this scale small improvements in the software and computing performance and workflows can lead to significant resource usage gains. ATLAS is reviewing together with CERN IT experts several typical simulation and data processing workloads for potential performance improvements in terms of memory and CPU usage, disk and network I/O. All ATLAS production and analysis grid jobs are instrumented to collect many performance metrics for detailed statistical studies using modern data analytics tools like ElasticSearch and Kibana. This presentation will review and explain the performance gains of several ATLAS simulation and data processing workflows and present analytics studies of the ATLAS grid workflows.

  1. The ATLAS Simulation Infrastructure

    CERN Document Server

    Aad, G.; Abdallah, J.; Abdelalim, A.A.; Abdesselam, A.; Abdinov, O.; Abi, B.; Abolins, M.; Abramowicz, H.; Abreu, H.; Acharya, B.S.; Adams, D.L.; Addy, T.N.; Adelman, J.; Adorisio, C.; Adragna, P.; Adye, T.; Aefsky, S.; Aguilar-Saavedra, J.A.; Aharrouche, M.; Ahlen, S.P.; Ahles, F.; Ahmad, A.; Ahmed, H.; Ahsan, M.; Aielli, G.; Akdogan, T.; Akesson, T.P.A.; Akimoto, G.; Akimov, A.V.; Aktas, A.; Alam, M.S.; Alam, M.A.; Albrand, S.; Aleksa, M.; Aleksandrov, I.N.; Alexa, C.; Alexander, G.; Alexandre, G.; Alexopoulos, T.; Alhroob, M.; Aliev, M.; Alimonti, G.; Alison, J.; Aliyev, M.; Allport, P.P.; Allwood-Spiers, S.E.; Almond, J.; Aloisio, A.; Alon, R.; Alonso, A.; Alviggi, M.G.; Amako, K.; Amelung, C.; Amorim, A.; Amoros, G.; Amram, N.; Anastopoulos, C.; Andeen, T.; Anders, C.F.; Anderson, K.J.; Andreazza, A.; Andrei, V.; Anduaga, X.S.; Angerami, A.; Anghinolfi, F.; Anjos, N.; Annovi, A.; Antonaki, A.; Antonelli, M.; Antonelli, S.; Antos, J.; Antunovic, B.; Anulli, F.; Aoun, S.; Arabidze, G.; Aracena, I.; Arai, Y.; Arce, A.T.H.; Archambault, J.P.; Arfaoui, S.; Arguin, J-F.; Argyropoulos, T.; Arik, M.; Armbruster, A.J.; Arnaez, O.; Arnault, C.; Artamonov, A.; Arutinov, D.; Asai, M.; Asai, S.; Asfandiyarov, R.; Ask, S.; Asman, B.; Asner, D.; Asquith, L.; Assamagan, K.; Astbury, A.; Astvatsatourov, A.; Atoian, G.; Auerbach, B.; Augsten, K.; Aurousseau, M.; Austin, N.; Avolio, G.; Avramidou, R.; Axen, D.; Ay, C.; Azuelos, G.; Azuma, Y.; Baak, M.A.; Bach, A.M.; Bachacou, H.; Bachas, K.; Backes, M.; Badescu, E.; Bagnaia, P.; Bai, Y.; Bain, T.; Baines, J.T.; Baker, O.K.; Baker, M.D.; Baker, S; Baltasar Dos Santos Pedrosa, F.; Banas, E.; Banerjee, P.; Banerjee, S.; Banfi, D.; Bangert, A.; Bansal, V.; Baranov, S.P.; Baranov, S.; Barashkou, A.; Barber, T.; Barberio, E.L.; Barberis, D.; Barbero, M.; Bardin, D.Y.; Barillari, T.; Barisonzi, M.; Barklow, T.; Barlow, N.; Barnett, B.M.; Barnett, R.M.; Baroncelli, A.; Barr, A.J.; Barreiro, F.; Barreiro Guimaraes da Costa, J.; Barrillon, P.; Bartoldus, R.; Bartsch, D.; Bates, R.L.; Batkova, L.; Batley, J.R.; Battaglia, A.; Battistin, M.; Bauer, F.; Bawa, H.S.; Bazalova, M.; Beare, B.; Beau, T.; Beauchemin, P.H.; Beccherle, R.; Becerici, N.; Bechtle, P.; Beck, G.A.; Beck, H.P.; Beckingham, M.; Becks, K.H.; Beddall, A.J.; Beddall, A.; Bednyakov, V.A.; Bee, C.; Begel, M.; Behar Harpaz, S.; Behera, P.K.; Beimforde, M.; Belanger-Champagne, C.; Bell, P.J.; Bell, W.H.; Bella, G.; Bellagamba, L.; Bellina, F.; Bellomo, M.; Belloni, A.; Belotskiy, K.; Beltramello, O.; Ben Ami, S.; Benary, O.; Benchekroun, D.; Bendel, M.; Benedict, B.H.; Benekos, N.; Benhammou, Y.; Benincasa, G.P.; Benjamin, D.P.; Benoit, M.; Bensinger, J.R.; Benslama, K.; Bentvelsen, S.; Beretta, M.; Berge, D.; Bergeaas Kuutmann, E.; Berger, N.; Berghaus, F.; Berglund, E.; Beringer, J.; Bernat, P.; Bernhard, R.; Bernius, C.; Berry, T.; Bertin, A.; Besana, M.I.; Besson, N.; Bethke, S.; Bianchi, R.M.; Bianco, M.; Biebel, O.; Biesiada, J.; Biglietti, M.; Bilokon, H.; Bindi, M.; Binet, S.; Bingul, A.; Bini, C.; Biscarat, C.; Bitenc, U.; Black, K.M.; Blair, R.E.; Blanchard, J-B; Blanchot, G.; Blocker, C.; Blondel, A.; Blum, W.; Blumenschein, U.; Bobbink, G.J.; Bocci, A.; Boehler, M.; Boek, J.; Boelaert, N.; Boser, S.; Bogaerts, J.A.; Bogouch, A.; Bohm, C.; Bohm, J.; Boisvert, V.; Bold, T.; Boldea, V.; Bondarenko, V.G.; Bondioli, M.; Boonekamp, M.; Bordoni, S.; Borer, C.; Borisov, A.; Borissov, G.; Borjanovic, I.; Borroni, S.; Bos, K.; Boscherini, D.; Bosman, M.; Boterenbrood, H.; Bouchami, J.; Boudreau, J.; Bouhova-Thacker, E.V.; Boulahouache, C.; Bourdarios, C.; Boveia, A.; Boyd, J.; Boyko, I.R.; Bozovic-Jelisavcic, I.; Bracinik, J.; Braem, A.; Branchini, P.; Brandenburg, G.W.; Brandt, A.; Brandt, G.; Brandt, O.; Bratzler, U.; Brau, B.; Brau, J.E.; Braun, H.M.; Brelier, B.; Bremer, J.; Brenner, R.; Bressler, S.; Britton, D.; Brochu, F.M.; Brock, I.; Brock, R.; Brodet, E.; Bromberg, C.; Brooijmans, G.; Brooks, W.K.; Brown, G.; Bruckman de Renstrom, P.A.; Bruncko, D.; Bruneliere, R.; Brunet, S.; Bruni, A.; Bruni, G.; Bruschi, M.; Bucci, F.; Buchanan, J.; Buchholz, P.; Buckley, A.G.; Budagov, I.A.; Budick, B.; Buscher, V.; Bugge, L.; Bulekov, O.; Bunse, M.; Buran, T.; Burckhart, H.; Burdin, S.; Burgess, T.; Burke, S.; Busato, E.; Bussey, P.; Buszello, C.P.; Butin, F.; Butler, B.; Butler, J.M.; Buttar, C.M.; Butterworth, J.M.; Byatt, T.; Caballero, J.; Cabrera Urban, S.; Caforio, D.; Cakir, O.; Calafiura, P.; Calderini, G.; Calfayan, P.; Calkins, R.; Caloba, L.P.; Calvet, D.; Camarri, P.; Cameron, D.; Campana, S.; Campanelli, M.; Canale, V.; Canelli, F.; Canepa, A.; Cantero, J.; Capasso, L.; Capeans Garrido, M.D.M.; Caprini, I.; Caprini, M.; Capua, M.; Caputo, R.; Caramarcu, C.; Cardarelli, R.; Carli, T.; Carlino, G.; Carminati, L.; Caron, B.; Caron, S.; Carrillo Montoya, G.D.; Carron Montero, S.; Carter, A.A.; Carter, J.R.; Carvalho, J.; Casadei, D.; Casado, M.P.; Cascella, M.; Castaneda Hernandez, A.M.; Castaneda-Miranda, E.; Castillo Gimenez, V.; Castro, N.F.; Cataldi, G.; Catinaccio, A.; Catmore, J.R.; Cattai, A.; Cattani, G.; Caughron, S.; Cauz, D.; Cavalleri, P.; Cavalli, D.; Cavalli-Sforza, M.; Cavasinni, V.; Ceradini, F.; Cerqueira, A.S.; Cerri, A.; Cerrito, L.; Cerutti, F.; Cetin, S.A.; Chafaq, A.; Chakraborty, D.; Chan, K.; Chapman, J.D.; Chapman, J.W.; Chareyre, E.; Charlton, D.G.; Chavda, V.; Cheatham, S.; Chekanov, S.; Chekulaev, S.V.; Chelkov, G.A.; Chen, H.; Chen, S.; Chen, X.; Cheplakov, A.; Chepurnov, V.F.; Cherkaoui El Moursli, R.; Tcherniatine, V.; Chesneanu, D.; Cheu, E.; Cheung, S.L.; Chevalier, L.; Chevallier, F.; Chiarella, V.; Chiefari, G.; Chikovani, L.; Childers, J.T.; Chilingarov, A.; Chiodini, G.; Chizhov, V.; Choudalakis, G.; Chouridou, S.; Christidi, I.A.; Christov, A.; Chromek-Burckhart, D.; Chu, M.L.; Chudoba, J.; Ciapetti, G.; Ciftci, A.K.; Ciftci, R.; Cinca, D.; Cindro, V.; Ciobotaru, M.D.; Ciocca, C.; Ciocio, A.; Cirilli, M.; Citterio, M.; Clark, A.; Clark, P.J.; Cleland, W.; Clemens, J.C.; Clement, B.; Clement, C.; Coadou, Y.; Cobal, M.; Coccaro, A.; Cochran, J.; Coggeshall, J.; Cogneras, E.; Colijn, A.P.; Collard, C.; Collins, N.J.; Collins-Tooth, C.; Collot, J.; Colon, G.; Conde Muino, P.; Coniavitis, E.; Consonni, M.; Constantinescu, S.; Conta, C.; Conventi, F.; Cooke, M.; Cooper, B.D.; Cooper-Sarkar, A.M.; Cooper-Smith, N.J.; Copic, K.; Cornelissen, T.; Corradi, M.; Corriveau, F.; Corso-Radu, A.; Cortes-Gonzalez, A.; Cortiana, G.; Costa, G.; Costa, M.J.; Costanzo, D.; Costin, T.; Cote, D.; Coura Torres, R.; Courneyea, L.; Cowan, G.; Cowden, C.; Cox, B.E.; Cranmer, K.; Cranshaw, J.; Cristinziani, M.; Crosetti, G.; Crupi, R.; Crepe-Renaudin, S.; Cuenca Almenar, C.; Cuhadar Donszelmann, T.; Curatolo, M.; Curtis, C.J.; Cwetanski, P.; Czyczula, Z.; D'Auria, S.; D'Onofrio, M.; D'Orazio, A.; Da Via, C; Dabrowski, W.; Dai, T.; Dallapiccola, C.; Dallison, S.J.; Daly, C.H.; Dam, M.; Danielsson, H.O.; Dannheim, D.; Dao, V.; Darbo, G.; Darlea, G.L.; Davey, W.; Davidek, T.; Davidson, N.; Davidson, R.; Davies, M.; Davison, A.R.; Dawson, I.; Daya, R.K.; De, K.; de Asmundis, R.; De Castro, S.; De Castro Faria Salgado, P.E.; De Cecco, S.; de Graat, J.; De Groot, N.; de Jong, P.; De Mora, L.; De Oliveira Branco, M.; De Pedis, D.; De Salvo, A.; De Sanctis, U.; De Santo, A.; De Vivie De Regie, J.B.; De Zorzi, G.; Dean, S.; Dedovich, D.V.; Degenhardt, J.; Dehchar, M.; Del Papa, C.; Del Peso, J.; Del Prete, T.; Dell'Acqua, A.; Dell'Asta, L.; Della Pietra, M.; della Volpe, D.; Delmastro, M.; Delsart, P.A.; Deluca, C.; Demers, S.; Demichev, M.; Demirkoz, B.; Deng, J.; Deng, W.; Denisov, S.P.; Derkaoui, J.E.; Derue, F.; Dervan, P.; Desch, K.; Deviveiros, P.O.; Dewhurst, A.; DeWilde, B.; Dhaliwal, S.; Dhullipudi, R.; Di Ciaccio, A.; Di Ciaccio, L.; Di Domenico, A.; Di Girolamo, A.; Di Girolamo, B.; Di Luise, S.; Di Mattia, A.; Di Nardo, R.; Di Simone, A.; Di Sipio, R.; Diaz, M.A.; Diblen, F.; Diehl, E.B.; Dietrich, J.; Dietzsch, T.A.; Diglio, S.; Dindar Yagci, K.; Dingfelder, J.; Dionisi, C.; Dita, P.; Dita, S.; Dittus, F.; Djama, F.; Djilkibaev, R.; Djobava, T.; do Vale, M.A.B.; Do Valle Wemans, A.; Doan, T.K.O.; Dobos, D.; Dobson, E.; Dobson, M.; Doglioni, C.; Doherty, T.; Dolejsi, J.; Dolenc, I.; Dolezal, Z.; Dolgoshein, B.A.; Dohmae, T.; Donega, M.; Donini, J.; Dopke, J.; Doria, A.; Dos Anjos, A.; Dotti, A.; Dova, M.T.; Doxiadis, A.; Doyle, A.T.; Drasal, Z.; Dris, M.; Dubbert, J.; Duchovni, E.; Duckeck, G.; Dudarev, A.; Dudziak, F.; Duhrssen, M.; Duflot, L.; Dufour, M-A.; Dunford, M.; Duran Yildiz, H.; Dushkin, A.; Duxfield, R.; Dwuznik, M.; Duren, M.; Ebenstein, W.L.; Ebke, J.; Eckweiler, S.; Edmonds, K.; Edwards, C.A.; Egorov, K.; Ehrenfeld, W.; Ehrich, T.; Eifert, T.; Eigen, G.; Einsweiler, K.; Eisenhandler, E.; Ekelof, T.; El Kacimi, M.; Ellert, M.; Elles, S.; Ellinghaus, F.; Ellis, K.; Ellis, N.; Elmsheuser, J.; Elsing, M.; Emeliyanov, D.; Engelmann, R.; Engl, A.; Epp, B.; Eppig, A.; Erdmann, J.; Ereditato, A.; Eriksson, D.; Ermoline, I.; Ernst, J.; Ernst, M.; Ernwein, J.; Errede, D.; Errede, S.; Ertel, E.; Escalier, M.; Escobar, C.; Espinal Curull, X.; Esposito, B.; Etienvre, A.I.; Etzion, E.; Evans, H.; Fabbri, L.; Fabre, C.; Facius, K.; Fakhrutdinov, R.M.; Falciano, S.; Fang, Y.; Fanti, M.; Farbin, A.; Farilla, A.; Farley, J.; Farooque, T.; Farrington, S.M.; Farthouat, P.; Fassnacht, P.; Fassouliotis, D.; Fatholahzadeh, B.; Fayard, L.; Fayette, F.; Febbraro, R.; Federic, P.; Fedin, O.L.; Fedorko, W.; Feligioni, L.; Felzmann, C.U.; Feng, C.; Feng, E.J.; Fenyuk, A.B.; Ferencei, J.; Ferland, J.; Fernandes, B.; Fernando, W.; Ferrag, S.; Ferrando, J.; Ferrara, V.; Ferrari, A.; Ferrari, P.; Ferrari, R.; Ferrer, A.; Ferrer, M.L.; Ferrere, D.; Ferretti, C.; Fiascaris, M.; Fiedler, F.; Filipcic, A.; Filippas, A.; Filthaut, F.; Fincke-Keeler, M.; Fiolhais, M.C.N.; Fiorini, L.; Firan, A.; Fischer, G.; Fisher, M.J.; Flechl, M.; Fleck, I.; Fleckner, J.; Fleischmann, P.; Fleischmann, S.; Flick, T.; Flores Castillo, L.R.; Flowerdew, M.J.; Fonseca Martin, T.; Formica, A.; Forti, A.; Fortin, D.; Fournier, D.; Fowler, A.J.; Fowler, K.; Fox, H.; Francavilla, P.; Franchino, S.; Francis, D.; Franklin, M.; Franz, S.; Fraternali, M.; Fratina, S.; Freestone, J.; French, S.T.; Froeschl, R.; Froidevaux, D.; Frost, J.A.; Fukunaga, C.; Fullana Torregrosa, E.; Fuster, J.; Gabaldon, C.; Gabizon, O.; Gadfort, T.; Gadomski, S.; Gagliardi, G.; Gagnon, P.; Galea, C.; Gallas, E.J.; Gallo, V.; Gallop, B.J.; Gallus, P.; Galyaev, E.; Gan, K.K.; Gao, Y.S.; Gaponenko, A.; Garcia-Sciveres, M.; Garcia, C.; Garcia Navarro, J.E.; Gardner, R.W.; Garelli, N.; Garitaonandia, H.; Garonne, V.; Gatti, C.; Gaudio, G.; Gautard, V.; Gauzzi, P.; Gavrilenko, I.L.; Gay, C.; Gaycken, G.; Gazis, E.N.; Ge, P.; Gee, C.N.P.; Geich-Gimbel, Ch.; Gellerstedt, K.; Gemme, C.; Genest, M.H.; Gentile, S.; Georgatos, F.; George, S.; Gershon, A.; Ghazlane, H.; Ghodbane, N.; Giacobbe, B.; Giagu, S.; Giakoumopoulou, V.; Giangiobbe, V.; Gianotti, F.; Gibbard, B.; Gibson, A.; Gibson, S.M.; Gilbert, L.M.; Gilchriese, M.; Gilewsky, V.; Gingrich, D.M.; Ginzburg, J.; Giokaris, N.; Giordani, M.P.; Giordano, R.; Giorgi, F.M.; Giovannini, P.; Giraud, P.F.; Girtler, P.; Giugni, D.; Giusti, P.; Gjelsten, B.K.; Gladilin, L.K.; Glasman, C.; Glazov, A.; Glitza, K.W.; Glonti, G.L.; Godfrey, J.; Godlewski, J.; Goebel, M.; Gopfert, T.; Goeringer, C.; Gossling, C.; Gottfert, T.; Goggi, V.; Goldfarb, S.; Goldin, D.; Golling, T.; Gomes, A.; Gomez Fajardo, L.S.; Goncalo, R.; Gonella, L.; Gong, C.; Gonzalez de la Hoz, S.; Gonzalez Silva, M.L.; Gonzalez-Sevilla, S.; Goodson, J.J.; Goossens, L.; Gordon, H.A.; Gorelov, I.; Gorfine, G.; Gorini, B.; Gorini, E.; Gorisek, A.; Gornicki, E.; Gosdzik, B.; Gosselink, M.; Gostkin, M.I.; Gough Eschrich, I.; Gouighri, M.; Goujdami, D.; Goulette, M.P.; Goussiou, A.G.; Goy, C.; Grabowska-Bold, I.; Grafstrom, P.; Grahn, K-J.; Grancagnolo, S.; Grassi, V.; Gratchev, V.; Grau, N.; Gray, H.M.; Gray, J.A.; Graziani, E.; Green, B.; Greenshaw, T.; Greenwood, Z.D.; Gregor, I.M.; Grenier, P.; Griesmayer, E.; Griffiths, J.; Grigalashvili, N.; Grillo, A.A.; Grimm, K.; Grinstein, S.; Grishkevich, Y.V.; Groh, M.; Groll, M.; Gross, E.; Grosse-Knetter, J.; Groth-Jensen, J.; Grybel, K.; Guicheney, C.; Guida, A.; Guillemin, T.; Guler, H.; Gunther, J.; Guo, B.; Gupta, A.; Gusakov, Y.; Gutierrez, A.; Gutierrez, P.; Guttman, N.; Gutzwiller, O.; Guyot, C.; Gwenlan, C.; Gwilliam, C.B.; Haas, A.; Haas, S.; Haber, C.; Hadavand, H.K.; Hadley, D.R.; Haefner, P.; Hartel, R.; Hajduk, Z.; Hakobyan, H.; Haller, J.; Hamacher, K.; Hamilton, A.; Hamilton, S.; Han, L.; Hanagaki, K.; Hance, M.; Handel, C.; Hanke, P.; Hansen, J.R.; Hansen, J.B.; Hansen, J.D.; Hansen, P.H.; Hansl-Kozanecka, T.; Hansson, P.; Hara, K.; Hare, G.A.; Harenberg, T.; Harrington, R.D.; Harris, O.M.; Harrison, K; Hartert, J.; Hartjes, F.; Harvey, A.; Hasegawa, S.; Hasegawa, Y.; Hashemi, K.; Hassani, S.; Haug, S.; Hauschild, M.; Hauser, R.; Havranek, M.; Hawkes, C.M.; Hawkings, R.J.; Hayakawa, T.; Hayward, H.S.; Haywood, S.J.; Head, S.J.; Hedberg, V.; Heelan, L.; Heim, S.; Heinemann, B.; Heisterkamp, S.; Helary, L.; Heller, M.; Hellman, S.; Helsens, C.; Hemperek, T.; Henderson, R.C.W.; Henke, M.; Henrichs, A.; Henriques Correia, A.M.; Henrot-Versille, S.; Hensel, C.; Henss, T.; Hernandez Jimenez, Y.; Hershenhorn, A.D.; Herten, G.; Hertenberger, R.; Hervas, L.; Hessey, N.P.; Higon-Rodriguez, E.; Hill, J.C.; Hiller, K.H.; Hillert, S.; Hillier, S.J.; Hinchliffe, I.; Hines, E.; Hirose, M.; Hirsch, F.; Hirschbuehl, D.; Hobbs, J.; Hod, N.; Hodgkinson, M.C.; Hodgson, P.; Hoecker, A.; Hoeferkamp, M.R.; Hoffman, J.; Hoffmann, D.; Hohlfeld, M.; Holy, T.; Holzbauer, J.L.; Homma, Y.; Horazdovsky, T.; Hori, T.; Horn, C.; Horner, S.; Horvat, S.; Hostachy, J-Y.; Hou, S.; Hoummada, A.; Howe, T.; Hrivnac, J.; Hryn'ova, T.; Hsu, P.J.; Hsu, S.C.; Huang, G.S.; Hubacek, Z.; Hubaut, F.; Huegging, F.; Hughes, E.W.; Hughes, G.; Hurwitz, M.; Husemann, U.; Huseynov, N.; Huston, J.; Huth, J.; Iacobucci, G.; Iakovidis, G.; Ibragimov, I.; Iconomidou-Fayard, L.; Idarraga, J.; 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Schwartzman, A.; Schwemling, Ph.; Schwienhorst, R.; Schwierz, R.; Schwindling, J.; Scott, W.G.; Searcy, J.; Sedykh, E.; Segura, E.; Seidel, S.C.; Seiden, A.; Seifert, F.; Seixas, J.M.; Sekhniaidze, G.; Seliverstov, D.M.; Sellden, B.; Semprini-Cesari, N.; Serfon, C.; Serin, L.; Seuster, R.; Severini, H.; Sevior, M.E.; Sfyrla, A.; Shabalina, E.; Shamim, M.; Shan, L.Y.; Shank, J.T.; Shao, Q.T.; Shapiro, M.; Shatalov, P.B.; Shaw, K.; Sherman, D.; Sherwood, P.; Shibata, A.; Shimojima, M.; Shin, T.; Shmeleva, A.; Shochet, M.J.; Shupe, M.A.; Sicho, P.; Sidoti, A.; Siegert, F; Siegrist, J.; Sijacki, Dj.; Silbert, O.; Silva, J.; Silver, Y.; Silverstein, D.; Silverstein, S.B.; Simak, V.; Simic, Lj.; Simion, S.; Simmons, B.; Simonyan, M.; Sinervo, P.; Sinev, N.B.; Sipica, V.; Siragusa, G.; Sisakyan, A.N.; Sivoklokov, S.Yu.; Sjoelin, J.; Sjursen, T.B.; Skovpen, K.; Skubic, P.; Slater, M.; Slavicek, T.; Sliwa, K.; Sloper, J.; Sluka, T.; Smakhtin, V.; Smirnov, S.Yu.; Smirnov, Y.; Smirnova, L.N.; Smirnova, O.; Smith, B.C.; Smith, D.; Smith, K.M.; Smizanska, M.; Smolek, K.; Snesarev, A.A.; Snow, S.W.; Snow, J.; Snuverink, J.; Snyder, S.; Soares, M.; Sobie, R.; Sodomka, J.; Soffer, A.; Solans, C.A.; Solar, M.; Solc, J.; Solfaroli Camillocci, E.; Solodkov, A.A.; Solovyanov, O.V.; Soluk, R.; Sondericker, J.; Sopko, V.; Sopko, B.; Sosebee, M.; Soukharev, A.; Spagnolo, S.; Spano, F.; Spencer, E.; Spighi, R.; Spigo, G.; Spila, F.; Spiwoks, R.; Spousta, M.; Spreitzer, T.; Spurlock, B.; St. Denis, R.D.; Stahl, T.; Stahlman, J.; Stamen, R.; Stancu, S.N.; Stanecka, E.; Stanek, R.W.; Stanescu, C.; Stapnes, S.; Starchenko, E.A.; Stark, J.; Staroba, P.; Starovoitov, P.; Stastny, J.; Stavina, P.; Steele, G.; Steinbach, P.; Steinberg, P.; Stekl, I.; Stelzer, B.; Stelzer, H.J.; Stelzer-Chilton, O.; Stenzel, H.; Stevenson, K.; Stewart, G.A.; Stockton, M.C.; Stoerig, K.; Stoicea, G.; Stonjek, S.; Strachota, P.; Stradling, A.R.; Straessner, A.; Strandberg, J.; Strandberg, S.; Strandlie, A.; Strauss, M.; Strizenec, P.; Strohmer, R.; Strom, D.M.; Stroynowski, R.; Strube, J.; Stugu, B.; Soh, D.A.; Su, D.; Sugaya, Y.; Sugimoto, T.; Suhr, C.; Suk, M.; Sulin, V.V.; Sultansoy, S.; Sumida, T.; Sun, X.H.; Sundermann, J.E.; Suruliz, K.; Sushkov, S.; Susinno, G.; Sutton, M.R.; Suzuki, T.; Suzuki, Y.; Sykora, I.; Sykora, T.; Szymocha, T.; Sanchez, J.; Ta, D.; Tackmann, K.; Taffard, A.; Tafirout, R.; Taga, A.; Takahashi, Y.; Takai, H.; Takashima, R.; Takeda, H.; Takeshita, T.; Talby, M.; Talyshev, A.; Tamsett, M.C.; Tanaka, J.; Tanaka, R.; Tanaka, S.; Tanaka, S.; Tapprogge, S.; Tardif, D.; Tarem, S.; Tarrade, F.; Tartarelli, G.F.; Tas, P.; Tasevsky, M.; Tassi, E.; Tatarkhanov, M.; Taylor, C.; Taylor, F.E.; Taylor, G.N.; Taylor, R.P.; Taylor, W.; Teixeira-Dias, P.; Ten Kate, H.; Teng, P.K.; Tennenbaum-Katan, Y.D.; Terada, S.; Terashi, K.; Terron, J.; Terwort, M.; Testa, M.; Teuscher, R.J.; Thioye, M.; Thoma, S.; Thomas, J.P.; Thompson, E.N.; Thompson, P.D.; Thompson, P.D.; Thompson, R.J.; Thompson, A.S.; Thomson, E.; Thun, R.P.; Tic, T.; Tikhomirov, V.O.; Tikhonov, Y.A.; Tipton, P.; Tique Aires Viegas, F.J.; Tisserant, S.; Toczek, B.; Todorov, T.; Todorova-Nova, S.; Toggerson, B.; Tojo, J.; Tokar, S.; Tokushuku, K.; Tollefson, K.; Tomasek, L.; Tomasek, M.; Tomoto, M.; Tompkins, L.; Toms, K.; Tonoyan, A.; Topfel, C.; Topilin, N.D.; Torrence, E.; Torro Pastor, E.; Toth, J.; Touchard, F.; Tovey, D.R.; Trefzger, T.; Tremblet, L.; Tricoli, A.; Trigger, I.M.; Trincaz-Duvoid, S.; Trinh, T.N.; Tripiana, M.F.; Triplett, N.; Trischuk, W.; Trivedi, A.; Trocme, B.; Troncon, C.; Trzupek, A.; Tsarouchas, C.; Tseng, J.C-L.; Tsiakiris, M.; Tsiareshka, P.V.; Tsionou, D.; Tsipolitis, G.; Tsiskaridze, V.; Tskhadadze, E.G.; Tsukerman, I.I.; Tsulaia, V.; Tsung, J.W.; Tsuno, S.; Tsybychev, D.; Tuggle, J.M.; Turecek, D.; Turk Cakir, I.; Turlay, E.; Tuts, P.M.; Twomey, M.S.; Tylmad, M.; Tyndel, M.; Uchida, K.; Ueda, I.; Ugland, M.; Uhlenbrock, M.; Uhrmacher, M.; Ukegawa, F.; Unal, G.; Undrus, A.; Unel, G.; Unno, Y.; Urbaniec, D.; Urkovsky, E.; Urquijo, P.; Urrejola, P.; Usai, G.; Uslenghi, M.; Vacavant, L.; Vacek, V.; Vachon, B.; Vahsen, S.; Valente, P.; Valentinetti, S.; Valkar, S.; Valladolid Gallego, E.; Vallecorsa, S.; Valls Ferrer, J.A.; Van Berg, R.; van der Graaf, H.; van der Kraaij, E.; van der Poel, E.; van der Ster, D.; van Eldik, N.; van Gemmeren, P.; van Kesteren, Z.; van Vulpen, I.; Vandelli, W.; Vaniachine, A.; Vankov, P.; Vannucci, F.; Vari, R.; Varnes, E.W.; Varouchas, D.; Vartapetian, A.; Varvell, K.E.; Vasilyeva, L.; Vassilakopoulos, V.I.; Vazeille, F.; Vellidis, C.; Veloso, F.; Veneziano, S.; Ventura, A.; Ventura, D.; Venturi, M.; Venturi, N.; Vercesi, V.; Verducci, M.; Verkerke, W.; Vermeulen, J.C.; Vetterli, M.C.; Vichou, I.; Vickey, T.; Viehhauser, G.H.A.; Villa, M.; Villani, E.G.; Villaplana Perez, M.; Vilucchi, E.; Vincter, M.G.; Vinek, E.; Vinogradov, V.B.; Viret, S.; Virzi, J.; Vitale, A.; Vitells, O.; Vivarelli, I.; Vives Vaque, F.; Vlachos, S.; Vlasak, M.; Vlasov, N.; Vogel, A.; Vokac, P.; Volpi, M.; von der Schmitt, H.; von Loeben, J.; von Radziewski, H.; von Toerne, E.; Vorobel, V.; Vorwerk, V.; Vos, M.; Voss, R.; Voss, T.T.; Vossebeld, J.H.; Vranjes, N.; Vranjes Milosavljevic, M.; Vrba, V.; Vreeswijk, M.; Vu Anh, T.; Vudragovic, D.; Vuillermet, R.; Vukotic, I.; Wagner, P.; Walbersloh, J.; Walder, J.; Walker, R.; Walkowiak, W.; Wall, R.; Wang, C.; Wang, H.; Wang, J.; Wang, S.M.; Warburton, A.; Ward, C.P.; Warsinsky, M.; Wastie, R.; Watkins, P.M.; Watson, A.T.; Watson, M.F.; Watts, G.; Watts, S.; Waugh, A.T.; Waugh, B.M.; Weber, M.D.; Weber, M.; Weber, M.S.; Weber, P.; Weidberg, A.R.; Weingarten, J.; Weiser, C.; Wellenstein, H.; Wells, P.S.; Wen, M.; Wenaus, T.; Wendler, S.; Wengler, T.; Wenig, S.; Wermes, N.; Werner, M.; Werner, P.; Werth, M.; Werthenbach, U.; Wessels, M.; Whalen, K.; White, A.; White, M.J.; White, S.; Whitehead, S.R.; Whiteson, D.; Whittington, D.; Wicek, F.; Wicke, D.; Wickens, F.J.; Wiedenmann, W.; Wielers, M.; Wienemann, P.; Wiglesworth, C.; Wiik, L.A.M.; Wildauer, A.; Wildt, M.A.; Wilkens, H.G.; Williams, E.; Williams, H.H.; Willocq, S.; Wilson, J.A.; Wilson, M.G.; Wilson, A.; Wingerter-Seez, I.; Winklmeier, F.; Wittgen, M.; Wolter, M.W.; Wolters, H.; Wosiek, B.K.; Wotschack, J.; Woudstra, M.J.; Wraight, K.; Wright, C.; Wright, D.; Wrona, B.; Wu, S.L.; Wu, X.; Wulf, E.; Wynne, B.M.; Xaplanteris, L.; Xella, S.; Xie, S.; Xu, D.; Xu, N.; Yamada, M.; Yamamoto, A.; Yamamoto, K.; Yamamoto, S.; Yamamura, T.; Yamaoka, J.; Yamazaki, T.; Yamazaki, Y.; Yan, Z.; Yang, H.; Yang, U.K.; Yang, Z.; Yao, W-M.; Yao, Y.; Yasu, Y.; Ye, J.; Ye, S.; Yilmaz, M.; Yoosoofmiya, R.; Yorita, K.; Yoshida, R.; Young, C.; Youssef, S.P.; Yu, D.; Yu, J.; Yuan, L.; Yurkewicz, A.; Zaidan, R.; Zaitsev, A.M.; Zajacova, Z.; Zambrano, V.; Zanello, L.; Zaytsev, A.; Zeitnitz, C.; Zeller, M.; Zemla, A.; Zendler, C.; Zenin, O.; Zenis, T.; Zenonos, Z.; Zenz, S.; Zerwas, D.; Zevi della Porta, G.; Zhan, Z.; Zhang, H.; Zhang, J.; Zhang, Q.; Zhang, X.; Zhao, L.; Zhao, T.; Zhao, Z.; Zhemchugov, A.; Zhong, J.; Zhou, B.; Zhou, N.; Zhou, Y.; Zhu, C.G.; Zhu, H.; Zhu, Y.; Zhuang, X.; Zhuravlov, V.; Zimmermann, R.; Zimmermann, S.; Zimmermann, S.; Ziolkowski, M.; Zivkovic, L.; Zobernig, G.; Zoccoli, A.; zur Nedden, M.; Zutshi, V.

    2010-01-01

    The simulation software for the ATLAS Experiment at the Large Hadron Collider is being used for large-scale production of events on the LHC Computing Grid. This simulation requires many components, from the generators that simulate particle collisions, through packages simulating the response of the various detectors and triggers. All of these components come together under the ATLAS simulation infrastructure. In this paper, that infrastructure is discussed, including that supporting the detector description, interfacing the event generation, and combining the GEANT4 simulation of the response of the individual detectors. Also described are the tools allowing the software validation, performance testing, and the validation of the simulated output against known physics processes.

  2. ATLAS Cloud R&D

    CERN Document Server

    Panitkin, S; The ATLAS collaboration; Caballero Bejar, J; Benjamin, D; DiGirolamo, A; Gable, I; Hendrix, V; Hover, J; Kucharczuk, K; Medrano LLamas, R; Love, P; Ohman, H; Paterson, M; Sobie, R; Taylor, R; Walker, R; Zaytsev, A

    2014-01-01

    The computing model of the ATLAS experiment was designed around the concept of grid computing and, since the start of data taking, this model has proven very successful. However, new cloud computing technologies bring attractive features to improve the operations and elasticity of scientific distributed computing. ATLAS sees grid and cloud computing as complementary technologies that will coexist at different levels of resource abstraction, and two years ago created an R&D working group to investigate the different integration scenarios. The ATLAS Cloud Computing R&D has been able to demonstrate the feasibility of offloading work from grid to cloud sites and, as of today, is able to integrate transparently various cloud resources into the PanDA workload management system. The ATLAS Cloud Computing R&D is operating various PanDA queues on private and public resources and has provided several hundred thousand CPU days to the experiment. As a result, the ATLAS Cloud Computing R&D group has gained...

  3. Event visualization in ATLAS

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00211497; The ATLAS collaboration; Boudreau, Joseph; Konstantinidis, Nikolaos; Martyniuk, Alex; Moyse, Edward; Thomas, Juergen; Waugh, Ben; Yallup, David

    2017-01-01

    At the beginning, HEP experiments made use of photographical images both to record and store experimental data and to illustrate their findings. Then the experiments evolved and needed to find ways to visualize their data. With the availability of computer graphics, software packages to display event data and the detector geometry started to be developed. Here, an overview of the usage of event display tools in HEP is presented. Then the case of the ATLAS experiment is considered in more detail and two widely used event display packages are presented, Atlantis and VP1, focusing on the software technologies they employ, as well as their strengths, differences and their usage in the experiment: from physics analysis to detector development, and from online monitoring to outreach and communication. Towards the end, the other ATLAS visualization tools will be briefly presented as well. Future development plans and improvements in the ATLAS event display packages will also be discussed.

  4. Supporting ATLAS

    CERN Multimedia

    maximilien brice

    2003-01-01

    Eighteen feet made of stainless steel will support the barrel ATLAS detector in the cavern at Point 1. In total, the ATLAS feet system will carry approximately 6000 tons, and will give the same inclination to the detector as the LHC accelerator.

  5. Supporting ATLAS

    CERN Multimedia

    2003-01-01

    Eighteen feet made of stainless steel will support the barrel ATLAS detector in the cavern at Point 1. In total, the ATLAS feet system will carry approximately 6000 tons, and will give the same inclination to the detector as the LHC accelerator. The installation of the feet is scheduled to finish during January 2004 with an installation precision at the 1 mm level despite their height of 5.3 metres. The manufacture was carried out in Russia (Company Izhorskiye Zavody in St. Petersburg), as part of a Russian and JINR Dubna in-kind contribution to ATLAS. Involved in the installation is a team from IHEP-Protvino (Russia), the ATLAS technical co-ordination team at CERN, and the CERN survey team. In all, about 15 people are involved. After the feet are in place, the barrel toroid magnet and the barrel calorimeters will be installed. This will keep the ATLAS team busy for the entire year 2004.

  6. COMPUTING

    CERN Multimedia

    M. Kasemann

    Introduction During the past six months, Computing participated in the STEP09 exercise, had a major involvement in the October exercise and has been working with CMS sites on improving open issues relevant for data taking. At the same time operations for MC production, real data reconstruction and re-reconstructions and data transfers at large scales were performed. STEP09 was successfully conducted in June as a joint exercise with ATLAS and the other experiments. It gave good indication about the readiness of the WLCG infrastructure with the two major LHC experiments stressing the reading, writing and processing of physics data. The October Exercise, in contrast, was conducted as an all-CMS exercise, where Physics, Computing and Offline worked on a common plan to exercise all steps to efficiently access and analyze data. As one of the major results, the CMS Tier-2s demonstrated to be fully capable for performing data analysis. In recent weeks, efforts were devoted to CMS Computing readiness. All th...

  7. The effect of morphometric atlas selection on multi-atlas-based automatic brachial plexus segmentation

    International Nuclear Information System (INIS)

    Van de Velde, Joris; Wouters, Johan; Vercauteren, Tom; De Gersem, Werner; Achten, Eric; De Neve, Wilfried; Van Hoof, Tom

    2015-01-01

    The present study aimed to measure the effect of a morphometric atlas selection strategy on the accuracy of multi-atlas-based BP autosegmentation using the commercially available software package ADMIRE® and to determine the optimal number of selected atlases to use. Autosegmentation accuracy was measured by comparing all generated automatic BP segmentations with anatomically validated gold standard segmentations that were developed using cadavers. Twelve cadaver computed tomography (CT) atlases were included in the study. One atlas was selected as a patient in ADMIRE®, and multi-atlas-based BP autosegmentation was first performed with a group of morphometrically preselected atlases. In this group, the atlases were selected on the basis of similarity in the shoulder protraction position with the patient. The number of selected atlases used started at two and increased up to eight. Subsequently, a group of randomly chosen, non-selected atlases were taken. In this second group, every possible combination of 2 to 8 random atlases was used for multi-atlas-based BP autosegmentation. For both groups, the average Dice similarity coefficient (DSC), Jaccard index (JI) and Inclusion index (INI) were calculated, measuring the similarity of the generated automatic BP segmentations and the gold standard segmentation. Similarity indices of both groups were compared using an independent sample t-test, and the optimal number of selected atlases was investigated using an equivalence trial. For each number of atlases, average similarity indices of the morphometrically selected atlas group were significantly higher than the random group (p < 0,05). In this study, the highest similarity indices were achieved using multi-atlas autosegmentation with 6 selected atlases (average DSC = 0,598; average JI = 0,434; average INI = 0,733). Morphometric atlas selection on the basis of the protraction position of the patient significantly improves multi-atlas-based BP autosegmentation accuracy

  8. Computational mouse atlases and their application to automatic assessment of craniofacial dysmorphology caused by the Crouzon mutation Fgfr2

    DEFF Research Database (Denmark)

    Ólafsdóttir, Hildur; Darvann, Tron Andre; Hermann, Nuno V.

    2007-01-01

    Crouzon syndrome is characterised by premature fusion of sutures and synchondroses. Recently the first mouse model of the syndrome was generated, having the mutation Cys342Tyr in Fgfr2c, equivalent to the most common human Crouzon/Pfeiffer syndrome mutation. In this study, a set of Micro CT scann....... Furthermore, the nonrigid approach is essential when it comes to analysing local, nonlinear shape differences.......Crouzon syndrome is characterised by premature fusion of sutures and synchondroses. Recently the first mouse model of the syndrome was generated, having the mutation Cys342Tyr in Fgfr2c, equivalent to the most common human Crouzon/Pfeiffer syndrome mutation. In this study, a set of Micro CT....... Subsequently, the atlas was deformed to match each subject from the two groups of mice. The accuracy of these registrations was measured by a comparison of manually placed landmarks from two different observers and automatically assessed landmarks. Both of the automatic approaches were within the inter...

  9. The ATLAS distributed analysis system

    International Nuclear Information System (INIS)

    Legger, F

    2014-01-01

    In the LHC operations era, analysis of the multi-petabyte ATLAS data sample by globally distributed physicists is a challenging task. To attain the required scale the ATLAS Computing Model was designed around the concept of Grid computing, realized in the Worldwide LHC Computing Grid (WLCG), the largest distributed computational resource existing in the sciences. The ATLAS experiment currently stores over 140 PB of data and runs about 140,000 concurrent jobs continuously at WLCG sites. During the first run of the LHC, the ATLAS Distributed Analysis (DA) service has operated stably and scaled as planned. More than 1600 users submitted jobs in 2012, with 2 million or more analysis jobs per week, peaking at about a million jobs per day. The system dynamically distributes popular data to expedite processing and maximally utilize resources. The reliability of the DA service is high and steadily improving; Grid sites are continually validated against a set of standard tests, and a dedicated team of expert shifters provides user support and communicates user problems to the sites. Both the user support techniques and the direct feedback of users have been effective in improving the success rate and user experience when utilizing the distributed computing environment. In this contribution a description of the main components, activities and achievements of ATLAS distributed analysis is given. Several future improvements being undertaken will be described.

  10. The ATLAS distributed analysis system

    Science.gov (United States)

    Legger, F.; Atlas Collaboration

    2014-06-01

    In the LHC operations era, analysis of the multi-petabyte ATLAS data sample by globally distributed physicists is a challenging task. To attain the required scale the ATLAS Computing Model was designed around the concept of Grid computing, realized in the Worldwide LHC Computing Grid (WLCG), the largest distributed computational resource existing in the sciences. The ATLAS experiment currently stores over 140 PB of data and runs about 140,000 concurrent jobs continuously at WLCG sites. During the first run of the LHC, the ATLAS Distributed Analysis (DA) service has operated stably and scaled as planned. More than 1600 users submitted jobs in 2012, with 2 million or more analysis jobs per week, peaking at about a million jobs per day. The system dynamically distributes popular data to expedite processing and maximally utilize resources. The reliability of the DA service is high and steadily improving; Grid sites are continually validated against a set of standard tests, and a dedicated team of expert shifters provides user support and communicates user problems to the sites. Both the user support techniques and the direct feedback of users have been effective in improving the success rate and user experience when utilizing the distributed computing environment. In this contribution a description of the main components, activities and achievements of ATLAS distributed analysis is given. Several future improvements being undertaken will be described.

  11. Mongolian Atlas

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Climatic atlas dated 1985, in Mongolian, with introductory material also in Russian and English. One hundred eight pages in single page PDFs.

  12. Networks in ATLAS

    Science.gov (United States)

    McKee, Shawn; ATLAS Collaboration

    2017-10-01

    Networks have played a critical role in high-energy physics (HEP), enabling us to access and effectively utilize globally distributed resources to meet the needs of our physicists. Because of their importance in enabling our grid computing infrastructure many physicists have taken leading roles in research and education (R&E) networking, participating in, and even convening, network related meetings and research programs with the broader networking community worldwide. This has led to HEP benefiting from excellent global networking capabilities for little to no direct cost. However, as other science domains ramp-up their need for similar networking it becomes less clear that this situation will continue unchanged. What this means for ATLAS in particular needs to be understood. ATLAS has evolved its computing model since the LHC started based upon its experience with using globally distributed resources. The most significant theme of those changes has been increased reliance upon, and use of, its networks. We will report on a number of networking initiatives in ATLAS including participation in the global perfSONAR network monitoring and measuring efforts of WLCG and OSG, the collaboration with the LHCOPN/LHCONE effort, the integration of network awareness into PanDA, the use of the evolving ATLAS analytics framework to better understand our networks and the changes in our DDM system to allow remote access to data. We will also discuss new efforts underway that are exploring the inclusion and use of software defined networks (SDN) and how ATLAS might benefit from: • Orchestration and optimization of distributed data access and data movement. • Better control of workflows, end to end. • Enabling prioritization of time-critical vs normal tasks • Improvements in the efficiency of resource usage

  13. Illustrated computer tomography

    International Nuclear Information System (INIS)

    Takahashi, S.

    1983-01-01

    This book provides the following information: basic aspects of computed tomography; atlas of computed tomography of the normal adult; clinical application of computed tomography; and radiotherapy planning and computed tomography

  14. Networks in ATLAS

    CERN Document Server

    Mc Kee, Shawn Patrick; The ATLAS collaboration

    2016-01-01

    Networks have played a critical role in high-energy physics (HEP), enabling us to access and effectively utilize globally distributed resources to meet the needs of our physicists. Because of their importance in enabling our grid computing infrastructure many physicists have taken leading roles in research and education (R&E) networking, participating in, and even convening, network related meetings and research programs with the broader networking community worldwide. This has led to HEP benefiting from excellent global networking capabilities for little to no direct cost. However, as other science domains ramp-up their need for similar networking it becomes less clear that this situation will continue unchanged. What this means for ATLAS in particular needs to be understood. ATLAS has evolved its computing model since the LHC started based upon its experience with using globally distributed resources. The most significant theme of those changes has been increased reliance upon, and use of, its networks....

  15. Networks in ATLAS

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00260714; The ATLAS collaboration

    2017-01-01

    Networks have played a critical role in high-energy physics (HEP), enabling us to access and effectively utilize globally distributed resources to meet the needs of our physicists. Because of their importance in enabling our grid computing infrastructure many physicists have taken leading roles in research and education (R&E) networking, participating in, and even convening, network related meetings and research programs with the broader networking community worldwide. This has led to HEP benefiting from excellent global networking capabilities for little to no direct cost. However, as other science domains ramp-up their need for similar networking it becomes less clear that this situation will continue unchanged. What this means for ATLAS in particular needs to be understood. ATLAS has evolved its computing model since the LHC started based upon its experience with using globally distributed resources. The most significant theme of those changes has been increased reliance upon, and use of, its networks....

  16. The ATLAS Analysis Architecture

    International Nuclear Information System (INIS)

    Cranmer, K.S.

    2008-01-01

    We present an overview of the ATLAS analysis architecture including the relevant aspects of the computing model and the major architectural aspects of the Athena framework. Emphasis will be given to the interplay between the analysis use cases and the technical aspects of the architecture including the design of the event data model, transient-persistent separation, data reduction strategies, analysis tools, and ROOT interoperability

  17. Automatic Testing and Assessment of Neuroanatomy Using a Digital Brain Atlas: Method and Development of Computer- and Mobile-Based Applications

    Science.gov (United States)

    Nowinski, Wieslaw L.; Thirunavuukarasuu, Arumugam; Ananthasubramaniam, Anand; Chua, Beng Choon; Qian, Guoyu; Nowinska, Natalia G.; Marchenko, Yevgen; Volkau, Ihar

    2009-01-01

    Preparation of tests and student's assessment by the instructor are time consuming. We address these two tasks in neuroanatomy education by employing a digital media application with a three-dimensional (3D), interactive, fully segmented, and labeled brain atlas. The anatomical and vascular models in the atlas are linked to "Terminologia…

  18. ATLAS Fact Sheet : To raise awareness of the ATLAS detector and collaboration on the LHC

    CERN Multimedia

    ATLAS Outreach

    2010-01-01

    Facts on the Detector, Calorimeters, Muon System, Inner Detector, Pixel Detector, Semiconductor Tracker, Transition Radiation Tracker,, Surface hall, Cavern, Detector, Magnet system, Solenoid, Toroid, Event rates, Physics processes, Supersymmetric particles, Comparing LHC with Cosmic rays, Heavy ion collisions, Trigger and Data Acquisition TDAQ, Computing, the LHC and the ATLAS collaboration. This fact sheet also contains images of ATLAS and the collaboration as well as a short list of videos on ATLAS available for viewing.

  19. Glance Information System for ATLAS Management

    International Nuclear Information System (INIS)

    Grael, F F; Maidantchik, C; Évora, L H R A; Karam, K; Moraes, L O F; Cirilli, M; Nessi, M; Pommès, K

    2011-01-01

    ATLAS Experiment is an international collaboration where more than 37 countries, 172 institutes and laboratories, 2900 physicists, engineers, and computer scientists plus 700 students participate. The management of this teamwork involves several aspects such as institute contribution, employment records, members' appointment, authors' list, preparation and publication of papers and speakers nomination. Previously, most of the information was accessible by a limited group and developers had to face problems such as different terminology, diverse data modeling, heterogeneous databases and unlike users needs. Moreover, the systems were not designed to handle new requirements. The maintenance has to be an easy task due to the long lifetime experiment and professionals turnover. The Glance system, a generic mechanism for accessing any database, acts as an intermediate layer isolating the user from the particularities of each database. It retrieves, inserts and updates the database independently of its technology and modeling. Relying on Glance, a group of systems were built to support the ATLAS management and operation aspects: ATLAS Membership, ATLAS Appointments, ATLAS Speakers, ATLAS Analysis Follow-Up, ATLAS Conference Notes, ATLAS Thesis, ATLAS Traceability and DSS Alarms Viewer. This paper presents the overview of the Glance information framework and describes the privilege mechanism developed to grant different level of access for each member and system.

  20. Glance Information System for ATLAS Management

    Science.gov (United States)

    Grael, F. F.; Maidantchik, C.; Évora, L. H. R. A.; Karam, K.; Moraes, L. O. F.; Cirilli, M.; Nessi, M.; Pommès, K.; ATLAS Collaboration

    2011-12-01

    ATLAS Experiment is an international collaboration where more than 37 countries, 172 institutes and laboratories, 2900 physicists, engineers, and computer scientists plus 700 students participate. The management of this teamwork involves several aspects such as institute contribution, employment records, members' appointment, authors' list, preparation and publication of papers and speakers nomination. Previously, most of the information was accessible by a limited group and developers had to face problems such as different terminology, diverse data modeling, heterogeneous databases and unlike users needs. Moreover, the systems were not designed to handle new requirements. The maintenance has to be an easy task due to the long lifetime experiment and professionals turnover. The Glance system, a generic mechanism for accessing any database, acts as an intermediate layer isolating the user from the particularities of each database. It retrieves, inserts and updates the database independently of its technology and modeling. Relying on Glance, a group of systems were built to support the ATLAS management and operation aspects: ATLAS Membership, ATLAS Appointments, ATLAS Speakers, ATLAS Analysis Follow-Up, ATLAS Conference Notes, ATLAS Thesis, ATLAS Traceability and DSS Alarms Viewer. This paper presents the overview of the Glance information framework and describes the privilege mechanism developed to grant different level of access for each member and system.

  1. Spanish ATLAS Tier-2: facing up to LHC Run 2

    CERN Document Server

    Gonzalez de la Hoz, Santiago; Fassi, Farida; Fernandez Casani, Alvaro; Kaci, Mohammed; Lacort Pellicer, Victor Ruben; Montiel Gonzalez, Almudena Del Rocio; Oliver Garcia, Elena; Pacheco Pages, Andres; Sánchez, Javier; Sanchez Martinez, Victoria; Salt, José; Villaplana Perez, Miguel

    2015-01-01

    The goal of this work is to describe the way of addressing the main challenges of Run-2 by the Spanish ATLAS Tier-2. The considerable increase of energy and luminosity for the upcoming Run-2 with respect to Run-1 has led to a revision of the ATLAS computing model as well as some of the main ATLAS computing tools. The adaptation on these changes will be shown, with the peculiarities that it is a distributed Tier-2 composed of three sites and its members are involved on ATLAS computing tasks with a hub of research, innovation and education.

  2. ATLAS@Home looks for CERN volunteers

    CERN Multimedia

    Rosaria Marraffino

    2014-01-01

    ATLAS@Home is a CERN volunteer computing project that runs simulated ATLAS events. As the project ramps up, the project team is looking for CERN volunteers to test the system before planning a bigger promotion for the public.   The ATLAS@home outreach website. ATLAS@Home is a large-scale research project that runs ATLAS experiment simulation software inside virtual machines hosted by volunteer computers. “People from all over the world offer up their computers’ idle time to run simulation programmes to help physicists extract information from the large amount of data collected by the detector,” explains Claire Adam Bourdarios of the ATLAS@Home project. “The ATLAS@Home project aims to extrapolate the Standard Model at a higher energy and explore what new physics may look like. Everything we’re currently running is preparation for next year's run.” ATLAS@Home became an official BOINC (Berkeley Open Infrastructure for Network ...

  3. The ATLAS Distributed Analysis System

    CERN Document Server

    Legger, F; The ATLAS collaboration; Pacheco Pages, A; Stradling, A

    2013-01-01

    In the LHC operations era, analysis of the multi-petabyte ATLAS data sample by globally distributed physicists is a challenging task. To attain the required scale the ATLAS Computing Model was designed around the concept of grid computing, realized in the Worldwide LHC Computing Grid (WLCG), the largest distributed computational resource existing in the sciences. The ATLAS experiment currently stores over 140 PB of data and runs about 140,000 concurrent jobs continuously at WLCG sites. During the first run of the LHC, the ATLAS Distributed Analysis (DA) service has operated stably and scaled as planned. More than 1600 users submitted jobs in 2012, with 2 million or more analysis jobs per week, peaking at about a million jobs per day. The system dynamically distributes popular data to expedite processing and maximally utilize resources. The reliability of the DA service is high but steadily improving; grid sites are continually validated against a set of standard tests, and a dedicated team of expert shifters ...

  4. The ATLAS Distributed Analysis System

    CERN Document Server

    Legger, F; The ATLAS collaboration

    2014-01-01

    In the LHC operations era, analysis of the multi-petabyte ATLAS data sample by globally distributed physicists is a challenging task. To attain the required scale the ATLAS Computing Model was designed around the concept of grid computing, realized in the Worldwide LHC Computing Grid (WLCG), the largest distributed computational resource existing in the sciences. The ATLAS experiment currently stores over 140 PB of data and runs about 140,000 concurrent jobs continuously at WLCG sites. During the first run of the LHC, the ATLAS Distributed Analysis (DA) service has operated stably and scaled as planned. More than 1600 users submitted jobs in 2012, with 2 million or more analysis jobs per week, peaking at about a million jobs per day. The system dynamically distributes popular data to expedite processing and maximally utilize resources. The reliability of the DA service is high but steadily improving; grid sites are continually validated against a set of standard tests, and a dedicated team of expert shifters ...

  5. ProstAtlas: A digital morphologic atlas of the prostate

    International Nuclear Information System (INIS)

    Betrouni, N.; Iancu, A.; Puech, P.; Mordon, S.; Makni, N.

    2012-01-01

    Computer-aided medical interventions and medical robotics for prostate cancer have known an increasing interest and research activity. However before the routine deployment of these procedures in clinical practice becomes a reality, in vivo and in silico validations must be undertaken. In this study, we developed a digital morphologic atlas of the prostate. We were interested by the gland, the peripheral zone and the central gland. Starting from an image base collected from 30 selected patients, a mean shape and most important deformations for each structure were deduced using principal component analysis. The usefulness of this atlas was highlighted in two applications: image simulation and physical phantom design

  6. Renewable Energy Atlas of the United States

    Energy Technology Data Exchange (ETDEWEB)

    Kuiper, J. [Environmental Science Division; Hlava, K. [Environmental Science Division; Greenwood, H. [Environmentall Science Division; Carr, A. [Environmental Science Division

    2013-12-13

    The Renewable Energy Atlas (Atlas) of the United States is a compilation of geospatial data focused on renewable energy resources, federal land ownership, and base map reference information. This report explains how to add the Atlas to your computer and install the associated software. The report also includes: A description of each of the components of the Atlas; Lists of the Geographic Information System (GIS) database content and sources; and A brief introduction to the major renewable energy technologies. The Atlas includes the following: A GIS database organized as a set of Environmental Systems Research Institute (ESRI) ArcGIS Personal GeoDatabases, and ESRI ArcReader and ArcGIS project files providing an interactive map visualization and analysis interface.

  7. The Next Generation ATLAS Production System

    CERN Document Server

    Borodin, Mikhail; The ATLAS collaboration; Golubkov, Dmitry; Klimentov, Alexei; Maeno, Tadashi; Mashinistov, Ruslan; Vaniachine, Alexandre

    2015-01-01

    The ATLAS experiment at LHC data processing and simulation grows continuously, as more data and more use cases emerge. For data processing the ATLAS experiment adopted the data transformation approach, where software applications transform the input data into outputs. In the ATLAS production system, each data transformation is represented by a task, a collection of many jobs, dynamically submitted by the ATLAS workload management system (PanDA/JEDI) and executed on the Grid, clouds and supercomputers. Patterns in ATLAS data transformation workflows composed of many tasks provided a scalable production system framework for template definitions of the many-tasks workflows. User interface and system logic of these workflows are being implemented in the Database Engine for Tasks (DEFT). Such development required using modern computing technologies and approaches. We report technical details of this development: database implementation, server logic and Web user interface technologies.

  8. ATLAS Job Transforms

    CERN Document Server

    Stewart, G A; The ATLAS collaboration; Maddocks, H J; Harenberg, T; Sandhoff, M; Sarrazin, B

    2013-01-01

    The need to run complex workflows for a high energy physics experiment such as ATLAS has always been present. However, as computing resources have become even more constrained, compared to the wealth of data generated by the LHC, the need to use resources efficiently and manage complex workflows within a single grid job have increased. In ATLAS, a new Job Transform framework has been developed that we describe in this paper. This framework manages the multiple execution steps needed to `transform' one data type into another (e.g., RAW data to ESD to AOD to final ntuple) and also provides a consistent interface for the ATLAS production system. The new framework uses a data driven workflow definition which is both easy to manage and powerful. After a transform is defined, jobs are expressed simply by specifying the input data and the desired output data. The transform infrastructure then executes only the necessary substeps to produce the final data products. The global execution cost of running the job is mini...

  9. ATLAS Job Transforms

    CERN Document Server

    Stewart, G A; The ATLAS collaboration; Maddocks, H J; Harenberg, T; Sandhoff, M; Sarrazin, B

    2013-01-01

    The need to run complex workflows for a high energy physics experiment such as ATLAS has always been present. However, as computing resources have become even more constrained, compared to the wealth of data generated by the LHC, the need to use resources efficiently and manage complex workflows within a single grid job have increased. In ATLAS, a new Job Transform framework has been developed that we describe in this paper. This framework manages the multiple execution steps needed to 'transform' one data type into another (e.g., RAW data to ESD to AOD to final ntuple) and also provides a consistent interface for the ATLAS production system. The new framework uses a data driven workflow definition which is both easy to manage and powerful. After a transform is defined, jobs are expressed simply by specifying the input data and the desired output data. The transform infrastructure then executes only the necessary substeps to produce the final data products. The global execution cost of running the job is mini...

  10. Advances in service and operations for ATLAS data management

    International Nuclear Information System (INIS)

    Stewart, Graeme A; Garonne, Vincent; Lassnig, Mario; Molfetas, Angelos; Barisits, Martin; Calvet, Ivan; Beermann, Thomas; Megino, Fernando Barreiro; Campana, Simone; Zhang, Donal; Tykhonov, Andrii; Serfon, Cedric; Oleynik, Danila; Petrosyan, Artem

    2012-01-01

    ATLAS has recorded almost 5PB of RAW data since the LHC started running at the end of 2009. Many more derived data products and complimentary simulation data have also been produced by the collaboration and, in total, 70PB is currently stored in the Worldwide LHC Computing Grid by ATLAS. All of this data is managed by the ATLAS Distributed Data Management system, called Don Quixote 2 (DQ2). DQ2 has evolved rapidly to help ATLAS Computing operations manage these large quantities of data across the many grid sites at which ATLAS runs and to help ATLAS physicists get access to this data. In this paper we describe new and improved DQ2 services: popularity; space monitoring and accounting; exclusion service; cleaning agents; deletion agents. We describe the experience of data management operation in ATLAS computing, showing how these services enable management of petabyte scale computing operations. We illustrate the coupling of data management services to other parts of the ATLAS computing infrastructure, in particular showing how feedback from the distributed analysis system in ATLAS has enabled dynamic placement of the most popular data, helping users and groups to analyse the increasing data volumes on the grid.

  11. Advances in service and operations for ATLAS data management

    Science.gov (United States)

    Stewart, Graeme A.; Garonne, Vincent; Lassnig, Mario; Molfetas, Angelos; Barisits, Martin; Zhang, Donal; Calvet, Ivan; Beermann, Thomas; Barreiro Megino, Fernando; Tykhonov, Andrii; Campana, Simone; Serfon, Cedric; Oleynik, Danila; Petrosyan, Artem; ATLAS Collaboration

    2012-06-01

    ATLAS has recorded almost 5PB of RAW data since the LHC started running at the end of 2009. Many more derived data products and complimentary simulation data have also been produced by the collaboration and, in total, 70PB is currently stored in the Worldwide LHC Computing Grid by ATLAS. All of this data is managed by the ATLAS Distributed Data Management system, called Don Quixote 2 (DQ2). DQ2 has evolved rapidly to help ATLAS Computing operations manage these large quantities of data across the many grid sites at which ATLAS runs and to help ATLAS physicists get access to this data. In this paper we describe new and improved DQ2 services: popularity; space monitoring and accounting; exclusion service; cleaning agents; deletion agents. We describe the experience of data management operation in ATLAS computing, showing how these services enable management of petabyte scale computing operations. We illustrate the coupling of data management services to other parts of the ATLAS computing infrastructure, in particular showing how feedback from the distributed analysis system in ATLAS has enabled dynamic placement of the most popular data, helping users and groups to analyse the increasing data volumes on the grid.

  12. Development, deployment and operations of ATLAS databases

    International Nuclear Information System (INIS)

    Vaniachine, A. V.; von der Schmitt, J. G.

    2008-01-01

    In preparation for ATLAS data taking, a coordinated shift from development towards operations has occurred in ATLAS database activities. In addition to development and commissioning activities in databases, ATLAS is active in the development and deployment (in collaboration with the WLCG 3D project) of the tools that allow the worldwide distribution and installation of databases and related datasets, as well as the actual operation of this system on ATLAS multi-grid infrastructure. We describe development and commissioning of major ATLAS database applications for online and offline. We present the first scalability test results and ramp-up schedule over the initial LHC years of operations towards the nominal year of ATLAS running, when the database storage volumes are expected to reach 6.1 TB for the Tag DB and 1.0 TB for the Conditions DB. ATLAS database applications require robust operational infrastructure for data replication between online and offline at Tier-0, and for the distribution of the offline data to Tier-1 and Tier-2 computing centers. We describe ATLAS experience with Oracle Streams and other technologies for coordinated replication of databases in the framework of the WLCG 3D services

  13. The ATLAS Glasgow Overview Week

    CERN Multimedia

    Richard Hawkings

    2007-01-01

    The ATLAS Overview Weeks always provide a good opportunity to see the status and progress throughout the experiment, and the July week at Glasgow University was no exception. The setting, amidst the traditional buildings of one of the UK's oldest universities, provided a nice counterpoint to all the cutting-edge research and technology being discussed. And despite predictions to the contrary, the weather at these northern latitudes was actually a great improvement on the previous few weeks in Geneva. The meeting sessions comprehensively covered the whole ATLAS project, from the subdetector and TDAQ systems and their commissioning, through to offline computing, analysis and physics. As a long-time ATLAS member who remembers plenary meetings in 1991 with 30 people drawing detector layouts on a whiteboard, the hardware and installation sessions were particularly impressive - to see how these dreams have been translated into 7000 tons of reality (and with attendant cabling, supports and services, which certainly...

  14. ATLAS DQ2 Deletion Service

    International Nuclear Information System (INIS)

    Oleynik, Danila; Petrosyan, Artem; Garonne, Vincent; Campana, Simone

    2012-01-01

    The ATLAS Distributed Data Management project DQ2 is responsible for the replication, access and bookkeeping of ATLAS data across more than 100 distributed grid sites. It also enforces data management policies decided on by the collaboration and defined in the ATLAS computing model. The DQ2 Deletion Service is one of the most important DDM services. This distributed service interacts with 3rd party grid middleware and the DQ2 catalogues to serve data deletion requests on the grid. Furthermore, it also takes care of retry strategies, check-pointing transactions, load management and fault tolerance. In this paper special attention is paid to the technical details which are used to achieve the high performance of service, accomplished without overloading either site storage, catalogues or other DQ2 components. Special attention is also paid to the deletion monitoring service that allows operators a detailed view of the working system.

  15. Encoding atlases by randomized classification forests for efficient multi-atlas label propagation.

    Science.gov (United States)

    Zikic, D; Glocker, B; Criminisi, A

    2014-12-01

    We propose a method for multi-atlas label propagation (MALP) based on encoding the individual atlases by randomized classification forests. Most current approaches perform a non-linear registration between all atlases and the target image, followed by a sophisticated fusion scheme. While these approaches can achieve high accuracy, in general they do so at high computational cost. This might negatively affect the scalability to large databases and experimentation. To tackle this issue, we propose to use a small and deep classification forest to encode each atlas individually in reference to an aligned probabilistic atlas, resulting in an Atlas Forest (AF). Our classifier-based encoding differs from current MALP approaches, which represent each point in the atlas either directly as a single image/label value pair, or by a set of corresponding patches. At test time, each AF produces one probabilistic label estimate, and their fusion is done by averaging. Our scheme performs only one registration per target image, achieves good results with a simple fusion scheme, and allows for efficient experimentation. In contrast to standard forest schemes, in which each tree would be trained on all atlases, our approach retains the advantages of the standard MALP framework. The target-specific selection of atlases remains possible, and incorporation of new scans is straightforward without retraining. The evaluation on four different databases shows accuracy within the range of the state of the art at a significantly lower running time. Copyright © 2014 Elsevier B.V. All rights reserved.

  16. Atlas of liver imaging

    International Nuclear Information System (INIS)

    1989-05-01

    This atlas is an outcome of an IAEA co-ordinated research programme. In addition to Japan, nine other Asian countries participated in the project and 293 liver scintigrams (116 from Japanese institutions and 177 from seven Asian countries) were evaluated by physicians from the participating Asian countries. The computer analysis of the scan findings of the individual physicians was carried out and individual scores have been separately tabulated for: (a) scan abnormality; (b) space occupying lesions; (c) cirrhosis and (d) diffuse liver diseases like hepatitis. Refs, figs and tabs

  17. ATLAS Outreach Highlights

    CERN Document Server

    Cheatham, Susan; The ATLAS collaboration

    2016-01-01

    The ATLAS outreach team is very active, promoting particle physics to a broad range of audiences including physicists, general public, policy makers, students and teachers, and media. A selection of current outreach activities and new projects will be presented. Recent highlights include the new ATLAS public website and ATLAS Open Data, the very recent public release of 1 fb-1 of ATLAS data.

  18. ATLAS Thesis Award 2017

    CERN Multimedia

    Anthony, Katarina

    2018-01-01

    Winners of the ATLAS Thesis Award were presented with certificates and glass cubes during a ceremony on 22 February, 2018. They are pictured here with Karl Jakobs (ATLAS Spokesperson), Max Klein (ATLAS Collaboration Board Chair) and Katsuo Tokushuku (ATLAS Collaboration Board Deputy Chair).

  19. Using the Hadoop/MapReduce approach for monitoring the CERN storage system and improving the ATLAS computing model

    CERN Document Server

    Russo, Stefano Alberto; Lamanna, M

    The processing of huge amounts of data, an already fundamental task for the research in the elementary particle physics field, is becoming more and more important also for companies operating in the Information Technology (IT) industry. In this context, if conventional approaches are adopted several problems arise, starting from the congestion of the communication channels. In the IT sector, one of the approaches designed to minimize this congestion on is to exploit the data locality, or in other words, to bring the computation as closer as possible to where the data resides. The most common implementation of this concept is the Hadoop/MapReduce framework. In this thesis work I evaluate the usage of Hadoop/MapReduce in two areas: a standard one similar to typical IT analyses, and an innovative one related to high energy physics analyses. The first consists in monitoring the history of the storage cluster which stores the data generated by the LHC experiments, the second in the physics analysis of the latter, ...

  20. The ATLAS Production System Evolution

    CERN Document Server

    Borodin, Mikhail; The ATLAS collaboration

    2017-01-01

    The second generation of the ATLAS Production System called ProdSys2 is a distributed workload manager that runs daily hundreds of thousands of jobs, from dozens of different ATLAS-specific workflows, across more than a hundred heterogeneous sites. It achieves high utilization by combining dynamic job definition based upon many criteria, such as input and output size, memory requirements and CPU consumption, with manageable scheduling policies and by supporting different kinds of computational resources, such as GRID, clouds, supercomputers and volunteer computers. The system dynamically assigns a group of jobs (task) to a group of geographically distributed computing resources. Dynamic assignment and resource utilization is one of the major features of the system. The Production System has a sophisticated job fault recovery mechanism, which efficiently allows running multi-terabyte tasks without human intervention. We have implemented new features which allow automatic task submission and chaining of differe...

  1. Pseudospread of the atlas: false sign of Jefferson fracture in young children

    International Nuclear Information System (INIS)

    Suss, R.A.; Zimmerman, R.D.; Leeds, N.E.

    1983-01-01

    Jefferson fractures are rare prior to teen-age. Three young children examined after trauma exhibited the characteristic spread appearance of the atlas, but fractures were excluded radiographically and clinically. A retrospective study demonstrated a similar appearance, termed pseudospread, in most children aged 3 months to 4 years, including over 90% during the second year. Pseudospread results from a discrepancy between the neural growth pattern of the atlas and the somatic pattern of the axis. An atlas spread index is defined and a normal range presented. When an atlas fracture is suggested by apparent lateral spread of the lateral atlas masses, computed tomography is useful to demonstrate an intact atlas ring

  2. Multi-atlas pancreas segmentation: Atlas selection based on vessel structure.

    Science.gov (United States)

    Karasawa, Ken'ichi; Oda, Masahiro; Kitasaka, Takayuki; Misawa, Kazunari; Fujiwara, Michitaka; Chu, Chengwen; Zheng, Guoyan; Rueckert, Daniel; Mori, Kensaku

    2017-07-01

    Automated organ segmentation from medical images is an indispensable component for clinical applications such as computer-aided diagnosis (CAD) and computer-assisted surgery (CAS). We utilize a multi-atlas segmentation scheme, which has recently been used in different approaches in the literature to achieve more accurate and robust segmentation of anatomical structures in computed tomography (CT) volume data. Among abdominal organs, the pancreas has large inter-patient variability in its position, size and shape. Moreover, the CT intensity of the pancreas closely resembles adjacent tissues, rendering its segmentation a challenging task. Due to this, conventional intensity-based atlas selection for pancreas segmentation often fails to select atlases that are similar in pancreas position and shape to those of the unlabeled target volume. In this paper, we propose a new atlas selection strategy based on vessel structure around the pancreatic tissue and demonstrate its application to a multi-atlas pancreas segmentation. Our method utilizes vessel structure around the pancreas to select atlases with high pancreatic resemblance to the unlabeled volume. Also, we investigate two types of applications of the vessel structure information to the atlas selection. Our segmentations were evaluated on 150 abdominal contrast-enhanced CT volumes. The experimental results showed that our approach can segment the pancreas with an average Jaccard index of 66.3% and an average Dice overlap coefficient of 78.5%. Copyright © 2017 Elsevier B.V. All rights reserved.

  3. ATLAS Distributed Analysis Tools

    CERN Document Server

    Gonzalez de la Hoz, Santiago; Liko, Dietrich

    2008-01-01

    The ATLAS production system has been successfully used to run production of simulation data at an unprecedented scale. Up to 10000 jobs were processed in one day. The experiences obtained operating the system on several grid flavours was essential to perform a user analysis using grid resources. First tests of the distributed analysis system were then performed. In the preparation phase data was registered in the LHC File Catalog (LFC) and replicated in external sites. For the main test, few resources were used. All these tests are only a first step towards the validation of the computing model. The ATLAS management computing board decided to integrate the collaboration efforts in distributed analysis in only one project, GANGA. The goal is to test the reconstruction and analysis software in a large scale Data production using Grid flavors in several sites. GANGA allows trivial switching between running test jobs on a local batch system and running large-scale analyses on the Grid; it provides job splitting a...

  4. Production Experience with the ATLAS Event Service

    CERN Document Server

    Benjamin, Douglas; The ATLAS collaboration

    2016-01-01

    The ATLAS Event Service (ES) has been designed and implemented for efficient running of ATLAS production workflows on a variety of computing platforms, ranging from conventional Grid sites to opportunistic, often short-lived resources, such as spot market commercial clouds, supercomputers and volunteer computing. The Event Service architecture allows real time delivery of fine grained workloads to running payload applications which process dispatched events or event ranges and immediately stream the outputs to highly scalable Object Stores. Thanks to its agile and flexible architecture the ES is currently being used by grid sites for assigning low priority workloads to otherwise idle computing resources; similarly harvesting HPC resources in an efficient back-fill mode; and massively scaling out to the 50-100k concurrent core level on the Amazon spot market to efficiently utilize those transient resources for peak production needs. Platform ports in development include ATLAS@Home (BOINC) and the Goggle Comput...

  5. A computational atlas of the hippocampal formation using ex vivo, ultra-high resolution MRI: Application to adaptive segmentation of in vivo MRI

    DEFF Research Database (Denmark)

    Iglesias, Juan Eugenio; Augustinack, Jean C.; Nguyen, Khoa

    2015-01-01

    level using ultra-high resolution, ex vivo MRI. Fifteen autopsy samples were scanned at 0.13 mm isotropic resolution (on average) using customized hardware. The images were manually segmented into 13 different hippocampal substructures using a protocol specifically designed for this study; precise...... datasets with different types of MRI contrast. The results show that the atlas and companion segmentation method: 1) can segment T1 and T2 images, as well as their combination, 2) replicate findings on mild cognitive impairment based on high-resolution T2 data, and 3) can discriminate between Alzheimer......'s disease subjects and elderly controls with 88% accuracy in standard resolution (1 mm) T1 data, significantly outperforming the atlas in FreeSurfer version 5.3 (86% accuracy) and classification based on whole hippocampal volume (82% accuracy)....

  6. Trigger Menu-aware Monitoring for the ATLAS experiment

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00441925; The ATLAS collaboration

    2017-01-01

    Changes in the trigger menu, the online algorithmic event-selection of the ATLAS experiment at the LHC, are followed by adjustments to the ATLAS trigger monitoring systems. During Run 1, and so far in Run 2, ATLAS has deployed monitoring updates with the installation of new software releases at Tier-0, the first level of the ATLAS computing grid. Having to wait for a new software release to be installed at Tier-0, in order to update ATLAS offline trigger monitoring configurations, results in a lag with respect to the modification of the trigger menu. We present the design and implementation of a `trigger menu-aware' monitoring system that aims to simplify the ATLAS operational workflows by allowing monitoring configuration changes to be made at the Tier-0 site by utilising an Oracle SQL database.

  7. A Lego version of ATLAS

    CERN Multimedia

    Laëtitia Pedroso

    2010-01-01

    There's nothing very unusual about a small child making simple objects out of Lego. But wouldn't you be surprised to learn that one six-year old has just made a life-like model of the ATLAS detector?   Bastian with his Lego ATLAS detector. © Photo provided by Kai Nicklas, Bastian's father. It all began a month ago when the boy's father was watching a video about the construction of the ATLAS detector on the Internet. He hadn't noticed that his son was watching it over his shoulder. The small boy was fascinated by what he was seeing on the computer screen and his first reaction was to exclaim: "Wow! That's a terrific machine! I think the people who built it must be really clever." The detector must have really fired his imagination because, after asking his father a few questions, he decided to make a Lego model of it. Look at the photo and you will see how closely the model he produced resembles the actual ATLAS detector. Is the little boy in question, Bastia...

  8. EnviroAtlas

    Data.gov (United States)

    City and County of Durham, North Carolina — This EnviroAtlas web service supports research and online mapping activities related to EnviroAtlas (https://www.epa.gov/enviroatlas). The layers in this web...

  9. 30 January 2012 - Danish National Research Foundation Chairman of board K. Bock and University of Copenhagen Rector R. Hemmingsen visiting ATLAS underground experimental area, CERN Control Centre and ALICE underground experimental area, throughout accompanied by J. Dines Hansen and B. Svane Nielsen; signing the guest book with CERN Director for Research and Scientific Computing S. Bertolucci and Head of International Relations F. Pauss.

    CERN Document Server

    Jean-Claude Gadmer

    2012-01-01

    30 January 2012 - Danish National Research Foundation Chairman of board K. Bock and University of Copenhagen Rector R. Hemmingsen visiting ATLAS underground experimental area, CERN Control Centre and ALICE underground experimental area, throughout accompanied by J. Dines Hansen and B. Svane Nielsen; signing the guest book with CERN Director for Research and Scientific Computing S. Bertolucci and Head of International Relations F. Pauss.

  10. 28th February 2011 - Turkish Minister of Foreign Affairs A. Davutoğlu signing the guest book with CERN Director for Research and Scientific Computing S. Bertolucci and Head of International Relations F. Pauss; meeting the CERN Turkish Community at Point 1; visiting the ATLAS control room with Former Collaboration Spokesperson P. Jenni.

    CERN Document Server

    Maximilien Brice

    2011-01-01

    28th February 2011 - Turkish Minister of Foreign Affairs A. Davutoğlu signing the guest book with CERN Director for Research and Scientific Computing S. Bertolucci and Head of International Relations F. Pauss; meeting the CERN Turkish Community at Point 1; visiting the ATLAS control room with Former Collaboration Spokesperson P. Jenni.

  11. 14th March 2011 - Australian Senator the Hon. K. Carr Minister for Innovation, Industry, Science and Research in the ATLAS Visitor Centre with Collaboration Spokesperson F. Gianotti,visiting the SM18 area with G. De Rijk,the Computing centre with Department Head F. Hemmer, signing the guest book with Director-General R. Heuer with Head of International relations F. Pauss

    CERN Multimedia

    Jean-claude Gadmer

    2011-01-01

    14th March 2011 - Australian Senator the Hon. K. Carr Minister for Innovation, Industry, Science and Research in the ATLAS Visitor Centre with Collaboration Spokesperson F. Gianotti,visiting the SM18 area with G. De Rijk,the Computing centre with Department Head F. Hemmer, signing the guest book with Director-General R. Heuer with Head of International relations F. Pauss

  12. 11 July 2011 - Carleton University Ottawa, Canada Vice President (Research and International) K. Matheson in the ATLAS visitor centre with Collaboration Spokesperson F. Gianotti, accompanied by Adviser J. Ellis and signing the guest book with CERN Director for Research and Scientific Computing S. Bertolucci.

    CERN Multimedia

    Jean-Claude Gadmer

    2011-01-01

    11 July 2011 - Carleton University Ottawa, Canada Vice President (Research and International) K. Matheson in the ATLAS visitor centre with Collaboration Spokesperson F. Gianotti, accompanied by Adviser J. Ellis and signing the guest book with CERN Director for Research and Scientific Computing S. Bertolucci.

  13. 28 March 2014 - Italian Minister of Education, University and Research S. Giannini welcomed by CERN Director-General R. Heuer and Director for Research and Scientific Computing S. Bertolucci in the ATLAS experimental cavern with Former Collaboration Spokesperson F. Gianotti. Signature of the guest book with Belgian State Secretary for the Scientific Policy P. Courard.

    CERN Multimedia

    Gadmer, Jean-Claude

    2014-01-01

    28 March 2014 - Italian Minister of Education, University and Research S. Giannini welcomed by CERN Director-General R. Heuer and Director for Research and Scientific Computing S. Bertolucci in the ATLAS experimental cavern with Former Collaboration Spokesperson F. Gianotti. Signature of the guest book with Belgian State Secretary for the Scientific Policy P. Courard.

  14. Production experience with the ATLAS Event Service

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00066086; The ATLAS collaboration; Calafiura, Paolo; Childers, John Taylor; De, Kaushik; Guan, Wen; Maeno, Tadashi; Nilsson, Paul; Tsulaia, Vakhtang; van Gemmeren, Peter; Wenaus, Torre

    2017-01-01

    The ATLAS Event Service (AES) has been designed and implemented for efficient running of ATLAS production workflows on a variety of computing platforms, ranging from conventional Grid sites to opportunistic, often short-lived resources, such as spot market commercial clouds, supercomputers and volunteer computing. The Event Service architecture allows real time delivery of fine grained workloads to running payload applications which process dispatched events or event ranges and immediately stream the outputs to highly scalable Object Stores. Thanks to its agile and flexible architecture the AES is currently being used by grid sites for assigning low priority workloads to otherwise idle computing resources; similarly harvesting HPC resources in an efficient back-fill mode; and massively scaling out to the 50-100k concurrent core level on the Amazon spot market to efficiently utilize those transient resources for peak production needs. Platform ports in development include ATLAS@Home (BOINC) and the Google Comp...

  15. The ATLAS Fast Tracker

    CERN Document Server

    Volpi, Guido; The ATLAS collaboration

    2015-01-01

    The use of tracking information at the trigger level in the LHC Run II period is crucial for the trigger an data acquisition (TDAQ) system. The tracking precision is in fact important to identify specific decay products of the Higgs boson or new phenomena, a well as to distinguish the contributions coming from many contemporary collisions that occur at every bunch crossing. However, the track reconstruction is among the most demanding tasks performed by the TDAQ computing farm; in fact, full reconstruction at full Level-1 trigger accept rate (100 KHz) is not possible. In order to overcome this limitation, the ATLAS experiment is planning the installation of a specific processor: the Fast Tracker (FTK), which is aimed at achieving this goal. The FTK is a pipeline of high performance electronic, based on custom and commercial devices, which is expected to reconstruct, with high resolution, the trajectories of charged tracks with a transverse momentum above 1 GeV, using the ATLAS inner tracker information. Patte...

  16. Berliner Philarmoniker ATLAS visit

    CERN Multimedia

    ATLAS Collaboration

    2017-01-01

    The Berliner Philarmoniker in on tour through Europe. They stopped on June 27th in Geneva, for a concert at the Victoria Hall. An ATLAS visit was organised the morning after, lead by the ATLAS spokesperson Karl Jakobs (welcome and overview talk) and two ATLAS guides (AVC visit and 3D movie).

  17. ATLAS PhD Grants 2015

    CERN Multimedia

    Marcelloni De Oliveira, Claudia

    2015-01-01

    ATLAS PHd Grants - We are excited to announce the creation of a dedicated grant scheme (thanks to a donation from Fabiola Gianotti and Peter Jenni following their award from the Fundamental Physics Prize foundation) to encourage young and high-caliber doctoral students in particle physics research (including computing for physics) and permit them to obtain world class exposure, supervision and training within the ATLAS collaboration. This special PhD Grant is aimed at graduate students preparing a doctoral thesis in particle physics (incl. computing for physics) to spend one year at CERN followed by one year support also at the home Institute.

  18. Report to users of ATLAS

    International Nuclear Information System (INIS)

    Ahmad, I.; Glagola, B.

    1995-05-01

    This report contains discussing in the following areas: Status of the Atlas accelerator; highlights of recent research at Atlas; concept for an advanced exotic beam facility based on Atlas; program advisory committee; Atlas executive committee; and Atlas and ANL physics division on the world wide web

  19. Recent ATLAS Articles on WLAP

    CERN Multimedia

    J. Herr

    As reported in the September 2004 ATLAS eNews, the Web Lecture Archive Project is a system for the archiving and publishing of multimedia presentations, using the Web as medium. We list here newly available WLAP items relating to ATLAS: Atlas Physics Workshop 6-11 June 2005 June 2005 ATLAS Week Plenary Session Click here to browse WLAP for all ATLAS lectures.

  20. Distributed processing and analysis of ATLAS experimental data

    CERN Document Server

    Barberis, D; The ATLAS collaboration

    2011-01-01

    The ATLAS experiment is taking data steadily since Autumn 2009, collecting close to 1 fb-1 of data (several petabytes of raw and reconstructed data per year of data-taking). Data are calibrated, reconstructed, distributed and analysed at over 100 different sites using the World-wide LHC Computing Grid and the tools produced by the ATLAS Distributed Computing project. In addition to event data, ATLAS produces a wealth of information on detector status, luminosity, calibrations, alignments, and data processing conditions. This information is stored in relational databases, online and offline, and made transparently available to analysers of ATLAS data world-wide through an infrastructure consisting of distributed database replicas and web servers that exploit caching technologies. This paper reports on the experience of using this distributed computing infrastructure with real data and in real time, on the evolution of the computing model driven by this experience, and on the system performance during the first...

  1. Distributed processing and analysis of ATLAS experimental data

    CERN Document Server

    Barberis, D; The ATLAS collaboration

    2011-01-01

    The ATLAS experiment is taking data steadily since Autumn 2009, and collected so far over 5 fb-1 of data (several petabytes of raw and reconstructed data per year of data-taking). Data are calibrated, reconstructed, distributed and analysed at over 100 different sites using the World-wide LHC Computing Grid and the tools produced by the ATLAS Distributed Computing project. In addition to event data, ATLAS produces a wealth of information on detector status, luminosity, calibrations, alignments, and data processing conditions. This information is stored in relational databases, online and offline, and made transparently available to analysers of ATLAS data world-wide through an infrastructure consisting of distributed database replicas and web servers that exploit caching technologies. This paper reports on the experience of using this distributed computing infrastructure with real data and in real time, on the evolution of the computing model driven by this experience, and on the system performance during the...

  2. Simulation of the heat transfer around the ATLAS muon chambers

    CERN Multimedia

    2005-01-01

    This 2D simulation recently carried out on the ATLAS muon chambers by a small team of CERN engineers specialises in the numerical computation of fluid dynamics, in other words the flow of fluids and heat.

  3. ERCP atlas

    International Nuclear Information System (INIS)

    Pott, G.; Schrameyer, B.

    1989-01-01

    Endoscopic-retrograde cholangio-pancreatography is a diagnostic tool that has become a routine method also in medical centres other than those specializing in the field of gastroenterology. It is estimated that there are about 1000 hospitals in the Federal Republic of Germany applying cholangio-pancreatography as a diagnostic method. Frequently, data interpretation is difficult, because imaging of subsequently detected lesions is found to have been insufficiently differential, or incomplete. The experienced examiner, who knows the pathological processes involved and hence to be expected, will perform the ERCP examination in a specific manner, i.e. purposefully. The ERCP atlas now presents a selection of typical, frequently found conditions, and of rarely encountered lesions. The material has been chosen from a total of 15 000 retrograde cholangio-pancreatographies. The introductory text is relatively short, as it is not so much intended to enhance experienced readers' skill in endoscopic diagnostics, - there is other literature for this purpose -, but rather as a brief survey for less experienced readers. (orig./MG) With 280 figs [de

  4. Class Generation for Numerical Wind Atlases

    DEFF Research Database (Denmark)

    Cutler, N.J.; Jørgensen, B.H.; Ersbøll, Bjarne Kjær

    2006-01-01

    A new optimised clustering method is presented for generating wind classes for mesoscale modelling to produce numerical wind atlases. It is compared with the existing method of dividing the data in 12 to 16 sectors, 3 to 7 wind-speed bins and dividing again according to the stability...... of the atmosphere. Wind atlases are typically produced using many years of on-site wind observations at many locations. Numerical wind atlases are the result of mesoscale model integrations based on synoptic scale wind climates and can be produced in a number of hours of computation. 40 years of twice daily NCEP...... adapting to the local topography. The purpose of forming classes is to minimise the computational time for the mesoscale model while still representing the synoptic climate features. Only tried briefly in the past, clustering has traits that can be used to improve the existing class generation method...

  5. Energy Frontier Research With ATLAS: Final Report

    Energy Technology Data Exchange (ETDEWEB)

    Butler, John [Boston Univ., MA (United States); Black, Kevin [Boston Univ., MA (United States); Ahlen, Steve [Boston Univ., MA (United States)

    2016-06-14

    The Boston University (BU) group is playing key roles across the ATLAS experiment: in detector operations, the online trigger, the upgrade, computing, and physics analysis. Our team has been critical to the maintenance and operations of the muon system since its installation. During Run 1 we led the muon trigger group and that responsibility continues into Run 2. BU maintains and operates the ATLAS Northeast Tier 2 computing center. We are actively engaged in the analysis of ATLAS data from Run 1 and Run 2. Physics analyses we have contributed to include Standard Model measurements (W and Z cross sections, t\\bar{t} differential cross sections, WWW^* production), evidence for the Higgs decaying to \\tau^+\\tau^-, and searches for new phenomena (technicolor, Z' and W', vector-like quarks, dark matter).

  6. Grid production with the ATLAS Event Service

    CERN Document Server

    Benjamin, Douglas; The ATLAS collaboration

    2018-01-01

    ATLAS has developed and previously presented a new computing architecture, the Event Service, that allows real time delivery of fine grained workloads which process dispatched events (or event ranges) and immediately streams outputs. The principal aim was to profit from opportunistic resources such as commercial cloud, supercomputing, and volunteer computing, and otherwise unused cycles on clusters and grids. During the development and deployment phase, its utility also on the grid and conventional clusters for the exploitation of otherwise unused cycles became apparent. Here we describe our experience commissioning the Event Service on the grid in the ATLAS production system. We study the performance compared with standard simulation production. We describe the integration with the ATLAS data management system to ensure scalability and compatibility with object stores. Finally, we outline the remaining steps towards a fully commissioned system.

  7. The ATLAS Detector Control System

    International Nuclear Information System (INIS)

    Lantzsch, K; Braun, H; Hirschbuehl, D; Kersten, S; Arfaoui, S; Franz, S; Gutzwiller, O; Schlenker, S; Tsarouchas, C A; Mindur, B; Hartert, J; Zimmermann, S; Talyshev, A; Oliveira Damazio, D; Poblaguev, A; Martin, T; Thompson, P D; Caforio, D; Sbarra, C; Hoffmann, D

    2012-01-01

    The ATLAS experiment is one of the multi-purpose experiments at the Large Hadron Collider (LHC) at CERN, constructed to study elementary particle interactions in collisions of high-energy proton beams. Twelve different sub detectors as well as the common experimental infrastructure are controlled and monitored by the Detector Control System (DCS) using a highly distributed system of 140 server machines running the industrial SCADA product PVSS. Higher level control system layers allow for automatic control procedures, efficient error recognition and handling, manage the communication with external systems such as the LHC controls, and provide a synchronization mechanism with the ATLAS data acquisition system. Different databases are used to store the online parameters of the experiment, replicate a subset used for physics reconstruction, and store the configuration parameters of the systems. This contribution describes the computing architecture and software tools to handle this complex and highly interconnected control system.

  8. The ATLAS Detector Control System

    Science.gov (United States)

    Lantzsch, K.; Arfaoui, S.; Franz, S.; Gutzwiller, O.; Schlenker, S.; Tsarouchas, C. A.; Mindur, B.; Hartert, J.; Zimmermann, S.; Talyshev, A.; Oliveira Damazio, D.; Poblaguev, A.; Braun, H.; Hirschbuehl, D.; Kersten, S.; Martin, T.; Thompson, P. D.; Caforio, D.; Sbarra, C.; Hoffmann, D.; Nemecek, S.; Robichaud-Veronneau, A.; Wynne, B.; Banas, E.; Hajduk, Z.; Olszowska, J.; Stanecka, E.; Bindi, M.; Polini, A.; Deliyergiyev, M.; Mandic, I.; Ertel, E.; Marques Vinagre, F.; Ribeiro, G.; Santos, H. F.; Barillari, T.; Habring, J.; Huber, J.; Arabidze, G.; Boterenbrood, H.; Hart, R.; Iakovidis, G.; Karakostas, K.; Leontsinis, S.; Mountricha, E.; Ntekas, K.; Filimonov, V.; Khomutnikov, V.; Kovalenko, S.; Grassi, V.; Mitrevski, J.; Phillips, P.; Chekulaev, S.; D'Auria, S.; Nagai, K.; Tartarelli, G. F.; Aielli, G.; Marchese, F.; Lafarguette, P.; Brenner, R.

    2012-12-01

    The ATLAS experiment is one of the multi-purpose experiments at the Large Hadron Collider (LHC) at CERN, constructed to study elementary particle interactions in collisions of high-energy proton beams. Twelve different sub detectors as well as the common experimental infrastructure are controlled and monitored by the Detector Control System (DCS) using a highly distributed system of 140 server machines running the industrial SCADA product PVSS. Higher level control system layers allow for automatic control procedures, efficient error recognition and handling, manage the communication with external systems such as the LHC controls, and provide a synchronization mechanism with the ATLAS data acquisition system. Different databases are used to store the online parameters of the experiment, replicate a subset used for physics reconstruction, and store the configuration parameters of the systems. This contribution describes the computing architecture and software tools to handle this complex and highly interconnected control system.

  9. Analysis facility infrastructure (Tier-3) for ATLAS experiment

    International Nuclear Information System (INIS)

    Gonzalez de la Hoz, S.; March, L.; Ros, E.; Sanchez, J.; Amoros, G.; Fassi, F.; Fernandez, A.; Kaci, M.; Lamas, A.; Salt, J.

    2008-01-01

    In the ATLAS computing model the tiered hierarchy ranged from the Tier-0 (CERN) down to desktops or workstations (Tier-3). The focus on defining the roles of each tiered component has evolved with the initial emphasis on the Tier-0 and Tier-1 definition and roles. The various LHC (Large Hadron Collider) projects, including ATLAS, then evolved the tiered hierarchy to include Tier-2's (Regional centers) as part of their projects. Tier-3 centres, on the other hand, have been defined as whatever an institution could construct to support their Physics goals using institutional and otherwise leveraged resources and therefore have not been considered to be part of the official ATLAS computing resources. However, Tier-3 centres are going to exist and will have implications on how the computing model should support ATLAS physicists. Tier-3 users will want to access LHC data and simulations and will want to enable their resources to support their analysis and simulation work. This document will define how IFIC (Instituto de Fisica Corpuscular de Valencia), after discussing with the ATLAS Tier-3 task force, should interact with the ATLAS computing model, detail the conditions under which Tier-3 centres can expect some level of support and set reasonable expectations for the scope and support of ATLAS Tier-3 sites. (orig.)

  10. Spanish ATLAS Tier-2 facing up to Run-2 period of LHC

    CERN Document Server

    Gonzalez de la Hoz, Santiago; The ATLAS collaboration; Fassi, Farida; Fernandez Casani, Alvaro; Kaci, Mohammed; Lacort Pellicer, Victor Ruben; Montiel Gonzalez, Almudena Del Rocio; Oliver Garcia, Elena; Pacheco Pages, Andres; Salt, José; Villaplana Perez, Miguel; Sanchez Martinez, Victoria; Sánchez, Javier

    2015-01-01

    The goal of this work is to describe the way of addressing the main challenges of Run-2 by the Spanish ATLAS Tier-2. The considerable increase of energy and luminosity for the upcoming Run-2 w.r.t. Run-1 has led to a revision of the ATLAS computing model as well as some of the main ATLAS computing tools. The adaptation to these changes will be shown, with the peculiarities that it is a distributed Tier-2 composed of three sites and its members are involved on ATLAS computing tasks with a hub of research, innovation and education.

  11. The magnetically driven imploding liner parameter space of the ATLAS capacitor bank

    CERN Document Server

    Lindemuth, I R; Faehl, R J; Reinovsky, R E

    2001-01-01

    Summary form only given, as follows. The Atlas capacitor bank (23 MJ, 30 MA) is now operational at Los Alamos. Atlas was designed primarily to magnetically drive imploding liners for use as impactors in shock and hydrodynamic experiments. We have conducted a computational "mapping" of the high-performance imploding liner parameter space accessible to Atlas. The effect of charge voltage, transmission inductance, liner thickness, liner initial radius, and liner length has been investigated. One conclusion is that Atlas is ideally suited to be a liner driver for liner-on-plasma experiments in a magnetized target fusion (MTF) context . The parameter space of possible Atlas reconfigurations has also been investigated.

  12. Development and Implementation of a Corriedale Ovine Brain Atlas for Use in Atlas-Based Segmentation.

    Directory of Open Access Journals (Sweden)

    Kishan Andre Liyanage

    Full Text Available Segmentation is the process of partitioning an image into subdivisions and can be applied to medical images to isolate anatomical or pathological areas for further analysis. This process can be done manually or automated by the use of image processing computer packages. Atlas-based segmentation automates this process by the use of a pre-labelled template and a registration algorithm. We developed an ovine brain atlas that can be used as a model for neurological conditions such as Parkinson's disease and focal epilepsy. 17 female Corriedale ovine brains were imaged in-vivo in a 1.5T (low-resolution MRI scanner. 13 of the low-resolution images were combined using a template construction algorithm to form a low-resolution template. The template was labelled to form an atlas and tested by comparing manual with atlas-based segmentations against the remaining four low-resolution images. The comparisons were in the form of similarity metrics used in previous segmentation research. Dice Similarity Coefficients were utilised to determine the degree of overlap between eight independent, manual and atlas-based segmentations, with values ranging from 0 (no overlap to 1 (complete overlap. For 7 of these 8 segmented areas, we achieved a Dice Similarity Coefficient of 0.5-0.8. The amygdala was difficult to segment due to its variable location and similar intensity to surrounding tissues resulting in Dice Coefficients of 0.0-0.2. We developed a low resolution ovine brain atlas with eight clinically relevant areas labelled. This brain atlas performed comparably to prior human atlases described in the literature and to intra-observer error providing an atlas that can be used to guide further research using ovine brains as a model and is hosted online for public access.

  13. Probabilistic liver atlas construction.

    Science.gov (United States)

    Dura, Esther; Domingo, Juan; Ayala, Guillermo; Marti-Bonmati, Luis; Goceri, E

    2017-01-13

    Anatomical atlases are 3D volumes or shapes representing an organ or structure of the human body. They contain either the prototypical shape of the object of interest together with other shapes representing its statistical variations (statistical atlas) or a probability map of belonging to the object (probabilistic atlas). Probabilistic atlases are mostly built with simple estimations only involving the data at each spatial location. A new method for probabilistic atlas construction that uses a generalized linear model is proposed. This method aims to improve the estimation of the probability to be covered by the liver. Furthermore, all methods to build an atlas involve previous coregistration of the sample of shapes available. The influence of the geometrical transformation adopted for registration in the quality of the final atlas has not been sufficiently investigated. The ability of an atlas to adapt to a new case is one of the most important quality criteria that should be taken into account. The presented experiments show that some methods for atlas construction are severely affected by the previous coregistration step. We show the good performance of the new approach. Furthermore, results suggest that extremely flexible registration methods are not always beneficial, since they can reduce the variability of the atlas and hence its ability to give sensible values of probability when used as an aid in segmentation of new cases.

  14. Global Data Grid Efforts for ATLAS

    CERN Multimedia

    Gardner, R.

    2001-01-01

    Over the past two years computational data grids have emerged as a promising new technology for large scale, data-intensive computing required by the LHC experiments, as outlined by the recent "Hoffman" review panel that addressed the LHC computing challenge. The problem essentially is to seamlessly link physicists to petabyte-scale data and computing resources, distributed worldwide, and connected by high-bandwidth research networks. Several new collaborative initiatives in Europe, the United States, and Asia have formed to address the problem. These projects are of great interest to ATLAS physicists and software developers since their objective is to offer tools that can be integrated into the core ATLAS application framework for distributed event reconstruction, Monte Carlo simulation, and data analysis, making it possible for individuals and groups of physicists to share information, data, and computing resources in new ways and at scales not previously attempted. In addition, much of the distributed IT...

  15. SU-E-J-128: Two-Stage Atlas Selection in Multi-Atlas-Based Image Segmentation

    International Nuclear Information System (INIS)

    Zhao, T; Ruan, D

    2015-01-01

    Purpose: In the new era of big data, multi-atlas-based image segmentation is challenged by heterogeneous atlas quality and high computation burden from extensive atlas collection, demanding efficient identification of the most relevant atlases. This study aims to develop a two-stage atlas selection scheme to achieve computational economy with performance guarantee. Methods: We develop a low-cost fusion set selection scheme by introducing a preliminary selection to trim full atlas collection into an augmented subset, alleviating the need for extensive full-fledged registrations. More specifically, fusion set selection is performed in two successive steps: preliminary selection and refinement. An augmented subset is first roughly selected from the whole atlas collection with a simple registration scheme and the corresponding preliminary relevance metric; the augmented subset is further refined into the desired fusion set size, using full-fledged registration and the associated relevance metric. The main novelty of this work is the introduction of an inference model to relate the preliminary and refined relevance metrics, based on which the augmented subset size is rigorously derived to ensure the desired atlases survive the preliminary selection with high probability. Results: The performance and complexity of the proposed two-stage atlas selection method were assessed using a collection of 30 prostate MR images. It achieved comparable segmentation accuracy as the conventional one-stage method with full-fledged registration, but significantly reduced computation time to 1/3 (from 30.82 to 11.04 min per segmentation). Compared with alternative one-stage cost-saving approach, the proposed scheme yielded superior performance with mean and medium DSC of (0.83, 0.85) compared to (0.74, 0.78). Conclusion: This work has developed a model-guided two-stage atlas selection scheme to achieve significant cost reduction while guaranteeing high segmentation accuracy. The benefit

  16. Two-stage atlas subset selection in multi-atlas based image segmentation.

    Science.gov (United States)

    Zhao, Tingting; Ruan, Dan

    2015-06-01

    Fast growing access to large databases and cloud stored data presents a unique opportunity for multi-atlas based image segmentation and also presents challenges in heterogeneous atlas quality and computation burden. This work aims to develop a novel two-stage method tailored to the special needs in the face of large atlas collection with varied quality, so that high-accuracy segmentation can be achieved with low computational cost. An atlas subset selection scheme is proposed to substitute a significant portion of the computationally expensive full-fledged registration in the conventional scheme with a low-cost alternative. More specifically, the authors introduce a two-stage atlas subset selection method. In the first stage, an augmented subset is obtained based on a low-cost registration configuration and a preliminary relevance metric; in the second stage, the subset is further narrowed down to a fusion set of desired size, based on full-fledged registration and a refined relevance metric. An inference model is developed to characterize the relationship between the preliminary and refined relevance metrics, and a proper augmented subset size is derived to ensure that the desired atlases survive the preliminary selection with high probability. The performance of the proposed scheme has been assessed with cross validation based on two clinical datasets consisting of manually segmented prostate and brain magnetic resonance images, respectively. The proposed scheme demonstrates comparable end-to-end segmentation performance as the conventional single-stage selection method, but with significant computation reduction. Compared with the alternative computation reduction method, their scheme improves the mean and medium Dice similarity coefficient value from (0.74, 0.78) to (0.83, 0.85) and from (0.82, 0.84) to (0.95, 0.95) for prostate and corpus callosum segmentation, respectively, with statistical significance. The authors have developed a novel two-stage atlas

  17. Two-stage atlas subset selection in multi-atlas based image segmentation

    Energy Technology Data Exchange (ETDEWEB)

    Zhao, Tingting, E-mail: tingtingzhao@mednet.ucla.edu; Ruan, Dan, E-mail: druan@mednet.ucla.edu [The Department of Radiation Oncology, University of California, Los Angeles, California 90095 (United States)

    2015-06-15

    Purpose: Fast growing access to large databases and cloud stored data presents a unique opportunity for multi-atlas based image segmentation and also presents challenges in heterogeneous atlas quality and computation burden. This work aims to develop a novel two-stage method tailored to the special needs in the face of large atlas collection with varied quality, so that high-accuracy segmentation can be achieved with low computational cost. Methods: An atlas subset selection scheme is proposed to substitute a significant portion of the computationally expensive full-fledged registration in the conventional scheme with a low-cost alternative. More specifically, the authors introduce a two-stage atlas subset selection method. In the first stage, an augmented subset is obtained based on a low-cost registration configuration and a preliminary relevance metric; in the second stage, the subset is further narrowed down to a fusion set of desired size, based on full-fledged registration and a refined relevance metric. An inference model is developed to characterize the relationship between the preliminary and refined relevance metrics, and a proper augmented subset size is derived to ensure that the desired atlases survive the preliminary selection with high probability. Results: The performance of the proposed scheme has been assessed with cross validation based on two clinical datasets consisting of manually segmented prostate and brain magnetic resonance images, respectively. The proposed scheme demonstrates comparable end-to-end segmentation performance as the conventional single-stage selection method, but with significant computation reduction. Compared with the alternative computation reduction method, their scheme improves the mean and medium Dice similarity coefficient value from (0.74, 0.78) to (0.83, 0.85) and from (0.82, 0.84) to (0.95, 0.95) for prostate and corpus callosum segmentation, respectively, with statistical significance. Conclusions: The authors

  18. Two-stage atlas subset selection in multi-atlas based image segmentation

    International Nuclear Information System (INIS)

    Zhao, Tingting; Ruan, Dan

    2015-01-01

    Purpose: Fast growing access to large databases and cloud stored data presents a unique opportunity for multi-atlas based image segmentation and also presents challenges in heterogeneous atlas quality and computation burden. This work aims to develop a novel two-stage method tailored to the special needs in the face of large atlas collection with varied quality, so that high-accuracy segmentation can be achieved with low computational cost. Methods: An atlas subset selection scheme is proposed to substitute a significant portion of the computationally expensive full-fledged registration in the conventional scheme with a low-cost alternative. More specifically, the authors introduce a two-stage atlas subset selection method. In the first stage, an augmented subset is obtained based on a low-cost registration configuration and a preliminary relevance metric; in the second stage, the subset is further narrowed down to a fusion set of desired size, based on full-fledged registration and a refined relevance metric. An inference model is developed to characterize the relationship between the preliminary and refined relevance metrics, and a proper augmented subset size is derived to ensure that the desired atlases survive the preliminary selection with high probability. Results: The performance of the proposed scheme has been assessed with cross validation based on two clinical datasets consisting of manually segmented prostate and brain magnetic resonance images, respectively. The proposed scheme demonstrates comparable end-to-end segmentation performance as the conventional single-stage selection method, but with significant computation reduction. Compared with the alternative computation reduction method, their scheme improves the mean and medium Dice similarity coefficient value from (0.74, 0.78) to (0.83, 0.85) and from (0.82, 0.84) to (0.95, 0.95) for prostate and corpus callosum segmentation, respectively, with statistical significance. Conclusions: The authors

  19. Computerized three-dimensional normal atlas

    International Nuclear Information System (INIS)

    Mano, Isamu; Suto, Yasuzo; Suzuki, Masataka; Iio, Masahiro.

    1990-01-01

    This paper presents our ongoing project in which normal human anatomy and its quantitative data are systematically arranged in a computer. The final product, the Computerized Three-Dimensional Normal Atlas, will be able to supply tomographic images in any direction, 3-D images, and coded information on organs, e.g., anatomical names, CT numbers, and T 1 and T 2 values. (author)

  20. Big Data tools as applied to ATLAS event data

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00225336; The ATLAS collaboration; Gardner, Robert; Bryant, Lincoln

    2017-01-01

    Big Data technologies have proven to be very useful for storage, processing and visualization of derived metrics associated with ATLAS distributed computing (ADC) services. Logfiles, database records, and metadata from a diversity of systems have been aggregated and indexed to create an analytics platform for ATLAS ADC operations analysis. Dashboards, wide area data access cost metrics, user analysis patterns, and resource utilization efficiency charts are produced flexibly through queries against a powerful analytics cluster. Here we explore whether these techniques and associated analytics ecosystem can be applied to add new modes of open, quick, and pervasive access to ATLAS event data. Such modes would simplify access and broaden the reach of ATLAS public data to new communities of users. An ability to efficiently store, filter, search and deliver ATLAS data at the event and/or sub-event level in a widely supported format would enable or significantly simplify usage of machine learning environments and to...

  1. ATLAS TDAQ application gateway upgrade during LS1

    CERN Document Server

    KOROL, A; The ATLAS collaboration; BOGDANCHIKOV, A; BRASOLIN, F; CONTESCU, A C; DUBROV, S; HAFEEZ, M; LEE, C J; SCANNICCHIO, D A; TWOMEY, M; VORONKOV, A; ZAYTSEV, A

    2014-01-01

    The ATLAS Gateway service is implemented with a set of dedicated computer nodes to provide a fine-grained access control between CERN General Public Network (GPN) and ATLAS Technical Control Network (ATCN). ATCN connects the ATLAS online farm used for ATLAS Operations and data taking, including the ATLAS TDAQ (Trigger and Data Aquisition) and DCS (Detector Control System) nodes. In particular, it provides restricted access to the web services (proxy), general login sessions (via SSH and RDP protocols), NAT and mail relay from ATCN. At the Operating System level the implementation is based on virtualization technologies. Here we report on the Gateway upgrade during Long Shutdown 1 (LS1) period: it includes the transition to the last production release of the CERN Linux distribution (SLC6), the migration to the centralized configuration management system (based on Puppet) and the redesign of the internal system architecture.

  2. Big Data Analytics Tools as Applied to ATLAS Event Data

    CERN Document Server

    Vukotic, Ilija; The ATLAS collaboration

    2016-01-01

    Big Data technologies have proven to be very useful for storage, processing and visualization of derived metrics associated with ATLAS distributed computing (ADC) services. Log file data and database records, and metadata from a diversity of systems have been aggregated and indexed to create an analytics platform for ATLAS ADC operations analysis. Dashboards, wide area data access cost metrics, user analysis patterns, and resource utilization efficiency charts are produced flexibly through queries against a powerful analytics cluster. Here we explore whether these techniques and analytics ecosystem can be applied to add new modes of open, quick, and pervasive access to ATLAS event data so as to simplify access and broaden the reach of ATLAS public data to new communities of users. An ability to efficiently store, filter, search and deliver ATLAS data at the event and/or sub-event level in a widely supported format would enable or significantly simplify usage of big data, statistical and machine learning tools...

  3. The Irish Wind Atlas

    Energy Technology Data Exchange (ETDEWEB)

    Watson, R [Univ. College Dublin, Dept. of Electronic and Electrical Engineering, Dublin (Ireland); Landberg, L [Risoe National Lab., Meteorology and Wind Energy Dept., Roskilde (Denmark)

    1999-03-01

    The development work on the Irish Wind Atlas is nearing completion. The Irish Wind Atlas is an updated improved version of the Irish section of the European Wind Atlas. A map of the irish wind resource based on a WA{sup s}P analysis of the measured data and station description of 27 measuring stations is presented. The results of previously presented WA{sup s}P/KAMM runs show good agreement with these results. (au)

  4. Future ATLAS Higgs Studies

    CERN Document Server

    Smart, Ben; The ATLAS collaboration

    2017-01-01

    The High-Luminosity LHC will prove a challenging environment to work in, with for example $=200$ expected. It will however also provide great opportunities for advancing studies of the Higgs boson. The ATLAS detector will be upgraded, and Higgs prospects analyses have been performed to assess the reach of ATLAS Higgs studies in the HL-LHC era. These analyses are presented, as are Run-2 ATLAS di-Higgs analyses for comparison.

  5. Integration of Titan supercomputer at OLCF with ATLAS production system

    CERN Document Server

    Panitkin, Sergey; The ATLAS collaboration

    2016-01-01

    The PanDA (Production and Distributed Analysis) workload management system was developed to meet the scale and complexity of distributed computing for the ATLAS experiment. PanDA managed resources are distributed worldwide, on hundreds of computing sites, with thousands of physicists accessing hundreds of Petabytes of data and the rate of data processing already exceeds Exabyte per year. While PanDA currently uses more than 200,000 cores at well over 100 Grid sites, future LHC data taking runs will require more resources than Grid computing can possibly provide. Additional computing and storage resources are required. Therefore ATLAS is engaged in an ambitious program to expand the current computing model to include additional resources such as the opportunistic use of supercomputers. In this talk we will describe a project aimed at integration of ATLAS Production System with Titan supercomputer at Oak Ridge Leadership Computing Facility (OLCF). Current approach utilizes modified PanDA Pilot framework for job...

  6. Integration of Titan supercomputer at OLCF with ATLAS Production System

    CERN Document Server

    AUTHOR|(SzGeCERN)643806; The ATLAS collaboration; De, Kaushik; Klimentov, Alexei; Nilsson, Paul; Oleynik, Danila; Padolski, Siarhei; Panitkin, Sergey; Wenaus, Torre

    2017-01-01

    The PanDA (Production and Distributed Analysis) workload management system was developed to meet the scale and complexity of distributed computing for the ATLAS experiment. PanDA managed resources are distributed worldwide, on hundreds of computing sites, with thousands of physicists accessing hundreds of Petabytes of data and the rate of data processing already exceeds Exabyte per year. While PanDA currently uses more than 200,000 cores at well over 100 Grid sites, future LHC data taking runs will require more resources than Grid computing can possibly provide. Additional computing and storage resources are required. Therefore ATLAS is engaged in an ambitious program to expand the current computing model to include additional resources such as the opportunistic use of supercomputers. In this paper we will describe a project aimed at integration of ATLAS Production System with Titan supercomputer at Oak Ridge Leadership Computing Facility (OLCF). Current approach utilizes modified PanDA Pilot framework for jo...

  7. Interactive videodisk atlas of knee anatomy

    International Nuclear Information System (INIS)

    McEnery, K.W.; Woods, J.W.; Glenn, W.F.; Rauschning, W.

    1987-01-01

    An interactive, computer-assisted atlas of knee anatomy has been developed. MR and CT images from normal volunteers and cryomicrotomed anatomic images were recorded on a laser viodeodisk. Computer software allows movement through the knee and correlation of radiographic images in the coronal, axial, and sagittal planes. Computer graphics are superimposed on the videodisk images. A high-resolution color graphics, touch-screen monitor is included in the computer system. Learning modules allow for rapid identification of specific structure by touching their location on the screen. Computer-created testing modules are available that provide for self-assessment

  8. Using containers with ATLAS offline software

    CERN Document Server

    Vogel, Marcelo; The ATLAS collaboration

    2017-01-01

    This paper describes the deployment of ATLAS offline software in containers for software development. For this we are using Docker, which is a lightweight virtualization technology that encapsulates a piece of software inside a complete file system. The deployment of offline releases via containers removes the strict requirement of compatibility between the runtime environment needed for job execution and the configuration of worker nodes at computing sites. If these two are decoupled from each other, sites can upgrade their nodes whenever and however they see fit. In this work, ATLAS software is distributed in containers either via the CernVM File System (CVMFS) or by means of a full ATLAS offline release installation. In software development, separating the build and runtime environment from the development environment allows users to take advantage of many modern code development tools that may not be available in production runtime setups like SLC6. It also frees developers from depending on resources lik...

  9. Renewable energy atlas of the United States.

    Energy Technology Data Exchange (ETDEWEB)

    Kuiper, J.A.; Hlava, K.Greenwood, H.; Carr, A. (Environmental Science Division)

    2012-05-01

    The Renewable Energy Atlas (Atlas) of the United States is a compilation of geospatial data focused on renewable energy resources, federal land ownership, and base map reference information. It is designed for the U.S. Department of Agriculture Forest Service (USFS) and other federal land management agencies to evaluate existing and proposed renewable energy projects. Much of the content of the Atlas was compiled at Argonne National Laboratory (Argonne) to support recent and current energy-related Environmental Impact Statements and studies, including the following projects: (1) West-wide Energy Corridor Programmatic Environmental Impact Statement (PEIS) (BLM 2008); (2) Draft PEIS for Solar Energy Development in Six Southwestern States (DOE/BLM 2010); (3) Supplement to the Draft PEIS for Solar Energy Development in Six Southwestern States (DOE/BLM 2011); (4) Upper Great Plains Wind Energy PEIS (WAPA/USFWS 2012, in progress); and (5) Energy Transport Corridors: The Potential Role of Federal Lands in States Identified by the Energy Policy Act of 2005, Section 368(b) (in progress). This report explains how to add the Atlas to your computer and install the associated software; describes each of the components of the Atlas; lists the Geographic Information System (GIS) database content and sources; and provides a brief introduction to the major renewable energy technologies.

  10. Distributed analysis challenges in ATLAS

    Energy Technology Data Exchange (ETDEWEB)

    Duckeck, Guenter; Legger, Federica; Mitterer, Christoph Anton; Walker, Rodney [Ludwig-Maximilians-Universitaet Muenchen (Germany)

    2016-07-01

    The ATLAS computing model has undergone massive changes to meet the high luminosity challenge of the second run of the Large Hadron Collider (LHC) at CERN. The production system and distributed data management have been redesigned, a new data format and event model for analysis have been introduced, and common reduction and derivation frameworks have been developed. We report on the impact these changes have on the distributed analysis system, study the various patterns of grid usage for user analysis, focusing on the differences between the first and th e second LHC runs, and measure performances of user jobs.

  11. Report to users of Atlas

    International Nuclear Information System (INIS)

    Ahmad, I.; Glagola, B.

    1996-06-01

    This report contains the following topics: Status of the ATLAS Accelerator; Highlights of Recent Research at ATLAS; Program Advisory Committee; ATLAS User Group Executive Committee; FMA Information Available On The World Wide Web; Conference on Nuclear Structure at the Limits; and Workshop on Experiments with Gammasphere at ATLAS

  12. Data handling and processing for the ATLAS experiment

    CERN Document Server

    Barberis, D; The ATLAS collaboration

    2011-01-01

    The ATLAS experiment has taken data steadily since Autumn 2009, collecting close to 1 fm-1 of data (several petabytes of raw and reconstructed data per year of data-taking). Data are calibrated, reconstructed, distributed and analysed at over 100 different sites using the World-wide LHC Computing Grid and the tools produced by the ATLAS Distributed Computing project. This paper reports on the experience of using this distributed computing infrastructure with real data and in real time, on the evolution of the computing model driven by this experience, and on the system performance during the first two years of operation.

  13. Data handling and processing for the ATLAS experiment

    CERN Document Server

    Barberis, D; The ATLAS collaboration

    2011-01-01

    The ATLAS experiment is taking data steadily since Autumn 2009, collecting so far over 2.5 fm-1 of data (several petabytes of raw and reconstructed data per year of data-taking). Data are calibrated, reconstructed, distributed and analysed at over 100 different sites using the World-wide LHC Computing Grid and the tools produced by the ATLAS Distributed Computing project. This paper reports on the experience of setting up and operating this distributed computing infrastructure with real data and in real time, on the evolution of the computing model driven by this experience, and on the system performance during the first two years of operation.

  14. ATLAS & Google — "Data Ocean" R&D Project

    CERN Document Server

    The ATLAS collaboration

    2017-01-01

    ATLAS is facing several challenges with respect to their computing requirements for LHC Run-3 (2020-2023) and HL-LHC runs (2025-2034). The challenges are not specific for ATLAS or/and LHC, but common for HENP computing community. Most importantly, storage continues to be the driving cost factor and at the current growth rate cannot absorb the increased physics output of the experiment. Novel computing models with a more dynamic use of storage and computing resources need to be considered. This project aims to start an R&D project for evaluating and adopting novel IT technologies for HENP computing. ATLAS and Google plan to launch an R&D project to integrate Google cloud resources (Storage and Compute) to the ATLAS distributed computing environment. After a series of teleconferences, a face-to-face brainstorming meeting in Denver, CO at the Supercomputing 2017 conference resulted in this proposal for a first prototype of the "Data Ocean" project. The idea is threefold: (a) to allow ATLAS to explore the...

  15. Virtual Machine Logbook - Enabling virtualization for ATLAS

    International Nuclear Information System (INIS)

    Yao Yushu; Calafiura, Paolo; Leggett, Charles; Poffet, Julien; Cavalli, Andrea; Frederic, Bapst

    2010-01-01

    ATLAS software has been developed mostly on CERN linux cluster lxplus or on similar facilities at the experiment Tier 1 centers. The fast rise of virtualization technology has the potential to change this model, turning every laptop or desktop into an ATLAS analysis platform. In the context of the CernVM project we are developing a suite of tools and CernVM plug-in extensions to promote the use of virtualization for ATLAS analysis and software development. The Virtual Machine Logbook (VML), in particular, is an application to organize work of physicists on multiple projects, logging their progress, and speeding up ''context switches'' from one project to another. An important feature of VML is the ability to share with a single 'click' the status of a given project with other colleagues. VML builds upon the save and restore capabilities of mainstream virtualization software like VMware, and provides a technology-independent client interface to them. A lot of emphasis in the design and implementation has gone into optimizing the save and restore process to makepractical to store many VML entries on a typical laptop disk or to share a VML entry over the network. At the same time, taking advantage of CernVM's plugin capabilities, we are extending the CernVM platform to help increase the usability of ATLAS software. For example, we added the ability to start the ATLAS event display on any computer running CernVM simply by clicking a button in a web browser. We want to integrate seamlessly VML with CernVM unique file system design to distribute efficiently ATLAS software on every physicist computer. The CernVM File System (CVMFS) download files on-demand via HTTP, and cache it locally for future use. This reduces by one order of magnitude the download sizes, making practical for a developer to work with multiple software releases on a virtual machine.

  16. Multilevel Workflow System in the ATLAS Experiment

    International Nuclear Information System (INIS)

    Borodin, M; De, K; Navarro, J Garcia; Golubkov, D; Klimentov, A; Maeno, T; Vaniachine, A

    2015-01-01

    The ATLAS experiment is scaling up Big Data processing for the next LHC run using a multilevel workflow system comprised of many layers. In Big Data processing ATLAS deals with datasets, not individual files. Similarly a task (comprised of many jobs) has become a unit of the ATLAS workflow in distributed computing, with about 0.8M tasks processed per year. In order to manage the diversity of LHC physics (exceeding 35K physics samples per year), the individual data processing tasks are organized into workflows. For example, the Monte Carlo workflow is composed of many steps: generate or configure hard-processes, hadronize signal and minimum-bias (pileup) events, simulate energy deposition in the ATLAS detector, digitize electronics response, simulate triggers, reconstruct data, convert the reconstructed data into ROOT ntuples for physics analysis, etc. Outputs are merged and/or filtered as necessary to optimize the chain. The bi-level workflow manager - ProdSys2 - generates actual workflow tasks and their jobs are executed across more than a hundred distributed computing sites by PanDA - the ATLAS job-level workload management system. On the outer level, the Database Engine for Tasks (DEfT) empowers production managers with templated workflow definitions. On the next level, the Job Execution and Definition Interface (JEDI) is integrated with PanDA to provide dynamic job definition tailored to the sites capabilities. We report on scaling up the production system to accommodate a growing number of requirements from main ATLAS areas: Trigger, Physics and Data Preparation. (paper)

  17. Recent ATLAS Articles on WLAP

    CERN Multimedia

    Goldfarb, S

    2005-01-01

    As reported in the September 2004 ATLAS eNews, the Web Lecture Archive Project is a system for the archiving and publishing of multimedia presentations, using the Web as medium. We list here newly available WLAP items relating to ATLAS: Atlas Software Week Plenary 6-10 December 2004 North American ATLAS Physics Workshop (Tucson) 20-21 December 2004 (17 talks) Physics Analysis Tools Tutorial (Tucson) 19 December 2004 Full Chain Tutorial 21 September 2004 ATLAS Plenary Sessions, 17-18 February 2005 (17 talks) Coming soon: ATLAS Tutorial on Electroweak Physics, 14 Feb. 2005 Software Workshop, 21-22 February 2005 Click here to browse WLAP for all ATLAS lectures.

  18. ATLAS Brochure (English version)

    CERN Multimedia

    Lefevre, Christiane

    2011-01-01

    ATLAS is the largest detector at the LHC, the most powerful particle accelerator in the world, which will start up in 2008. ATLAS is a multi-purpose detector, designed to throw light on fundamental questions such as the origin of mass and the nature of the Universe's dark matter.

  19. ATLAS brochure (Italian version)

    CERN Multimedia

    Lefevre, C

    2010-01-01

    ATLAS is the largest detector at the LHC, the most powerful particle accelerator in the world. ATLAS is a multi-purpose detector, designed to throw light on fundamental questions such as the origin of mass and the nature of the Universe's dark matter.

  20. ATLAS brochure (French version)

    CERN Multimedia

    Lefevre, C

    2012-01-01

    ATLAS is the largest detector at the LHC, the most powerful particle accelerator in the world. ATLAS is a multi-purpose detector, designed to throw light on fundamental questions such as the origin of mass and the nature of the Universe's dark matter.

  1. ATLAS brochure (German version)

    CERN Multimedia

    Lefevre, C

    2012-01-01

    ATLAS is the largest detector at the LHC, the most powerful particle accelerator in the world. ATLAS is a multi-purpose detector, designed to throw light on fundamental questions such as the origin of mass and the nature of the Universe's dark matter.

  2. ATLAS brochure (Danish version)

    CERN Multimedia

    Lefevre, C

    2010-01-01

    ATLAS is the largest detector at the LHC, the most powerful particle accelerator in the world. ATLAS is a multi-purpose detector, designed to throw light on fundamental questions such as the origin of mass and the nature of the Universe's dark matter.

  3. ATLAS Thesis Awards 2015

    CERN Multimedia

    Biondi, Silvia

    2016-01-01

    Winners of the ATLAS Thesis Award were presented with certificates and glass cubes during a ceremony on Thursday 25 February. The winners also presented their work in front of members of the ATLAS Collaboration. Winners: Javier Montejo Berlingen, Barcelona (Spain), Ruth Pöttgen, Mainz (Germany), Nils Ruthmann, Freiburg (Germany), and Steven Schramm, Toronto (Canada).

  4. ATLAS OF EUROPEAN VALUES

    NARCIS (Netherlands)

    M Ed Uwe Krause

    2008-01-01

    Uwe Krause: Atlas of Eurpean Values De Atlas of European Values is een samenwerkingsproject met bijbehorende website van de Universiteit van Tilburg en Fontys Lerarenopleiding in Tilburg, waarbij de wetenschappelijke data van de European Values Study (EVS) voor het onderwijs toegankelijk worden

  5. ATLAS people can run!

    CERN Multimedia

    Claudia Marcelloni de Oliveira; Pauline Gagnon

    It must be all the training we are getting every day, running around trying to get everything ready for the start of the LHC next year. This year, the ATLAS runners were in fine form and came in force. Nine ATLAS teams signed up for the 37th Annual CERN Relay Race with six runners per team. Under a blasting sun on Wednesday 23rd May 2007, each team covered the distances of 1000m, 800m, 800m, 500m, 500m and 300m taking the runners around the whole Meyrin site, hills included. A small reception took place in the ATLAS secretariat a week later to award the ATLAS Cup to the best ATLAS team. For the details on this complex calculation which takes into account the age of each runner, their gender and the color of their shoes, see the July 2006 issue of ATLAS e-news. The ATLAS Running Athena Team, the only all-women team enrolled this year, won the much coveted ATLAS Cup for the second year in a row. In fact, they are so good that Peter Schmid and Patrick Fassnacht are wondering about reducing the women's bonus in...

  6. ATLAS Colouring Book

    CERN Multimedia

    Anthony, Katarina

    2016-01-01

    The ATLAS Experiment Colouring Book is a free-to-download educational book, ideal for kids aged 5-9. It aims to introduce children to the field of High-Energy Physics, as well as the work being carried out by the ATLAS Collaboration.

  7. ATLAS brochure (Catalan version)

    CERN Multimedia

    Lefevre, C

    2008-01-01

    ATLAS is the largest detector at the LHC, the most powerful particle accelerator in the world, which will start up in 2008. ATLAS is a multi-purpose detector, designed to throw light on fundamental questions such as the origin of mass and the nature of the Universe's dark matter.

  8. ATLAS Brochure (french version)

    CERN Multimedia

    Marcastel, F

    2007-01-01

    ATLAS is the largest detector at the LHC, the most powerful particle accelerator in the world, which will start up in 2008. ATLAS is a multi-purpose detector, designed to throw light on fundamental questions such as the origin of mass and the nature of the Universe's dark matter.

  9. ATLAS brochure (Polish version)

    CERN Multimedia

    Lefevre, C

    2007-01-01

    ATLAS is the largest detector at the LHC, the most powerful particle accelerator in the world, which will start up in 2008. ATLAS is a multi-purpose detector, designed to throw light on fundamental questions such as the origin of mass and the nature of the Universe's dark matter.

  10. ATLAS brochure (Norwegian version)

    CERN Multimedia

    Lefevre, C

    2009-01-01

    ATLAS is the largest detector at the LHC, the most powerful particle accelerator in the world. ATLAS is a multi-purpose detector, designed to throw light on fundamental questions such as the origin of mass and the nature of the Universe's dark matter. Français

  11. ATLAS Brochure (german version)

    CERN Multimedia

    Marcastel, F

    2007-01-01

    ATLAS is the largest detector at the LHC, the most powerful particle accelerator in the world, which will start up in 2008. ATLAS is a multi-purpose detector, designed to throw light on fundamental questions such as the origin of mass and the nature of the Universe's dark matter.

  12. ATLAS Brochure (english version)

    CERN Multimedia

    Marcastel, F

    2007-01-01

    ATLAS is the largest detector at the LHC, the most powerful particle accelerator in the world, which will start up in 2008. ATLAS is a multi-purpose detector, designed to throw light on fundamental questions such as the origin of mass and the nature of the Universe's dark matter.

  13. ATLAS brochure (Spanish version)

    CERN Multimedia

    Lefevre, C

    2008-01-01

    ATLAS is the largest detector at the LHC, the most powerful particle accelerator in the world, which will start up in 2008. ATLAS is a multi-purpose detector, designed to throw light on fundamental questions such as the origin of mass and the nature of the Universe's dark matter.

  14. ATLAS Visitors Centre

    CERN Multimedia

    claudia Marcelloni

    2009-01-01

    ATLAS Visitors Centre has opened its shiny new doors to the public. Officially launched on Monday February 23rd, 2009, the permanent exhibition at Point 1 was conceived as a tour resource for ATLAS guides, and as a way to preserve the public’s opportunity to get a close-up look at the experiment in action when the cavern is sealed.

  15. A Slice of ATLAS

    CERN Document Server

    2004-01-01

    An entire section of the ATLAS detector is being assembled at Prévessin. Since May the components have been tested using a beam from the SPS, giving the ATLAS team valuable experience of operating the detector as well as an opportunity to debug the system.

  16. ATLAS rewards industry

    CERN Document Server

    Maximilien Brice

    2006-01-01

    For contributing vital pieces to the ATLAS puzzle, three industries were recognized on Friday 5 May during a supplier awards ceremony. After a welcome and overview of the ATLAS experiment by spokesperson Peter Jenni, CERN Secretary-General Maximilian Metzger stressed the importance of industry to CERN's scientific goals. Picture 30 : representatives of the three award-wining companies after the ceremony

  17. Distributed computing and farm management with application to the search for heavy gauge bosons using the ATLAS experiment at the LHC (CERN)

    CERN Document Server

    Lopez-Perez, Juan Antonio; Salt, Jose; Ros, Eduardo

    2008-01-01

    The Standard Model of particle physics describes the strong, weak, and electromagnetic forces between the fundamental particles of ordinary matter. However, it presents several problems and some questions remain unanswered so it cannot be considered a complete theory of fundamental interactions. Many extensions have been proposed in order to address these problems. Some important recent extensions are the Extra Dimensions theories. In the context of some models with Extra Dimensions of size about $1 TeV^{-}1$, in particular in the ADD model with only fermions confined to a D-brane, heavy Kaluza-Klein excitations are expected, with the same properties as SM gauge bosons but more massive. In this work, three hadronic decay modes of some of such massive gauge bosons, Z* and W*, are investigated using the ATLAS experiment at the Large Hadron Collider (LHC), presently under construction at CERN. These hadronic modes are more difficult to detect than the leptonic ones, but they should allow a measurement of the cou...

  18. Use of Anisotropy, 3D Segmented Atlas, and Computational Analysis to Identify Gray Matter Subcortical Lesions Common to Concussive Injury from Different Sites on the Cortex.

    Directory of Open Access Journals (Sweden)

    Praveen Kulkarni

    Full Text Available Traumatic brain injury (TBI can occur anywhere along the cortical mantel. While the cortical contusions may be random and disparate in their locations, the clinical outcomes are often similar and difficult to explain. Thus a question that arises is, do concussions at different sites on the cortex affect similar subcortical brain regions? To address this question we used a fluid percussion model to concuss the right caudal or rostral cortices in rats. Five days later, diffusion tensor MRI data were acquired for indices of anisotropy (IA for use in a novel method of analysis to detect changes in gray matter microarchitecture. IA values from over 20,000 voxels were registered into a 3D segmented, annotated rat atlas covering 150 brain areas. Comparisons between left and right hemispheres revealed a small population of subcortical sites with altered IA values. Rostral and caudal concussions were of striking similarity in the impacted subcortical locations, particularly the central nucleus of the amygdala, laterodorsal thalamus, and hippocampal complex. Subsequent immunohistochemical analysis of these sites showed significant neuroinflammation. This study presents three significant findings that advance our understanding and evaluation of TBI: 1 the introduction of a new method to identify highly localized disturbances in discrete gray matter, subcortical brain nuclei without postmortem histology, 2 the use of this method to demonstrate that separate injuries to the rostral and caudal cortex produce the same subcortical, disturbances, and 3 the central nucleus of the amygdala, critical in the regulation of emotion, is vulnerable to concussion.

  19. Dear ATLAS colleagues,

    CERN Multimedia

    PH Department

    2008-01-01

    We are collecting old pairs of glasses to take out to Mali, where they can be re-used by people there. The price for a pair of glasses can often exceed 3 months salary, so they are prohibitively expensive for many people. If you have any old spectacles you can donate, please put them in the special box in the ATLAS secretariat, bldg.40-4-D01 before the Christmas closure on 19 December so we can take them with us when we leave for Africa at the end of the month. (more details in ATLAS e-news edition of 29 September 2008: http://atlas-service-enews.web.cern.ch/atlas-service-enews/news/news_mali.php) many thanks! Katharine Leney co-driver of the ATLAS car on the Charity Run to Mali

  20. Wind Atlas for Egypt

    DEFF Research Database (Denmark)

    The results of a comprehensive, 8-year wind resource assessment programme in Egypt are presented. The objective has been to provide reliable and accurate wind atlas data sets for evaluating the potential wind power output from large electricityproducing wind turbine installations. The regional wind...... climates of Egypt have been determined by two independent methods: a traditional wind atlas based on observations from more than 30 stations all over Egypt, and a numerical wind atlas based on long-term reanalysis data and a mesoscale model (KAMM). The mean absolute error comparing the two methods is about...... 10% for two large-scale KAMM domains covering all of Egypt, and typically about 5% for several smaller-scale regional domains. The numerical wind atlas covers all of Egypt, whereas the meteorological stations are concentrated in six regions. The Wind Atlas for Egypt represents a significant step...

  1. Software Validation in ATLAS

    International Nuclear Information System (INIS)

    Hodgkinson, Mark; Seuster, Rolf; Simmons, Brinick; Sherwood, Peter; Rousseau, David

    2012-01-01

    The ATLAS collaboration operates an extensive set of protocols to validate the quality of the offline software in a timely manner. This is essential in order to process the large amounts of data being collected by the ATLAS detector in 2011 without complications on the offline software side. We will discuss a number of different strategies used to validate the ATLAS offline software; running the ATLAS framework software, Athena, in a variety of configurations daily on each nightly build via the ATLAS Nightly System (ATN) and Run Time Tester (RTT) systems; the monitoring of these tests and checking the compilation of the software via distributed teams of rotating shifters; monitoring of and follow up on bug reports by the shifter teams and periodic software cleaning weeks to improve the quality of the offline software further.

  2. ATLAS' major cooling project

    CERN Multimedia

    2005-01-01

    In 2005, a considerable effort has been put into commissioning the various units of ATLAS' complex cryogenic system. This is in preparation for the imminent cooling of some of the largest components of the detector in their final underground configuration. The liquid helium and nitrogen ATLAS refrigerators in USA 15. Cryogenics plays a vital role in operating massive detectors such as ATLAS. In many ways the liquefied argon, nitrogen and helium are the life-blood of the detector. ATLAS could not function without cryogens that will be constantly pumped via proximity systems to the superconducting magnets and subdetectors. In recent weeks compressors at the surface and underground refrigerators, dewars, pumps, linkages and all manner of other components related to the cryogenic system have been tested and commissioned. Fifty metres underground The helium and nitrogen refrigerators, installed inside the service cavern, are an important part of the ATLAS cryogenic system. Two independent helium refrigerators ...

  3. Wind Atlas for Egypt

    DEFF Research Database (Denmark)

    Mortensen, Niels Gylling; Said Said, Usama; Badger, Jake

    2006-01-01

    The results of a comprehensive, 8-year wind resource assessment programme in Egypt are presented. The objective has been to provide reliable and accurate wind atlas data sets for evaluating the potential wind power output from large electricityproducing wind turbine installations. The regional wind...... climates of Egypt have been determined by two independent methods: a traditional wind atlas based on observations from more than 30 stations all over Egypt, and a numerical wind atlas based on long-term reanalysis data and a mesoscale model (KAMM). The mean absolute error comparing the two methods is about...... 10% for two large-scale KAMM domains covering all of Egypt, and typically about 5% for several smaller-scale regional domains. The numerical wind atlas covers all of Egypt, whereas the meteorological stations are concentrated in six regions. The Wind Atlas for Egypt represents a significant step...

  4. The ATLAS online High Level Trigger framework: Experience reusing offline software components in the ATLAS trigger

    International Nuclear Information System (INIS)

    Wiedenmann, Werner

    2010-01-01

    Event selection in the ATLAS High Level Trigger is accomplished to a large extent by reusing software components and event selection algorithms developed and tested in an offline environment. Many of these offline software modules are not specifically designed to run in a heavily multi-threaded online data flow environment. The ATLAS High Level Trigger (HLT) framework based on the GAUDI and ATLAS ATHENA frameworks, forms the interface layer, which allows the execution of the HLT selection and monitoring code within the online run control and data flow software. While such an approach provides a unified environment for trigger event selection across all of ATLAS, it also poses strict requirements on the reused software components in terms of performance, memory usage and stability. Experience of running the HLT selection software in the different environments and especially on large multi-node trigger farms has been gained in several commissioning periods using preloaded Monte Carlo events, in data taking periods with cosmic events and in a short period with proton beams from LHC. The contribution discusses the architectural aspects of the HLT framework, its performance and its software environment within the ATLAS computing, trigger and data flow projects. Emphasis is also put on the architectural implications for the software by the use of multi-core processors in the computing farms and the experiences gained with multi-threading and multi-process technologies.

  5. Canadian ATLAS data center to support CERN's LHC

    CERN Multimedia

    2006-01-01

    "The biggest science experiment in history is currently underway at the world-famous CERN labs in Switzerland, and Canada is poised to play a critical role in its success. Thanks to a $10.5 million investment announced by the Canada Foundation for Innovation (CFI), an ultra-sophisticated computing facility -- the ATLAS Data Center -- will be created to support the ATLAS project at CERN's Large Hadron Collider (LHC)." (1 page)

  6. COMPUTING

    CERN Multimedia

    M. Kasemann

    Overview In autumn the main focus was to process and handle CRAFT data and to perform the Summer08 MC production. The operational aspects were well covered by regular Computing Shifts, experts on duty and Computing Run Coordination. At the Computing Resource Board (CRB) in October a model to account for service work at Tier 2s was approved. The computing resources for 2009 were reviewed for presentation at the C-RRB. The quarterly resource monitoring is continuing. Facilities/Infrastructure operations Operations during CRAFT data taking ran fine. This proved to be a very valuable experience for T0 workflows and operations. The transfers of custodial data to most T1s went smoothly. A first round of reprocessing started at the Tier-1 centers end of November; it will take about two weeks. The Computing Shifts procedure was tested full scale during this period and proved to be very efficient: 30 Computing Shifts Persons (CSP) and 10 Computing Resources Coordinators (CRC). The shift program for the shut down w...

  7. Generation of Individual Whole-Brain Atlases With Resting-State fMRI Data Using Simultaneous Graph Computation and Parcellation.

    Science.gov (United States)

    Wang, J; Hao, Z; Wang, H

    2018-01-01

    The human brain can be characterized as functional networks. Therefore, it is important to subdivide the brain appropriately in order to construct reliable networks. Resting-state functional connectivity-based parcellation is a commonly used technique to fulfill this goal. Here we propose a novel individual subject-level parcellation approach based on whole-brain resting-state functional magnetic resonance imaging (fMRI) data. We first used a supervoxel method known as simple linear iterative clustering directly on resting-state fMRI time series to generate supervoxels, and then combined similar supervoxels to generate clusters using a clustering method known as graph-without-cut (GWC). The GWC approach incorporates spatial information and multiple features of the supervoxels by energy minimization, simultaneously yielding an optimal graph and brain parcellation. Meanwhile, it theoretically guarantees that the actual cluster number is exactly equal to the initialized cluster number. By comparing the results of the GWC approach and those of the random GWC approach, we demonstrated that GWC does not rely heavily on spatial structures, thus avoiding the challenges encountered in some previous whole-brain parcellation approaches. In addition, by comparing the GWC approach to two competing approaches, we showed that GWC achieved better parcellation performances in terms of different evaluation metrics. The proposed approach can be used to generate individualized brain atlases for applications related to cognition, development, aging, disease, personalized medicine, etc. The major source codes of this study have been made publicly available at https://github.com/yuzhounh/GWC.

  8. Generation of Individual Whole-Brain Atlases With Resting-State fMRI Data Using Simultaneous Graph Computation and Parcellation

    Directory of Open Access Journals (Sweden)

    J. Wang

    2018-05-01

    Full Text Available The human brain can be characterized as functional networks. Therefore, it is important to subdivide the brain appropriately in order to construct reliable networks. Resting-state functional connectivity-based parcellation is a commonly used technique to fulfill this goal. Here we propose a novel individual subject-level parcellation approach based on whole-brain resting-state functional magnetic resonance imaging (fMRI data. We first used a supervoxel method known as simple linear iterative clustering directly on resting-state fMRI time series to generate supervoxels, and then combined similar supervoxels to generate clusters using a clustering method known as graph-without-cut (GWC. The GWC approach incorporates spatial information and multiple features of the supervoxels by energy minimization, simultaneously yielding an optimal graph and brain parcellation. Meanwhile, it theoretically guarantees that the actual cluster number is exactly equal to the initialized cluster number. By comparing the results of the GWC approach and those of the random GWC approach, we demonstrated that GWC does not rely heavily on spatial structures, thus avoiding the challenges encountered in some previous whole-brain parcellation approaches. In addition, by comparing the GWC approach to two competing approaches, we showed that GWC achieved better parcellation performances in terms of different evaluation metrics. The proposed approach can be used to generate individualized brain atlases for applications related to cognition, development, aging, disease, personalized medicine, etc. The major source codes of this study have been made publicly available at https://github.com/yuzhounh/GWC.

  9. ATLAS Data Challenge 1

    CERN Document Server

    Poulard, G

    2003-01-01

    In 2002 the ATLAS experiment started a series of Data Challenges (DC) of which the goals are the validation of the Computing Model, of the complete software suite, of the data model, and to ensure the correctness of the technical choices to be made. A major feature of the first Data Challenge (DC1) was the preparation and the deployment of the software required for the production of large event samples for the High Level Trigger (HLT) and physics communities, and the production of those samples as a world-wide distributed activity. The first phase of DC1 was run during summer 2002, and involved 39 institutes in 18 countries. More than 10 million physics events and 30 million single particle events were fully simulated. Over a period of about 40 calendar days 71000 CPU-days were used producing 30 Tbytes of data in about 35000 partitions. In the second phase the next processing step was performed with the participation of 56 institutes in 21 countries (~ 4000 processors used in parallel). The basic elements of ...

  10. COMPUTING

    CERN Multimedia

    I. Fisk

    2011-01-01

    Introduction CMS distributed computing system performed well during the 2011 start-up. The events in 2011 have more pile-up and are more complex than last year; this results in longer reconstruction times and harder events to simulate. Significant increases in computing capacity were delivered in April for all computing tiers, and the utilisation and load is close to the planning predictions. All computing centre tiers performed their expected functionalities. Heavy-Ion Programme The CMS Heavy-Ion Programme had a very strong showing at the Quark Matter conference. A large number of analyses were shown. The dedicated heavy-ion reconstruction facility at the Vanderbilt Tier-2 is still involved in some commissioning activities, but is available for processing and analysis. Facilities and Infrastructure Operations Facility and Infrastructure operations have been active with operations and several important deployment tasks. Facilities participated in the testing and deployment of WMAgent and WorkQueue+Request...

  11. COMPUTING

    CERN Multimedia

    P. McBride

    The Computing Project is preparing for a busy year where the primary emphasis of the project moves towards steady operations. Following the very successful completion of Computing Software and Analysis challenge, CSA06, last fall, we have reorganized and established four groups in computing area: Commissioning, User Support, Facility/Infrastructure Operations and Data Operations. These groups work closely together with groups from the Offline Project in planning for data processing and operations. Monte Carlo production has continued since CSA06, with about 30M events produced each month to be used for HLT studies and physics validation. Monte Carlo production will continue throughout the year in the preparation of large samples for physics and detector studies ramping to 50 M events/month for CSA07. Commissioning of the full CMS computing system is a major goal for 2007. Site monitoring is an important commissioning component and work is ongoing to devise CMS specific tests to be included in Service Availa...

  12. COMPUTING

    CERN Multimedia

    M. Kasemann

    Overview During the past three months activities were focused on data operations, testing and re-enforcing shift and operational procedures for data production and transfer, MC production and on user support. Planning of the computing resources in view of the new LHC calendar in ongoing. Two new task forces were created for supporting the integration work: Site Commissioning, which develops tools helping distributed sites to monitor job and data workflows, and Analysis Support, collecting the user experience and feedback during analysis activities and developing tools to increase efficiency. The development plan for DMWM for 2009/2011 was developed at the beginning of the year, based on the requirements from the Physics, Computing and Offline groups (see Offline section). The Computing management meeting at FermiLab on February 19th and 20th was an excellent opportunity discussing the impact and for addressing issues and solutions to the main challenges facing CMS computing. The lack of manpower is particul...

  13. Evolution of the ATLAS Nightly Build System

    International Nuclear Information System (INIS)

    Undrus, A

    2012-01-01

    The ATLAS Nightly Build System is a major component in the ATLAS collaborative software organization, validation, and code approval scheme. For over 10 years of development it has evolved into a factory for automatic release production and grid distribution. The 50 multi-platform branches of ATLAS releases provide vast opportunities for testing new packages, verification of patches to existing software, and migration to new platforms and compilers for ATLAS code that currently contains 2200 packages with 4 million C++ and 1.4 million python scripting lines written by about 1000 developers. Recent development was focused on the integration of ATLAS Nightly Build and Installation systems. The nightly releases are distributed and validated and some are transformed into stable releases used for data processing worldwide. The ATLAS Nightly System is managed by the NICOS control tool on a computing farm with 50 powerful multiprocessor nodes. NICOS provides the fully automated framework for the release builds, testing, and creation of distribution kits. The ATN testing framework of the Nightly System runs unit and integration tests in parallel suites, fully utilizing the resources of multi-core machines, and provides the first results even before compilations complete. The NICOS error detection system is based on several techniques and classifies the compilation and test errors according to their severity. It is periodically tuned to place greater emphasis on certain software defects by highlighting the problems on NICOS web pages and sending automatic e-mail notifications to responsible developers. These and other recent developments will be presented and future plans will be described.

  14. Distributed analysis in ATLAS using GANGA

    International Nuclear Information System (INIS)

    Elmsheuser, Johannes; Brochu, Frederic; Egede, Ulrik; Reece, Will; Williams, Michael; Gaidioz, Benjamin; Maier, Andrew; Moscicki, Jakub; Vanderster, Daniel; Lee, Hurng-Chun; Pajchel, Katarina; Samset, Bjorn; Slater, Mark; Soroko, Alexander; Cowan, Greig

    2010-01-01

    Distributed data analysis using Grid resources is one of the fundamental applications in high energy physics to be addressed and realized before the start of LHC data taking. The needs to manage the resources are very high. In every experiment up to a thousand physicists will be submitting analysis jobs to the Grid. Appropriate user interfaces and helper applications have to be made available to assure that all users can use the Grid without expertise in Grid technology. These tools enlarge the number of Grid users from a few production administrators to potentially all participating physicists. The GANGA job management system (http://cern.ch/ganga), developed as a common project between the ATLAS and LHCb experiments, provides and integrates these kind of tools. GANGA provides a simple and consistent way of preparing, organizing and executing analysis tasks within the experiment analysis framework, implemented through a plug-in system. It allows trivial switching between running test jobs on a local batch system and running large-scale analyzes on the Grid, hiding Grid technicalities. We will be reporting on the plug-ins and our experiences of distributed data analysis using GANGA within the ATLAS experiment. Support for all Grids presently used by ATLAS, namely the LCG/EGEE, NDGF/NorduGrid, and OSG/PanDA is provided. The integration and interaction with the ATLAS data management system DQ2 into GANGA is a key functionality. An intelligent job brokering is set up by using the job splitting mechanism together with data-set and file location knowledge. The brokering is aided by an automated system that regularly processes test analysis jobs at all ATLAS DQ2 supported sites. Large numbers of analysis jobs can be sent to the locations of data following the ATLAS computing model. GANGA supports amongst other things tasks of user analysis with reconstructed data and small scale production of Monte Carlo data.

  15. The ATLAS Pixel Detector

    CERN Document Server

    Huegging, Fabian

    2006-06-26

    The contruction of the ATLAS Pixel Detector which is the innermost layer of the ATLAS tracking system is prgressing well. Because the pixel detector will contribute significantly to the ATLAS track and vertex reconstruction. The detector consists of identical sensor-chip-hybrid modules, arranged in three barrels in the centre and three disks on either side for the forward region. The position of the detector near the interaction point requires excellent radiation hardness, mechanical and thermal robustness, good long-term stability for all parts, combined with a low material budget. The final detector layout, new results from production modules and the status of assembly are presented.

  16. Integrating Networking into ATLAS

    CERN Document Server

    Mc Kee, Shawn Patrick; The ATLAS collaboration

    2018-01-01

    Networking is foundational to the ATLAS distributed infrastructure and there are many ongoing activities related to networking both within and outside of ATLAS. We will report on the progress in a number of areas exploring ATLAS's use of networking and our ability to monitor the network, analyze metrics from the network, and tune and optimize application and end-host parameters to make the most effective use of the network. Specific topics will include work on Open vSwitch for production systems, network analytics, FTS testing and tuning, and network problem alerting and alarming.

  17. Iberian ATLAS Cloud response during the first LHC collisions

    CERN Document Server

    Villaplana, M; The ATLAS collaboration; Borges, G; Borrego, C; Carvalho, J; David, M; Espinal, X; Fernández, A; Gomes, J; González de la Hoz, S; Kaci, M; Lamas, A; Nadal, J; Oliveira, M; Oliver, E; Osuna, C; Pacheco, A; Pardo, JJ; del Peso, J; Salt, J; Sánchez, J; Wolters, H

    2011-01-01

    The computing model of the ATLAS experiment at the LHC (Large Hadron Collider) is based on a tiered hierarchy that ranges from Tier0 (CERN) down to end-user's own resources (Tier3). According to the same computing model, the role of the Tier2s is to provide computing resources for event simulation processing and distributed data analysis. Tier3 centers, on the other hand, are the responsibility of individual institutions to define, fund, deploy and support. In this contribution we report on the operations of the ATLAS Iberian Cloud centers facing data taking and we describe some of the Tier3 facilities currently deployed at the Cloud.

  18. First-year experience with the ATLAS online monitoring framework

    International Nuclear Information System (INIS)

    Corso-Radu, A

    2010-01-01

    ATLAS is one of the four experiments in the Large Hadron Collider (LHC) at CERN, which has been put in operation this year. The challenging experimental environment and the extreme detector complexity required development of a highly scalable distributed monitoring framework, which is currently being used to monitor the quality of the data being taken as well as operational conditions of the hardware and software elements of the detector, trigger and data acquisition systems. At the moment the ATLAS Trigger/DAQ system is distributed over more than 1000 computers, which is about one third of the final ATLAS size. At every minute of an ATLAS data taking session the monitoring framework serves several thousands physics events to monitoring data analysis applications, handles more than 4 million histograms updates coming from more than 4 thousands applications, executes 10 thousands advanced data quality checks for a subset of those histograms, displays histograms and results of these checks on several dozens of monitors installed in main and satellite ATLAS control rooms. This note presents the overview of the online monitoring software framework, and describes the experience, which was gained during an extensive commissioning period as well as at the first phase of LHC beam in September 2008. Performance results, obtained on the current ATLAS DAQ system will also be presented, showing that the performance of the framework is adequate for the final ATLAS system.

  19. 11 March 2009 - Italian Minister of Education, University and Research M. Gelmini, visiting ATLAS and CMS underground experimental areas and LHC tunnel with Director for Research and Scientific Computing S. Bertolucci. Signature of the guest book with CERN Director-General R. Heuer and S. Bertolucci at CMS Point 5.

    CERN Multimedia

    Maximilien Brice

    2009-01-01

    Members of the Ministerial delegation: Cons. Amb. Sebastiano FULCI, Consigliere Diplomatico Dott.ssa Elisa GREGORINI, Segretario Particolare del Ministro Dott. Massimo ZENNARO, Responsabile rapporti con la stampa Prof. Roberto PETRONZIO, Presidente dell’INFN (Istituto Nazionale di Fisica Nucleare) Dott. Luciano CRISCUOLI, Direttore Generale della Ricerca, MIUR Dott. Andrea MARINONI, Consulente scientifico del Ministro CERN delegation present throughout the programme: Prof. Sergio Bertolucci, Director for Research and Scientific Computing Prof. Fabiola Gianotti, ATLAS Collaboration Spokesperson Prof. Paolo Giubellino, ALICE Deputy Spokesperson, Universita & INFN, Torino Prof. Guido Tonelli, CMS Collaboration Deputy Spokesperson, INFN Pisa Dr Monica Pepe-Altarelli, LHCb Collaboration CERN Team Leader Guests in the ATLAS exhibition area: Dr Marcello Givoletti\tPresident of CAEN Dr Davide Malacalza\tPresident of ASG Ansaldo Superconductors and users: Prof. Clara Matteuzzi, LHCb Collaboration, Universita' d...

  20. COMPUTING

    CERN Multimedia

    I. Fisk

    2013-01-01

    Computing activity had ramped down after the completion of the reprocessing of the 2012 data and parked data, but is increasing with new simulation samples for analysis and upgrade studies. Much of the Computing effort is currently involved in activities to improve the computing system in preparation for 2015. Operations Office Since the beginning of 2013, the Computing Operations team successfully re-processed the 2012 data in record time, not only by using opportunistic resources like the San Diego Supercomputer Center which was accessible, to re-process the primary datasets HTMHT and MultiJet in Run2012D much earlier than planned. The Heavy-Ion data-taking period was successfully concluded in February collecting almost 500 T. Figure 3: Number of events per month (data) In LS1, our emphasis is to increase efficiency and flexibility of the infrastructure and operation. Computing Operations is working on separating disk and tape at the Tier-1 sites and the full implementation of the xrootd federation ...

  1. Production experience with the ATLAS Event Service

    Science.gov (United States)

    Benjamin, D.; Calafiura, P.; Childers, T.; De, K.; Guan, W.; Maeno, T.; Nilsson, P.; Tsulaia, V.; Van Gemmeren, P.; Wenaus, T.; ATLAS Collaboration

    2017-10-01

    The ATLAS Event Service (AES) has been designed and implemented for efficient running of ATLAS production workflows on a variety of computing platforms, ranging from conventional Grid sites to opportunistic, often short-lived resources, such as spot market commercial clouds, supercomputers and volunteer computing. The Event Service architecture allows real time delivery of fine grained workloads to running payload applications which process dispatched events or event ranges and immediately stream the outputs to highly scalable Object Stores. Thanks to its agile and flexible architecture the AES is currently being used by grid sites for assigning low priority workloads to otherwise idle computing resources; similarly harvesting HPC resources in an efficient back-fill mode; and massively scaling out to the 50-100k concurrent core level on the Amazon spot market to efficiently utilize those transient resources for peak production needs. Platform ports in development include ATLAS@Home (BOINC) and the Google Compute Engine, and a growing number of HPC platforms. After briefly reviewing the concept and the architecture of the Event Service, we will report the status and experience gained in AES commissioning and production operations on supercomputers, and our plans for extending ES application beyond Geant4 simulation to other workflows, such as reconstruction and data analysis.

  2. Implementation of the ATLAS trigger within the ATLAS Multi­Threaded Software Framework AthenaMT

    CERN Document Server

    Wynne, Benjamin; The ATLAS collaboration

    2016-01-01

    We present an implementation of the ATLAS High Level Trigger that provides parallel execution of trigger algorithms within the ATLAS multi­threaded software framework, AthenaMT. This development will enable the ATLAS High Level Trigger to meet future challenges due to the evolution of computing hardware and upgrades of the Large Hadron Collider, LHC, and ATLAS Detector. During the LHC data­taking period starting in 2021, luminosity will reach up to three times the original design value. Luminosity will increase further, to up to 7.5 times the design value, in 2026 following LHC and ATLAS upgrades. This includes an upgrade of the ATLAS trigger architecture that will result in an increase in the High Level Trigger input rate by a factor of 4 to 10 compared to the current maximum rate of 100 kHz. The current ATLAS multiprocess framework, AthenaMP, manages a number of processes that process events independently, executing algorithms sequentially in each process. AthenaMT will provide a fully multi­threaded env...

  3. The Latest from ATLAS

    CERN Multimedia

    2009-01-01

    Since November 2008, ATLAS has undertaken detailed maintenance, consolidation and repair work on the detector (see Bulletin of 20 July 2009). Today, the fraction of the detector that is operational has increased compared to last year: less than 1% of dead channels for most of the sub-systems. "We are going to start taking data this year with a detector which is even more efficient than it was last year," agrees ATLAS Spokesperson, Fabiola Gianotti. By mid-September the detector was fully closed again, and the cavern sealed. The magnet system has been operated at nominal current for extensive periods over recent months. Once the cavern was sealed, ATLAS began two weeks of combined running. Right now, subsystems are joining the run incrementally until the point where the whole detector is integrated and running as one. In the words of ATLAS Technical Coordinator, Marzio Nessi: "Now we really start physics." In parallel, the analysis ...

  4. ATLAS soft QCD results

    CERN Document Server

    Sykora, Tomas; The ATLAS collaboration

    2018-01-01

    Recent results of soft QCD measurements performed by the ATLAS collaboration are reported. The measurements include total, elastic and inelastic cross sections, inclusive spectra, underlying event and particle correlations in p-p and p-Pb collisions.

  5. PeptideAtlas

    Data.gov (United States)

    U.S. Department of Health & Human Services — PeptideAtlas is a multi-organism, publicly accessible compendium of peptides identified in a large set of tandem mass spectrometry proteomics experiments. Mass...

  6. Apollo Image Atlas

    Data.gov (United States)

    National Aeronautics and Space Administration — The Apollo Image Atlas is a comprehensive collection of Apollo-Saturn mission photography. Included are almost 25,000 lunar images, both from orbit and from the...

  7. Consolidated Lunar Atlas

    Data.gov (United States)

    National Aeronautics and Space Administration — The Consolidated Lunar Atlas is a collection of the best photographic images of the moon, including low-oblique photography, full-moon photography, and tabular and...

  8. ATLAS fast physics monitoring

    Indian Academy of Sciences (India)

    2012-11-16

    Nov 16, 2012 ... laboration has set up a framework to automatically process the ... ing (FPM) is complementary to data quality monitoring as problems may ... the full power of the ATLAS software framework Athena [4] and the availability of the.

  9. Printed circuit for ATLAS

    CERN Multimedia

    Laurent Guiraud

    1999-01-01

    A printed circuit board made by scientists in the ATLAS collaboration for the transition radiaton tracker (TRT). This will read data produced when a high energy particle crosses the boundary between two materials with different electrical properties.

  10. ATLAS Metadata Task Force

    Energy Technology Data Exchange (ETDEWEB)

    ATLAS Collaboration; Costanzo, D.; Cranshaw, J.; Gadomski, S.; Jezequel, S.; Klimentov, A.; Lehmann Miotto, G.; Malon, D.; Mornacchi, G.; Nemethy, P.; Pauly, T.; von der Schmitt, H.; Barberis, D.; Gianotti, F.; Hinchliffe, I.; Mapelli, L.; Quarrie, D.; Stapnes, S.

    2007-04-04

    This document provides an overview of the metadata, which are needed to characterizeATLAS event data at different levels (a complete run, data streams within a run, luminosity blocks within a run, individual events).

  11. California Ocean Uses Atlas

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset is a result of the California Ocean Uses Atlas Project: a collaboration between NOAA's National Marine Protected Areas Center and Marine Conservation...

  12. ATLAS, an integrated structural analysis and design system. Volume 4: Random access file catalog

    Science.gov (United States)

    Gray, F. P., Jr. (Editor)

    1979-01-01

    A complete catalog is presented for the random access files used by the ATLAS integrated structural analysis and design system. ATLAS consists of several technical computation modules which output data matrices to corresponding random access file. A description of the matrices written on these files is contained herein.

  13. Fast and robust multi-atlas segmentation of brain magnetic resonance images

    DEFF Research Database (Denmark)

    Lötjönen, Jyrki Mp; Wolz, Robin; Koikkalainen, Juha R

    2010-01-01

    of standard normalised mutual information in registration without compromising the accuracy but leading to threefold decrease in the computation time. We study and validate also different methods for atlas selection. Finally, we propose two new approaches for combining multi-atlas segmentation and intensity...

  14. ATLAS accelerator laboratory report

    International Nuclear Information System (INIS)

    Den Hartog, P.

    1986-01-01

    The operation of the ATLAS Accelerator is reported. Modifications are reported, including the installation of conductive tires for the Pelletron chain pulleys, installation of a new high frequency sweeper system at the entrance to the linac, and improvements to the rf drive ports of eight resonators to correct failures in the thermally conductive ceramic insulators. Progress is reported on the positive-ion injector upgrade for ATLAS. Also reported are building modifications and possible new uses for the tandem injector

  15. The ATLAS electromagnetic calorimeter

    CERN Multimedia

    Maximilien Brice

    2003-01-01

    Michel Mathieu, a technician for the ATLAS collaboration, is cabling the ATLAS electromagnetic calorimeter's first end-cap, before insertion into its cryostat. Millions of wires are connected to the electromagnetic calorimeter on this end-cap that must be carefully fed out from the detector so that data can be read out. Every element on the detector will be attached to one of these wires so that a full digital map of the end-cap can be recreated.

  16. Budker INP in ATLAS

    CERN Multimedia

    2001-01-01

    The Novosibirsk group has proposed a new design for the ATLAS liquid argon electromagnetic end-cap calorimeter with a constant thickness of absorber plates. This design has signifi- cant advantages compared to one in the Technical Proposal and it has been accepted by the ATLAS Collaboration. The Novosibirsk group is responsible for the fabrication of the precision aluminium structure for the e.m.end-cap calorimeter.

  17. ATLAS construction status

    International Nuclear Information System (INIS)

    Jenni, P.

    2006-01-01

    The ATLAS detector is being constructed at the LHC, in view of a data-taking startup in 2007. This report concentrates on the progress and the technical challenges of the detector construction, and summarizes the status of the work as of August 2004. The project is on track to allow the highly motivated ATLAS Collaboration to enter into a new exploratory domain of high-energy physics in 2007. (author)

  18. COMPUTING

    CERN Multimedia

    I. Fisk

    2010-01-01

    Introduction It has been a very active quarter in Computing with interesting progress in all areas. The activity level at the computing facilities, driven by both organised processing from data operations and user analysis, has been steadily increasing. The large-scale production of simulated events that has been progressing throughout the fall is wrapping-up and reprocessing with pile-up will continue. A large reprocessing of all the proton-proton data has just been released and another will follow shortly. The number of analysis jobs by users each day, that was already hitting the computing model expectations at the time of ICHEP, is now 33% higher. We are expecting a busy holiday break to ensure samples are ready in time for the winter conferences. Heavy Ion An activity that is still in progress is computing for the heavy-ion program. The heavy-ion events are collected without zero suppression, so the event size is much large at roughly 11 MB per event of RAW. The central collisions are more complex and...

  19. COMPUTING

    CERN Multimedia

    M. Kasemann P. McBride Edited by M-C. Sawley with contributions from: P. Kreuzer D. Bonacorsi S. Belforte F. Wuerthwein L. Bauerdick K. Lassila-Perini M-C. Sawley

    Introduction More than seventy CMS collaborators attended the Computing and Offline Workshop in San Diego, California, April 20-24th to discuss the state of readiness of software and computing for collisions. Focus and priority were given to preparations for data taking and providing room for ample dialog between groups involved in Commissioning, Data Operations, Analysis and MC Production. Throughout the workshop, aspects of software, operating procedures and issues addressing all parts of the computing model were discussed. Plans for the CMS participation in STEP’09, the combined scale testing for all four experiments due in June 2009, were refined. The article in CMS Times by Frank Wuerthwein gave a good recap of the highly collaborative atmosphere of the workshop. Many thanks to UCSD and to the organizers for taking care of this workshop, which resulted in a long list of action items and was definitely a success. A considerable amount of effort and care is invested in the estimate of the comput...

  20. Overview of the ATLAS Fast Tracker Project

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00025195; The ATLAS collaboration

    2016-01-01

    The next LHC runs, with a significant increase in instantaneous luminosity, will provide a big challenge for the trigger and data acquisition systems of all the experiments. An intensive use of the tracking information at the trigger level will be important to keep high efficiency for interesting events despite the increase in multiple collisions per bunch crossing. In order to increase the use of tracks within the High Level Trigger, the ATLAS experiment planned the installation of a hardware processor dedicated to tracking: the Fast TracKer processor. The Fast Tracker is designed to perform full scan track reconstruction of every event accepted by the ATLAS first level hardware trigger. To achieve this goal the system uses a parallel architecture, with algorithms designed to exploit the computing power of custom Associative Memory chips, and modern field programmable gate arrays. The processor will provide computing power to reconstruct tracks with transverse momentum greater than 1 GeV in the whole trackin...

  1. Alignment of the ATLAS Inner Detector Tracking System

    CERN Document Server

    Moles-Valls, R

    2008-01-01

    The ATLAS experiment is equipped with a tracking system for c harged particles built on two technologies: silicon and drift tube base detectors. These kind of detectors compose the ATLAS Inner Detector (ID). The Alignment of the ATLAS ID tracking s ystem requires the determination of almost 36000 degrees of freedom. From the tracking point o f view, the alignment parameters should be know to a few microns precision. This permits to att ain optimal measurements of the parameters of the charged particles trajectories, thus ena bling ATLAS to achieve its physics goals. The implementation of the alignment software, its framewor k and the data flow will be discussed. Special attention will be paid to the recent challenges wher e large scale computing simulation of the ATLAS detector has been performed, mimicking the ATLAS o peration, which is going to be very important for the LHC startup scenario. The alignment r esult for several challenges (real cosmic ray data taking and computing system commissioning) will be...

  2. ATLAS Facility Description Report

    International Nuclear Information System (INIS)

    Kang, Kyoung Ho; Moon, Sang Ki; Park, Hyun Sik; Cho, Seok; Choi, Ki Yong

    2009-04-01

    A thermal-hydraulic integral effect test facility, ATLAS (Advanced Thermal-hydraulic Test Loop for Accident Simulation), has been constructed at KAERI (Korea Atomic Energy Research Institute). The ATLAS has the same two-loop features as the APR1400 and is designed according to the well-known scaling method suggested by Ishii and Kataoka to simulate the various test scenarios as realistically as possible. It is a half-height and 1/288-volume scaled test facility with respect to the APR1400. The fluid system of the ATLAS consists of a primary system, a secondary system, a safety injection system, a break simulating system, a containment simulating system, and auxiliary systems. The primary system includes a reactor vessel, two hot legs, four cold legs, a pressurizer, four reactor coolant pumps, and two steam generators. The secondary system of the ATLAS is simplified to be of a circulating loop-type. Most of the safety injection features of the APR1400 and the OPR1000 are incorporated into the safety injection system of the ATLAS. In the ATLAS test facility, about 1300 instrumentations are installed to precisely investigate the thermal-hydraulic behavior in simulation of the various test scenarios. This report describes the scaling methodology, the geometric data of the individual component, and the specification and the location of the instrumentations in detail

  3. The last ATLAS overview week now available on Web Lectures

    CERN Multimedia

    Jeremy Herr

    2006-01-01

    As reported in the September 2004 ATLAS eNews, the Web Lecture Archive Project, WLAP, a collaboration between the University of Michigan and CERN, has developed a synchronized system for recording and publishing educational multimedia presentations, using the Web as medium. This year, the University of Michigan team has been asked to record and publish all ATLAS Plenary sessions, as well as a large number of Physics and Computing tutorials. A significant amount of this material has already been published and can be accessed via the links below. All lectures can be viewed on any major platform with any common internet browser, either via streaming or local download (for limited bandwidth). Please enjoy the lectures and send us a note at wlap@umich.edu to tell us what you think. The newly available WLAP items relating to ATLAS is the following: ATLAS Week Plenary, CERN, 2-3 October 2006 All previous WLAP lectures are also avilable on the web.

  4. ATLAS Tier-3 within IFIC-Valencia analysis facility

    CERN Document Server

    Villaplana, M; The ATLAS collaboration; Fernández, A; Salt, J; Lamas, A; Fassi, F; Kaci, M; Oliver, E; Sánchez, J; Sánchez-Martínez, V

    2012-01-01

    The ATLAS Tier-3 at IFIC-Valencia is attached to a Tier-2 that has 50% of the Spanish Federated Tier-2 resources. In its design, the Tier-3 includes a GRID-aware part that shares some of the features of IFIC Tier-2 such as using Lustre as a file system. ATLAS users, 70% of IFIC users, also have the possibility of analysing data with a PROOF farm and storing them locally. In this contribution we discuss the design of the analysis facility as well as the monitoring tools we use to control and improve its performance. We also comment on how the recent changes in the ATLAS computing GRID model affect IFIC. Finally, how this complex system can coexist with the other scientific applications running at IFIC (non-ATLAS users) is presented.

  5. Reliability Engineering for ATLAS Petascale Data Processing on the Grid

    CERN Document Server

    Golubkov, D V; The ATLAS collaboration; Vaniachine, A V

    2012-01-01

    The ATLAS detector is in its third year of continuous LHC running taking data for physics analysis. A starting point for ATLAS physics analysis is reconstruction of the raw data. First-pass processing takes place shortly after data taking, followed later by reprocessing of the raw data with updated software and calibrations to improve the quality of the reconstructed data for physics analysis. Data reprocessing involves a significant commitment of computing resources and is conducted on the Grid. The reconstruction of one petabyte of ATLAS data with 1B collision events from the LHC takes about three million core-hours. Petascale data processing on the Grid involves millions of data processing jobs. At such scales, the reprocessing must handle a continuous stream of failures. Automatic job resubmission recovers transient failures at the cost of CPU time used by the failed jobs. Orchestrating ATLAS data processing applications to ensure efficient usage of tens of thousands of CPU-cores, reliability engineering ...

  6. Morphometric Atlas Selection for Automatic Brachial Plexus Segmentation

    International Nuclear Information System (INIS)

    Van de Velde, Joris; Wouters, Johan; Vercauteren, Tom; De Gersem, Werner; Duprez, Fréderic; De Neve, Wilfried; Van Hoof, Tom

    2015-01-01

    Purpose: The purpose of this study was to determine the effects of atlas selection based on different morphometric parameters, on the accuracy of automatic brachial plexus (BP) segmentation for radiation therapy planning. The segmentation accuracy was measured by comparing all of the generated automatic segmentations with anatomically validated gold standard atlases developed using cadavers. Methods and Materials: Twelve cadaver computed tomography (CT) atlases (3 males, 9 females; mean age: 73 years) were included in the study. One atlas was selected to serve as a patient, and the other 11 atlases were registered separately onto this “patient” using deformable image registration. This procedure was repeated for every atlas as a patient. Next, the Dice and Jaccard similarity indices and inclusion index were calculated for every registered BP with the original gold standard BP. In parallel, differences in several morphometric parameters that may influence the BP segmentation accuracy were measured for the different atlases. Specific brachial plexus-related CT-visible bony points were used to define the morphometric parameters. Subsequently, correlations between the similarity indices and morphometric parameters were calculated. Results: A clear negative correlation between difference in protraction-retraction distance and the similarity indices was observed (mean Pearson correlation coefficient = −0.546). All of the other investigated Pearson correlation coefficients were weak. Conclusions: Differences in the shoulder protraction-retraction position between the atlas and the patient during planning CT influence the BP autosegmentation accuracy. A greater difference in the protraction-retraction distance between the atlas and the patient reduces the accuracy of the BP automatic segmentation result

  7. Migration of ATLAS PanDA to CERN

    International Nuclear Information System (INIS)

    Stewart, Graeme Andrew; Klimentov, Alexei; Maeno, Tadashi; Nevski, Pavel; Nowak, Marcin; De Castro Faria Salgado, Pedro Emanuel; Wenaus, Torre; Koblitz, Birger; Lamanna, Massimo

    2010-01-01

    The ATLAS Production and Distributed Analysis System (PanDA) is a key component of the ATLAS distributed computing infrastructure. All ATLAS production jobs, and a substantial amount of user and group analysis jobs, pass through the PanDA system, which manages their execution on the grid. PanDA also plays a key role in production task definition and the data set replication request system. PanDA has recently been migrated from Brookhaven National Laboratory (BNL) to the European Organization for Nuclear Research (CERN), a process we describe here. We discuss how the new infrastructure for PanDA, which relies heavily on services provided by CERN IT, was introduced in order to make the service as reliable as possible and to allow it to be scaled to ATLAS's increasing need for distributed computing. The migration involved changing the backend database for PanDA from MySQL to Oracle, which impacted upon the database schemas. The process by which the client code was optimised for the new database backend is discussed. We describe the procedure by which the new database infrastructure was tested and commissioned for production use. Operations during the migration had to be planned carefully to minimise disruption to ongoing ATLAS offline computing. All parts of the migration were fully tested before commissioning the new infrastructure and the gradual migration of computing resources to the new system allowed any problems of scaling to be addressed.

  8. Multilevel Workflow System in the ATLAS Experiment

    CERN Document Server

    Borodin, M; The ATLAS collaboration; Golubkov, D; Klimentov, A; Maeno, T; Vaniachine, A

    2015-01-01

    The ATLAS experiment is scaling up Big Data processing for the next LHC run using a multilevel workflow system comprised of many layers. In Big Data processing ATLAS deals with datasets, not individual files. Similarly a task (comprised of many jobs) has become a unit of the ATLAS workflow in distributed computing, with about 0.8M tasks processed per year. In order to manage the diversity of LHC physics (exceeding 35K physics samples per year), the individual data processing tasks are organized into workflows. For example, the Monte Carlo workflow is composed of many steps: generate or configure hard-processes, hadronize signal and minimum-bias (pileup) events, simulate energy deposition in the ATLAS detector, digitize electronics response, simulate triggers, reconstruct data, convert the reconstructed data into ROOT ntuples for physics analysis, etc. Outputs are merged and/or filtered as necessary to optimize the chain. The bi-level workflow manager - ProdSys2 - generates actual workflow tasks and their jobs...

  9. Performance and impact of dynamic data placement in ATLAS

    CERN Document Server

    Maier, Thomas; The ATLAS collaboration

    2018-01-01

    For high-throughput computing the efficient use of distributed computing resources relies on an evenly distributed workload, which in turn requires wide availability of input data that is used in physics analysis. In ATLAS, the dynamic data placement agent C3PO was implemented in the ATLAS distributed data management system Rucio which identifies popular data and creates additional, transient replicas to make data more widely and more reliably available. This contribution presents studies on the performance of C3PO and the impact it has on throughput rates of distributed computing in ATLAS. This includes analysis of the placement algorithm selection behaviour regarding the data considered for replication and destination storage elements, usage after the placement decision of the chosen datasets in general and the newly created copies in particular, and the impact on metrics like job waiting times, task completion times and failure rates of tasks.

  10. Study of ATLAS TRT performance with GRID and supercomputers.

    CERN Document Server

    Krasnopevtsev, Dimitriy; The ATLAS collaboration; Mashinistov, Ruslan; Belyaev, Nikita; Ryabinkin, Evgeny

    2015-01-01

    After the early success in discovering a new particle consistent with the long awaited Higgs boson, Large Hadron Collider experiments are ready for the precision measurements and further discoveries that will be made possible by much higher LHC collision rates from spring 2015. A proper understanding of the detectors performance at high occupancy conditions is important for many on-going physics analyses. The ATLAS Transition Radiation Tracker (TRT) is one of these detectors. TRT is a large straw tube tracking system that is the outermost of the three subsystems of the ATLAS Inner Detector (ID). TRT contributes significantly to the resolution for high-pT tracks in the ID providing excellent particle identification capabilities and electron-pion separation. ATLAS experiment is using Worldwide LHC Computing Grid. WLCG is a global collaboration of computer centers and provides seamless access to computing resources which include data storage capacity, processing power, sensors, visualisation tools and more. WLCG...

  11. Study of ATLAS TRT performance with GRID and supercomputers.

    CERN Document Server

    Krasnopevtsev, Dimitriy; The ATLAS collaboration; Belyaev, Nikita; Mashinistov, Ruslan; Ryabinkin, Evgeny

    2015-01-01

    After the early success in discovering a new particle consistent with the long awaited Higgs boson, Large Hadron Collider experiments are ready for the precision measurements and further discoveries that will be made possible by much higher LHC collision rates from spring 2015. A proper understanding of the detectors performance at highoccupancy conditions is important for many on-going physics analyses. The ATLAS Transition Radiation Tracker (TRT) is one of these detectors. TRT is a large straw tube tracking system that is the outermost of the three subsystems of the ATLAS Inner Detector (ID). TRT contributes significantly to the resolution for high-pT tracks in the ID providing excellent particle identification capabilities and electron-pion separation. ATLAS experiment is using Worldwide LHC Computing Grid. WLCG is a global collaboration of computer centers and provides seamless access to computing resources which include data storage capacity, processing power, sensors, visualization tools and more. WLCG ...

  12. COMPUTING

    CERN Multimedia

    P. McBride

    It has been a very active year for the computing project with strong contributions from members of the global community. The project has focused on site preparation and Monte Carlo production. The operations group has begun processing data from P5 as part of the global data commissioning. Improvements in transfer rates and site availability have been seen as computing sites across the globe prepare for large scale production and analysis as part of CSA07. Preparations for the upcoming Computing Software and Analysis Challenge CSA07 are progressing. Ian Fisk and Neil Geddes have been appointed as coordinators for the challenge. CSA07 will include production tests of the Tier-0 production system, reprocessing at the Tier-1 sites and Monte Carlo production at the Tier-2 sites. At the same time there will be a large analysis exercise at the Tier-2 centres. Pre-production simulation of the Monte Carlo events for the challenge is beginning. Scale tests of the Tier-0 will begin in mid-July and the challenge it...

  13. COMPUTING

    CERN Multimedia

    I. Fisk

    2011-01-01

    Introduction It has been a very active quarter in Computing with interesting progress in all areas. The activity level at the computing facilities, driven by both organised processing from data operations and user analysis, has been steadily increasing. The large-scale production of simulated events that has been progressing throughout the fall is wrapping-up and reprocessing with pile-up will continue. A large reprocessing of all the proton-proton data has just been released and another will follow shortly. The number of analysis jobs by users each day, that was already hitting the computing model expectations at the time of ICHEP, is now 33% higher. We are expecting a busy holiday break to ensure samples are ready in time for the winter conferences. Heavy Ion The Tier 0 infrastructure was able to repack and promptly reconstruct heavy-ion collision data. Two copies were made of the data at CERN using a large CASTOR disk pool, and the core physics sample was replicated ...

  14. COMPUTING

    CERN Multimedia

    I. Fisk

    2012-01-01

    Introduction Computing continued with a high level of activity over the winter in preparation for conferences and the start of the 2012 run. 2012 brings new challenges with a new energy, more complex events, and the need to make the best use of the available time before the Long Shutdown. We expect to be resource constrained on all tiers of the computing system in 2012 and are working to ensure the high-priority goals of CMS are not impacted. Heavy ions After a successful 2011 heavy-ion run, the programme is moving to analysis. During the run, the CAF resources were well used for prompt analysis. Since then in 2012 on average 200 job slots have been used continuously at Vanderbilt for analysis workflows. Operations Office As of 2012, the Computing Project emphasis has moved from commissioning to operation of the various systems. This is reflected in the new organisation structure where the Facilities and Data Operations tasks have been merged into a common Operations Office, which now covers everything ...

  15. COMPUTING

    CERN Multimedia

    M. Kasemann

    CCRC’08 challenges and CSA08 During the February campaign of the Common Computing readiness challenges (CCRC’08), the CMS computing team had achieved very good results. The link between the detector site and the Tier0 was tested by gradually increasing the number of parallel transfer streams well beyond the target. Tests covered the global robustness at the Tier0, processing a massive number of very large files and with a high writing speed to tapes.  Other tests covered the links between the different Tiers of the distributed infrastructure and the pre-staging and reprocessing capacity of the Tier1’s: response time, data transfer rate and success rate for Tape to Buffer staging of files kept exclusively on Tape were measured. In all cases, coordination with the sites was efficient and no serious problem was found. These successful preparations prepared the ground for the second phase of the CCRC’08 campaign, in May. The Computing Software and Analysis challen...

  16. COMPUTING

    CERN Multimedia

    I. Fisk

    2010-01-01

    Introduction The first data taking period of November produced a first scientific paper, and this is a very satisfactory step for Computing. It also gave the invaluable opportunity to learn and debrief from this first, intense period, and make the necessary adaptations. The alarm procedures between different groups (DAQ, Physics, T0 processing, Alignment/calibration, T1 and T2 communications) have been reinforced. A major effort has also been invested into remodeling and optimizing operator tasks in all activities in Computing, in parallel with the recruitment of new Cat A operators. The teams are being completed and by mid year the new tasks will have been assigned. CRB (Computing Resource Board) The Board met twice since last CMS week. In December it reviewed the experience of the November data-taking period and could measure the positive improvements made for the site readiness. It also reviewed the policy under which Tier-2 are associated with Physics Groups. Such associations are decided twice per ye...

  17. COMPUTING

    CERN Multimedia

    M. Kasemann

    Introduction More than seventy CMS collaborators attended the Computing and Offline Workshop in San Diego, California, April 20-24th to discuss the state of readiness of software and computing for collisions. Focus and priority were given to preparations for data taking and providing room for ample dialog between groups involved in Commissioning, Data Operations, Analysis and MC Production. Throughout the workshop, aspects of software, operating procedures and issues addressing all parts of the computing model were discussed. Plans for the CMS participation in STEP’09, the combined scale testing for all four experiments due in June 2009, were refined. The article in CMS Times by Frank Wuerthwein gave a good recap of the highly collaborative atmosphere of the workshop. Many thanks to UCSD and to the organizers for taking care of this workshop, which resulted in a long list of action items and was definitely a success. A considerable amount of effort and care is invested in the estimate of the co...

  18. Report to users of ATLAS

    International Nuclear Information System (INIS)

    Ahmad, I.; Glagola, B.

    1997-03-01

    This report covers the following topics: (1) status of the ATLAS accelerator; (2) progress in R and D towards a proposal for a National ISOL Facility; (3) highlights of recent research at ATLAS; (4) the move of gammasphere from LBNL to ANL; (5) Accelerator Target Development laboratory; (6) Program Advisory Committee; (7) ATLAS User Group Executive Committee; and (8) ATLAS user handbook available in the World Wide Web. A brief summary is given for each topic

  19. Recent ATLAS Articles on WLAP

    CERN Multimedia

    Goldfarb, S.

    As reported in the September 2004 ATLAS eNews, the Web Lecture Archive Project is a system for the archiving and publishing of multimedia presentations, using the Web as medium. We list here newly available WLAP items relating to ATLAS: June ATLAS Plenary Meeting Tutorial on Physics EDM and Tools (June) Freiburg Overview Week Ketevi Assamagan's Tutorial on Analysis Tools Click here to browse WLAP for all ATLAS lectures.

  20. ATLAS Overview Week at Brookhaven

    CERN Multimedia

    Pilcher, J

    Over 200 ATLAS participants gathered at Brookhaven National Laboratory during the first week of June for our annual overview week. Some system communities arrived early and held meetings on Saturday and Sunday, and the detector interface group (DIG) and Technical Coordination also took advantage of the time to discuss issues of interest for all detector systems. Sunday was also marked by a workshop on the possibilities for heavy ion physics with ATLAS. Beginning on Monday, and for the rest of the week, sessions were held in common in the well equipped Berkner Hall auditorium complex. Laptop computers became the norm for presentations and a wireless network kept laptop owners well connected. Most lunches and dinners were held on the lawn outside Berkner Hall. The weather was very cooperative and it was an extremely pleasant setting. This picture shows most of the participants from a view on the roof of Berkner Hall. Technical Coordination and Integration issues started the reports on Monday and became a...

  1. ATLAS FTK: Fast Track Trigger

    CERN Document Server

    Volpi, Guido; The ATLAS collaboration

    2015-01-01

    An overview of the ATLAS Fast Tracker processor is presented, reporting the design of the system, its expected performance, and the integration status. The next LHC runs, with a significant increase in instantaneous luminosity, will provide a big challenge to the trigger and data acquisition systems of all the experiments. An intensive use of the tracking information at the trigger level will be important to keep high efficiency in interesting events, despite the increase in multiple p-p collisions per bunch crossing (pile-up). In order to increase the use of tracks within the High Level Trigger (HLT), the ATLAS experiment planned the installation of an hardware processor dedicated to tracking: the Fast TracKer (FTK) processor. The FTK is designed to perform full scan track reconstruction at every Level-1 accept. To achieve this goal, the FTK uses a fully parallel architecture, with algorithms designed to exploit the computing power of custom VLSI chips, the Associative Memory, as well as modern FPGAs. The FT...

  2. Atlas of Skeletal SPECT/CT Clinical Images

    International Nuclear Information System (INIS)

    2016-01-01

    The atlas focuses specifically on single photon emission computed tomography/computed tomography (SPECT/CT) in musculoskeletal imaging, and thus illustrates the inherent advantages of the combination of the metabolic and anatomical component in a single procedure. In addition, the atlas provides information on the usefulness of several sets of specific indications. The publication, which serves more as a training tool rather than a textbook, will help to further integrate the SPECT and CT experience in clinical practice by presenting a series of typical cases with many different patterns of SPECT/CT seen in bone scintigraphy

  3. COMPUTING

    CERN Multimedia

    2010-01-01

    Introduction Just two months after the “LHC First Physics” event of 30th March, the analysis of the O(200) million 7 TeV collision events in CMS accumulated during the first 60 days is well under way. The consistency of the CMS computing model has been confirmed during these first weeks of data taking. This model is based on a hierarchy of use-cases deployed between the different tiers and, in particular, the distribution of RECO data to T1s, who then serve data on request to T2s, along a topology known as “fat tree”. Indeed, during this period this model was further extended by almost full “mesh” commissioning, meaning that RECO data were shipped to T2s whenever possible, enabling additional physics analyses compared with the “fat tree” model. Computing activities at the CMS Analysis Facility (CAF) have been marked by a good time response for a load almost evenly shared between ALCA (Alignment and Calibration tasks - highest p...

  4. COMPUTING

    CERN Multimedia

    Contributions from I. Fisk

    2012-01-01

    Introduction The start of the 2012 run has been busy for Computing. We have reconstructed, archived, and served a larger sample of new data than in 2011, and we are in the process of producing an even larger new sample of simulations at 8 TeV. The running conditions and system performance are largely what was anticipated in the plan, thanks to the hard work and preparation of many people. Heavy ions Heavy Ions has been actively analysing data and preparing for conferences.  Operations Office Figure 6: Transfers from all sites in the last 90 days For ICHEP and the Upgrade efforts, we needed to produce and process record amounts of MC samples while supporting the very successful data-taking. This was a large burden, especially on the team members. Nevertheless the last three months were very successful and the total output was phenomenal, thanks to our dedicated site admins who keep the sites operational and the computing project members who spend countless hours nursing the...

  5. COMPUTING

    CERN Multimedia

    M. Kasemann

    Introduction A large fraction of the effort was focused during the last period into the preparation and monitoring of the February tests of Common VO Computing Readiness Challenge 08. CCRC08 is being run by the WLCG collaboration in two phases, between the centres and all experiments. The February test is dedicated to functionality tests, while the May challenge will consist of running at all centres and with full workflows. For this first period, a number of functionality checks of the computing power, data repositories and archives as well as network links are planned. This will help assess the reliability of the systems under a variety of loads, and identifying possible bottlenecks. Many tests are scheduled together with other VOs, allowing the full scale stress test. The data rates (writing, accessing and transfer¬ring) are being checked under a variety of loads and operating conditions, as well as the reliability and transfer rates of the links between Tier-0 and Tier-1s. In addition, the capa...

  6. COMPUTING

    CERN Multimedia

    Matthias Kasemann

    Overview The main focus during the summer was to handle data coming from the detector and to perform Monte Carlo production. The lessons learned during the CCRC and CSA08 challenges in May were addressed by dedicated PADA campaigns lead by the Integration team. Big improvements were achieved in the stability and reliability of the CMS Tier1 and Tier2 centres by regular and systematic follow-up of faults and errors with the help of the Savannah bug tracking system. In preparation for data taking the roles of a Computing Run Coordinator and regular computing shifts monitoring the services and infrastructure as well as interfacing to the data operations tasks are being defined. The shift plan until the end of 2008 is being put together. User support worked on documentation and organized several training sessions. The ECoM task force delivered the report on “Use Cases for Start-up of pp Data-Taking” with recommendations and a set of tests to be performed for trigger rates much higher than the ...

  7. COMPUTING

    CERN Multimedia

    P. MacBride

    The Computing Software and Analysis Challenge CSA07 has been the main focus of the Computing Project for the past few months. Activities began over the summer with the preparation of the Monte Carlo data sets for the challenge and tests of the new production system at the Tier-0 at CERN. The pre-challenge Monte Carlo production was done in several steps: physics generation, detector simulation, digitization, conversion to RAW format and the samples were run through the High Level Trigger (HLT). The data was then merged into three "Soups": Chowder (ALPGEN), Stew (Filtered Pythia) and Gumbo (Pythia). The challenge officially started when the first Chowder events were reconstructed on the Tier-0 on October 3rd. The data operations teams were very busy during the the challenge period. The MC production teams continued with signal production and processing while the Tier-0 and Tier-1 teams worked on splitting the Soups into Primary Data Sets (PDS), reconstruction and skimming. The storage sys...

  8. COMPUTING

    CERN Multimedia

    I. Fisk

    2013-01-01

    Computing operation has been lower as the Run 1 samples are completing and smaller samples for upgrades and preparations are ramping up. Much of the computing activity is focusing on preparations for Run 2 and improvements in data access and flexibility of using resources. Operations Office Data processing was slow in the second half of 2013 with only the legacy re-reconstruction pass of 2011 data being processed at the sites.   Figure 1: MC production and processing was more in demand with a peak of over 750 Million GEN-SIM events in a single month.   Figure 2: The transfer system worked reliably and efficiently and transferred on average close to 520 TB per week with peaks at close to 1.2 PB.   Figure 3: The volume of data moved between CMS sites in the last six months   The tape utilisation was a focus for the operation teams with frequent deletion campaigns from deprecated 7 TeV MC GEN-SIM samples to INVALID datasets, which could be cleaned up...

  9. COMPUTING

    CERN Multimedia

    I. Fisk

    2012-01-01

      Introduction Computing activity has been running at a sustained, high rate as we collect data at high luminosity, process simulation, and begin to process the parked data. The system is functional, though a number of improvements are planned during LS1. Many of the changes will impact users, we hope only in positive ways. We are trying to improve the distributed analysis tools as well as the ability to access more data samples more transparently.  Operations Office Figure 2: Number of events per month, for 2012 Since the June CMS Week, Computing Operations teams successfully completed data re-reconstruction passes and finished the CMSSW_53X MC campaign with over three billion events available in AOD format. Recorded data was successfully processed in parallel, exceeding 1.2 billion raw physics events per month for the first time in October 2012 due to the increase in data-parking rate. In parallel, large efforts were dedicated to WMAgent development and integrati...

  10. Illustrative Example of Distributed Analysis in ATLAS Spanish Tier-2 and Tier-3 centers

    CERN Document Server

    Oliver, E; The ATLAS collaboration; González de la Hoz, S; Kaci, M; Lamas, A; Salt, J; Sánchez, J; Villaplana, M

    2011-01-01

    Data taking in ATLAS has been going on for more than one year. The necessity of a computing infrastructure for data storage, access for thousands of users and process of hundreds of million of events has been confirmed in this period. Fortunately, this task has been managed by the GRID infrastructure and the manpower that also has been developing specific GRID tools for the ATLAS community. An example of a physics analysis, searches for the decay of a heavy resonance into a ttbar pair, using this infrastructure is shown. Concretely using the ATLAS Spanish Tier-2 and the IFIC Tier-3. In this moment, the ATLAS Distributed Computing group is working to improve the connectivity among centers in order to be ready for the foreseen increase on the ATLAS activity in the next years.

  11. Baby brain atlases.

    Science.gov (United States)

    Oishi, Kenichi; Chang, Linda; Huang, Hao

    2018-04-03

    The baby brain is constantly changing due to its active neurodevelopment, and research into the baby brain is one of the frontiers in neuroscience. To help guide neuroscientists and clinicians in their investigation of this frontier, maps of the baby brain, which contain a priori knowledge about neurodevelopment and anatomy, are essential. "Brain atlas" in this review refers to a 3D-brain image with a set of reference labels, such as a parcellation map, as the anatomical reference that guides the mapping of the brain. Recent advancements in scanners, sequences, and motion control methodologies enable the creation of various types of high-resolution baby brain atlases. What is becoming clear is that one atlas is not sufficient to characterize the existing knowledge about the anatomical variations, disease-related anatomical alterations, and the variations in time-dependent changes. In this review, the types and roles of the human baby brain MRI atlases that are currently available are described and discussed, and future directions in the field of developmental neuroscience and its clinical applications are proposed. The potential use of disease-based atlases to characterize clinically relevant information, such as clinical labels, in addition to conventional anatomical labels, is also discussed. Copyright © 2018. Published by Elsevier Inc.

  12. ATLAS Review Office

    CERN Multimedia

    Szeless, B

    The ATLAS internal reviews, be it the mandatory Production Readiness Reviews, the now newly installed Production Advancement Reviews, or the more and more requested different Design Reviews, have become a part of our ATLAS culture over the past years. The Activity Systems Status Overviews are, for the time being, a one in time event and should be held for each system as soon as possible to have some meaning. There seems to a consensus that the reviews have become a useful project tool for the ATLAS management but even more so for the sub-systems themselves making achievements as well as possible shortcomings visible. One other recognized byproduct is the increasing cross talk between the systems, a very important ingredient to make profit all the systems from the large collective knowledge we dispose of in ATLAS. In the last two months, the first two PARs were organized for the MDT End Caps and the TRT Barrel Modules, both part of the US contribution to the ATLAS Project. Furthermore several different design...

  13. ATLAS MPGD production status

    CERN Document Server

    Schioppa, Marco; The ATLAS collaboration

    2018-01-01

    Micromegas (MICRO MEsh GAseous Structure) chambers are Micro-Pattern Gaseous Detectors designed to provide a high spatial resolution and reasonable good time resolution in highly irradiated environments. In 2007 an ambitious long-term R\\&D activity was started in the context of the ATLAS experiment, at CERN: the Muon ATLAS Micromegas Activity (MAMMA). After years of tests on prototypes and technology breakthroughs, Micromegas chambers were chosen as tracking detectors for an upgrade of the ATLAS Muon Spectrometer. These novel detectors will be installed in 2020 at the end of the second long shutdown of the Large Hadron Collider, and will serve mainly as precision detectors in the innermost part of the forward ATLAS Muon Spectrometer. Four different types of Micromegas modules, eight layers each, up to $3 m^2$ area (of unprecedented size), will cover a surface of $150 m^2$ for a total active area of about $1200 m^2$. With this upgrade the ATLAS muon system will maintain the full acceptance of its excellent...

  14. ATLAS: Exceeding all expectations

    CERN Multimedia

    CERN Bulletin

    2010-01-01

    “One year ago it would have been impossible for us to guess that the machine and the experiments could achieve so much so quickly”, says Fabiola Gianotti, ATLAS spokesperson. The whole chain – from collision to data analysis – has worked remarkably well in ATLAS.   The first LHC proton run undoubtedly exceeded expectations for the ATLAS experiment. “ATLAS has worked very well since the beginning. Its overall data-taking efficiency is greater than 90%”, says Fabiola Gianotti. “The quality and maturity of the reconstruction and simulation software turned out to be better than we expected for this initial stage of the experiment. The Grid is a great success, and right from the beginning it has allowed members of the collaboration all over the world to participate in the data analysis in an effective and timely manner, and to deliver physics results very quickly”. In just a few months of data taking, ATLAS has observed t...

  15. An ATLAS Virtual Visit connects physicists at the Town Square of Cracow and physicists of the LHC Experiment in the ATLAS control room; special participation of CERN's General Director, Rolf Heuer and the Director for Research and Scientific Computing, Sergio Bertolucci.

    CERN Multimedia

    2012-01-01

    he 12 Festival of Science "Theory-knowledge-experience...". Fest will be located on the traditional Main Square, which is visited by thousands of citizens and tourists. The Institute of Nuclear Physics as usual participates in this annual event. Our visitors will learn the secrets of the CERN experiments on the Large Hadron Collider - ATLAS, LHCb, ALICE, CMS, find out more about the Higgs particles, antimatter quark-gluon plasma (beeing guided by our scientists and PhD students). One of the attractions will be ATLAS Control Room Virtual Visit. Visiting people will have an opportunity to see how ATLAS is controlled and operated to collect its exciting data and ask questions to scientists and engineers involved in LHC program at CERN. Institute of Nuclear Physics has prepared also several interactive demonstrations of Atomic Force Microscopy, Magnetic Resonance, Hadron Therapy and Crystal Physics.

  16. COMPUTING

    CERN Multimedia

    I. Fisk

    2011-01-01

    Introduction The Computing Team successfully completed the storage, initial processing, and distribution for analysis of proton-proton data in 2011. There are still a variety of activities ongoing to support winter conference activities and preparations for 2012. Heavy ions The heavy-ion run for 2011 started in early November and has already demonstrated good machine performance and success of some of the more advanced workflows planned for 2011. Data collection will continue until early December. Facilities and Infrastructure Operations Operational and deployment support for WMAgent and WorkQueue+Request Manager components, routinely used in production by Data Operations, are provided. The GlideInWMS and components installation are now deployed at CERN, which is added to the GlideInWMS factory placed in the US. There has been new operational collaboration between the CERN team and the UCSD GlideIn factory operators, covering each others time zones by monitoring/debugging pilot jobs sent from the facto...

  17. ATLAS Offline Data Quality Monitoring

    CERN Document Server

    Adelman, J; Boelaert, N; D'Onofrio, M; Frost, J A; Guyot, C; Hauschild, M; Hoecker, A; Leney, K J C; Lytken, E; Martinez-Perez, M; Masik, J; Nairz, A M; Onyisi, P U E; Roe, S; Schatzel, S; Schaetzel, S; Wilson, M G

    2010-01-01

    The ATLAS experiment at the Large Hadron Collider reads out 100 Million electronic channels at a rate of 200 Hz. Before the data are shipped to storage and analysis centres across the world, they have to be checked to be free from irregularities which render them scientifically useless. Data quality offline monitoring provides prompt feedback from full first-pass event reconstruction at the Tier-0 computing centre and can unveil problems in the detector hardware and in the data processing chain. Detector information and reconstructed proton-proton collision event characteristics are distilled into a few key histograms and numbers which are automatically compared with a reference. The results of the comparisons are saved as status flags in a database and are published together with the histograms on a web server. They are inspected by a 24/7 shift crew who can notify on-call experts in case of problems and in extreme cases signal data taking abort.

  18. Performance of ATLAS tracking detector

    CERN Document Server

    Lacuesta, V; The ATLAS collaboration

    2012-01-01

    The track and vertex reconstruction algorithms of the ATLAS Inner Detector have demonstrated excellent performance in the early data from the LHC. However, the rapidly increas- ing number of interactions per bunch crossing introduces new challenges both in computational aspects and physics performance. The combination of both silicon and gas based detectors provides high precision impact parameter and momentum measurement of charged particles, with high efficiency and small fake rate. Vertex reconstruction is used to identify with high efficiency the hard scattering process and to measure the amount of pile-up interactions, both aspects are cru- cial for many physics analyses. The performance of track and vertex reconstruction efficiency and resolution achieved in the 2011 and 2012 data-taking period are presented.

  19. ATLAS data sonification : a new interface for musical expression

    CERN Document Server

    Hill, Ewan; The ATLAS collaboration

    2016-01-01

    The goal of this project is to transform ATLAS data into sound and explore how ATLAS audio can be a source of inspiration and education for musicians and for the general public. Real-time ATLAS data is sonified and streamed as music on a dedicated website. Listeners may be motivated to learn more about the ATLAS experiment and composers have the opportunity to explore the physics in the collision data through a new medium. The ATLAS collaboration has shared its expertise and access to the live data stream from which the live event displays are generated. This poster tells the story of a long journey from the hallways of CERN where the project collaboration began to the halls of the Montreux Jazz Festival where harmonies were performed. The mapping of the data to sound will be outlined and interactions with musicians and contributions to conferences dedicated to human-computer interaction will also be discussed. It is a partnership between the ATLAS collaboration and the MIT multimedia lab.

  20. The ATLAS Eventlndex: data flow and inclusion of other metadata

    Science.gov (United States)

    Barberis, D.; Cárdenas Zárate, S. E.; Favareto, A.; Fernandez Casani, A.; Gallas, E. J.; Garcia Montoro, C.; Gonzalez de la Hoz, S.; Hrivnac, J.; Malon, D.; Prokoshin, F.; Salt, J.; Sanchez, J.; Toebbicke, R.; Yuan, R.; ATLAS Collaboration

    2016-10-01

    The ATLAS EventIndex is the catalogue of the event-related metadata for the information collected from the ATLAS detector. The basic unit of this information is the event record, containing the event identification parameters, pointers to the files containing this event as well as trigger decision information. The main use case for the EventIndex is event picking, as well as data consistency checks for large production campaigns. The EventIndex employs the Hadoop platform for data storage and handling, as well as a messaging system for the collection of information. The information for the EventIndex is collected both at Tier-0, when the data are first produced, and from the Grid, when various types of derived data are produced. The EventIndex uses various types of auxiliary information from other ATLAS sources for data collection and processing: trigger tables from the condition metadata database (COMA), dataset information from the data catalogue AMI and the Rucio data management system and information on production jobs from the ATLAS production system. The ATLAS production system is also used for the collection of event information from the Grid jobs. EventIndex developments started in 2012 and in the middle of 2015 the system was commissioned and started collecting event metadata, as a part of ATLAS Distributed Computing operations.

  1. The ATLAS Inner Detector

    CERN Document Server

    Gray, HM; The ATLAS collaboration

    2012-01-01

    The ATLAS experiment at the LHC is equipped with a charged particle tracking system, the Inner Detector, built on three subdetectors, which provide high precision measurements made from a fine detector granularity. The Pixel and microstrip (SCT) subdetectors, which use the silicon technology, are complemented with the Transition Radiation Tracker. Since the LHC startup in 2009, the ATLAS inner tracker has played a central role in many ATLAS physics analyses. Rapid improvements in the calibration and alignment of the detector allowed it to reach nearly the nominal performance in the timespan of a few months. The tracking performance proved to be stable as the LHC luminosity increased by five orders of magnitude during the 2010 proton run, New developments in the offline reconstruction for the 2011 run will improve the tracking performance in high pile-up conditions as well as in highly boosted jets will be discussed.

  2. ATLAS rewards industry

    CERN Multimedia

    2006-01-01

    Showing excellence in mechanics, electronics and cryogenics, three industries are honoured for their contributions to the ATLAS experiment. Representatives of the three award-wining companies after the ceremony. For contributing vital pieces to the ATLAS puzzle, three industries were recognized on Friday 5 May during a supplier awards ceremony. After a welcome and overview of the ATLAS experiment by spokesperson Peter Jenni, CERN Secretary-General Maximilian Metzger stressed the importance of industry to CERN's scientific goals. Close interaction with CERN was a key factor in the selection of each rewarded company, in addition to the high-quality products they delivered to the experiment. Alu Menziken Industrie AG, of Switzerland, was honoured for the production of 380,000 aluminium tubes for the Monitored Drift Tube Chambers (MDT). As Giora Mikenberg, the Muon System Project Leader stressed, the aluminium tubes were delivered on time with an extraordinary quality and precision. Between October 2000 and Jan...

  3. Two ATLAS suppliers honoured

    CERN Multimedia

    2007-01-01

    The ATLAS experiment has recognised the outstanding contribution of two firms to the pixel detector. Recipients of the supplier award with Peter Jenni, ATLAS spokesperson, and Maximilian Metzger, CERN Secretary-General.At a ceremony held at CERN on 28 November, the ATLAS collaboration presented awards to two of its suppliers that had produced sensor wafers for the pixel detector. The CiS Institut für Mikrosensorik of Erfurt in Germany has supplied 655 sensor wafers containing a total of 1652 sensor tiles and the firm ON Semiconductor has supplied 515 sensor wafers (1177 sensor tiles) from its foundry at Roznov in the Czech Republic. Both firms have successfully met the very demanding requirements. ATLAS’s huge pixel detector is very complicated, requiring expertise in highly specialised integrated microelectronics and precision mechanics. Pixel detector project leader Kevin Einsweiler admits that when the project was first propo...

  4. The ATLAS Tau Trigger

    CERN Document Server

    Rados, PK; The ATLAS collaboration

    2014-01-01

    Physics processes involving tau leptons play a crucial role in understanding particle physics at the high energy frontier. The ability to efficiently trigger on events containing hadronic tau decays is therefore of particular importance to the ATLAS experiment. During the 2012 run, the Large Hadronic Collder (LHC) reached instantaneous luminosities of nearly $10^{34} cm^{-2}s^{-1}$ with bunch crossings occurring every $50 ns$. This resulted in a huge event rate and a high probability of overlapping interactions per bunch crossing (pile-up). With this in mind it was necessary to design an ATLAS tau trigger system that could reduce the event rate to a manageable level, while efficiently extracting the most interesting physics events in a pile-up robust manner. In this poster the ATLAS tau trigger is described, its performance during 2012 is presented, and the outlook for the LHC Run II is briefly summarized.

  5. Calorimetry triggering in ATLAS

    CERN Document Server

    Igonkina, O; Adragna, P; Aharrouche, M; Alexandre, G; Andrei, V; Anduaga, X; Aracena, I; Backlund, S; Baines, J; Barnett, B M; Bauss, B; Bee, C; Behera, P; Bell, P; Bendel, M; Benslama, K; Berry, T; Bogaerts, A; Bohm, C; Bold, T; Booth, J R A; Bosman, M; Boyd, J; Bracinik, J; Brawn, I, P; Brelier, B; Brooks, W; Brunet, S; Bucci, F; Casadei, D; Casado, P; Cerri, A; Charlton, D G; Childers, J T; Collins, N J; Conde Muino, P; Coura Torres, R; Cranmer, K; Curtis, C J; Czyczula, Z; Dam, M; Damazio, D; Davis, A O; De Santo, A; Degenhardt, J; Delsart, P A; Demers, S; Demirkoz, B; Di Mattia, A; Diaz, M; Djilkibaev, R; Dobson, E; Dova, M, T; Dufour, M A; Eckweiler, S; Ehrenfeld, W; Eifert, T; Eisenhandler, E; Ellis, N; Emeliyanov, D; Enoque Ferreira de Lima, D; Faulkner, P J W; Ferland, J; Flacher, H; Fleckner, J E; Flowerdew, M; Fonseca-Martin, T; Fratina, S; Fhlisch, F; Gadomski, S; Gallacher, M P; Garitaonandia Elejabarrieta, H; Gee, C N P; George, S; Gillman, A R; Goncalo, R; Grabowska-Bold, I; Groll, M; Gringer, C; Hadley, D R; Haller, J; Hamilton, A; Hanke, P; Hauser, R; Hellman, S; Hidvgi, A; Hillier, S J; Hryn'ova, T; Idarraga, J; Johansen, M; Johns, K; Kalinowski, A; Khoriauli, G; Kirk, J; Klous, S; Kluge, E-E; Koeneke, K; Konoplich, R; Konstantinidis, N; Kwee, R; Landon, M; LeCompte, T; Ledroit, F; Lei, X; Lendermann, V; Lilley, J N; Losada, M; Maettig, S; Mahboubi, K; Mahout, G; Maltrana, D; Marino, C; Masik, J; Meier, K; Middleton, R P; Mincer, A; Moa, T; Monticelli, F; Moreno, D; Morris, J D; Mller, F; Navarro, G A; Negri, A; Nemethy, P; Neusiedl, A; Oltmann, B; Olvito, D; Osuna, C; Padilla, C; Panes, B; Parodi, F; Perera, V J O; Perez, E; Perez Reale, V; Petersen, B; Pinzon, G; Potter, C; Prieur, D P F; Prokishin, F; Qian, W; Quinonez, F; Rajagopalan, S; Reinsch, A; Rieke, S; Riu, I; Robertson, S; Rodriguez, D; Rogriquez, Y; Rhr, F; Saavedra, A; Sankey, D P C; Santamarina, C; Santamarina Rios, C; Scannicchio, D; Schiavi, C; Schmitt, K; Schultz-Coulon, H C; Schfer, U; Segura, E; Silverstein, D; Silverstein, S; Sivoklokov, S; Sjlin, J; Staley, R J; Stamen, R; Stelzer, J; Stockton, M C; Straessner, A; Strom, D; Sushkov, S; Sutton, M; Tamsett, M; Tan, C L A; Tapprogge, S; Thomas, J P; Thompson, P D; Torrence, E; Tripiana, M; Urquijo, P; Urrejola, P; Vachon, B; Vercesi, V; Vorwerk, V; Wang, M; Watkins, P M; Watson, A; Weber, P; Weidberg, T; Werner, P; Wessels, M; Wheeler-Ellis, S; Whiteson, D; Wiedenmann, W; Wielers, M; Wildt, M; Winklmeier, F; Wu, X; Xella, S; Zhao, L; Zobernig, H; de Seixas, J M; dos Anjos, A; Asman, B; Özcan, E

    2009-01-01

    The ATLAS experiment is preparing for data taking at 14 TeV collision energy. A rich discovery physics program is being prepared in addition to the detailed study of Standard Model processes which will be produced in abundance. The ATLAS multi-level trigger system is designed to accept one event in 2 105 to enable the selection of rare and unusual physics events. The ATLAS calorimeter system is a precise instrument, which includes liquid Argon electro-magnetic and hadronic components as well as a scintillator-tile hadronic calorimeter. All these components are used in the various levels of the trigger system. A wide physics coverage is ensured by inclusively selecting events with candidate electrons, photons, taus, jets or those with large missing transverse energy. The commissioning of the trigger system is being performed with cosmic ray events and by replaying simulated Monte Carlo events through the trigger and data acquisition system.

  6. ATLAS TDAQ System Administration:

    CERN Document Server

    Lee, Christopher Jon; The ATLAS collaboration; Bogdanchikov, Alexander; Ballestrero, Sergio; Contescu, Alexandru Cristian; Dubrov, Sergei; Fazio, Daniel; Korol, Aleksandr; Scannicchio, Diana; Twomey, Matthew Shaun; Voronkov, Artem

    2015-01-01

    The ATLAS Trigger and Data Acquisition (TDAQ) system is responsible for the online processing of live data, streaming from the ATLAS experiment at the Large Hadron Collider (LHC) at CERN. The online farm is composed of ̃3000 servers, processing the data readout from ̃100 million detector channels through multiple trigger levels. During the two years of the first Long Shutdown (LS1) there has been a tremendous amount of work done by the ATLAS TDAQ System Administrators, implementing numerous new software applications, upgrading the OS and the hardware, changing some design philosophies and exploiting the High Level Trigger farm with different purposes. During the data taking only critical security updates are applied and broken hardware is replaced to ensure a stable operational environment. The LS1 provided an excellent opportunity to look into new technologies and applications that would help to improve and streamline the daily tasks of not only the System Administrators, but also of the scientists who wil...

  7. Calorimetry triggering in ATLAS

    International Nuclear Information System (INIS)

    Igonkina, O; Achenbach, R; Andrei, V; Adragna, P; Aharrouche, M; Bauss, B; Bendel, M; Alexandre, G; Anduaga, X; Aracena, I; Backlund, S; Bogaerts, A; Baines, J; Barnett, B M; Bee, C; P, Behera; Bell, P; Benslama, K; Berry, T; Bohm, C

    2009-01-01

    The ATLAS experiment is preparing for data taking at 14 TeV collision energy. A rich discovery physics program is being prepared in addition to the detailed study of Standard Model processes which will be produced in abundance. The ATLAS multi-level trigger system is designed to accept one event in 2 | 10 5 to enable the selection of rare and unusual physics events. The ATLAS calorimeter system is a precise instrument, which includes liquid Argon electro-magnetic and hadronic components as well as a scintillator-tile hadronic calorimeter. All these components are used in the various levels of the trigger system. A wide physics coverage is ensured by inclusively selecting events with candidate electrons, photons, taus, jets or those with large missing transverse energy. The commissioning of the trigger system is being performed with cosmic ray events and by replaying simulated Monte Carlo events through the trigger and data acquisition system.

  8. Calorimetry Triggering in ATLAS

    International Nuclear Information System (INIS)

    Igonkina, O.; Achenbach, R.; Adragna, P.; Aharrouche, M.; Alexandre, G.; Andrei, V.; Anduaga, X.; Aracena, I.; Backlund, S.; Baines, J.; Barnett, B.M.; Bauss, B.; Bee, C.; Behera, P.; Bell, P.; Bendel, M.; Benslama, K.; Berry, T.; Bogaerts, A.; Bohm, C.; Bold, T.; Booth, J.R.A.; Bosman, M.; Boyd, J.; Bracinik, J.; Brawn, I.P.; Brelier, B.; Brooks, W.; Brunet, S.; Bucci, F.; Casadei, D.; Casado, P.; Cerri, A.; Charlton, D.G.; Childers, J.T.; Collins, N.J.; Conde Muino, P.; Coura Torres, R.; Cranmer, K.; Curtis, C.J.; Czyczula, Z.; Dam, M.; Damazio, D.; Davis, A.O.; De Santo, A.; Degenhardt, J.

    2011-01-01

    The ATLAS experiment is preparing for data taking at 14 TeV collision energy. A rich discovery physics program is being prepared in addition to the detailed study of Standard Model processes which will be produced in abundance. The ATLAS multi-level trigger system is designed to accept one event in 2/10 5 to enable the selection of rare and unusual physics events. The ATLAS calorimeter system is a precise instrument, which includes liquid Argon electro-magnetic and hadronic components as well as a scintillator-tile hadronic calorimeter. All these components are used in the various levels of the trigger system. A wide physics coverage is ensured by inclusively selecting events with candidate electrons, photons, taus, jets or those with large missing transverse energy. The commissioning of the trigger system is being performed with cosmic ray events and by replaying simulated Monte Carlo events through the trigger and data acquisition system.

  9. Calorimetry triggering in ATLAS

    Energy Technology Data Exchange (ETDEWEB)

    Igonkina, O [Nikhef National Institute for Subatomic Physics, Amsterdam (Netherlands); Achenbach, R; Andrei, V [Kirchhoff Institut fuer Physik, Universitaet Heidelberg, Heidelberg (Germany); Adragna, P [Physics Department, Queen Mary, University of London, London (United Kingdom); Aharrouche, M; Bauss, B; Bendel, M [Institut fr Physik, Universitt Mainz, Mainz (Germany); Alexandre, G [Section de Physique, Universite de Geneve, Geneva (Switzerland); Anduaga, X [Universidad Nacional de La Plata, La Plata (Argentina); Aracena, I [Stanford Linear Accelerator Center (SLAC), Stanford (United States); Backlund, S; Bogaerts, A [European Laboratory for Particle Physics (CERN), Geneva (Switzerland); Baines, J; Barnett, B M [STFC Rutherford Appleton Laboratory, Harwell Science and Innovation Campus, Didcot, Oxon (United Kingdom); Bee, C [Centre de Physique des Particules de Marseille, IN2P3-CNRS, Marseille (France); P, Behera [Iowa State University, Ames, Iowa (United States); Bell, P [School of Physics and Astronomy, University of Manchester, Manchester (United Kingdom); Benslama, K [University of Regina, Regina (Canada); Berry, T [Department of Physics, Royal Holloway and Bedford New College, Egham (United Kingdom); Bohm, C [Fysikum, Stockholm University, Stockholm (Sweden)

    2009-04-01

    The ATLAS experiment is preparing for data taking at 14 TeV collision energy. A rich discovery physics program is being prepared in addition to the detailed study of Standard Model processes which will be produced in abundance. The ATLAS multi-level trigger system is designed to accept one event in 2 | 10{sup 5} to enable the selection of rare and unusual physics events. The ATLAS calorimeter system is a precise instrument, which includes liquid Argon electro-magnetic and hadronic components as well as a scintillator-tile hadronic calorimeter. All these components are used in the various levels of the trigger system. A wide physics coverage is ensured by inclusively selecting events with candidate electrons, photons, taus, jets or those with large missing transverse energy. The commissioning of the trigger system is being performed with cosmic ray events and by replaying simulated Monte Carlo events through the trigger and data acquisition system.

  10. COMPUTING

    CERN Multimedia

    M. Kasemann

    CMS relies on a well functioning, distributed computing infrastructure. The Site Availability Monitoring (SAM) and the Job Robot submission have been very instrumental for site commissioning in order to increase availability of more sites such that they are available to participate in CSA07 and are ready to be used for analysis. The commissioning process has been further developed, including "lessons learned" documentation via the CMS twiki. Recently the visualization, presentation and summarizing of SAM tests for sites has been redesigned, it is now developed by the central ARDA project of WLCG. Work to test the new gLite Workload Management System was performed; a 4 times increase in throughput with respect to LCG Resource Broker is observed. CMS has designed and launched a new-generation traffic load generator called "LoadTest" to commission and to keep exercised all data transfer routes in the CMS PhE-DEx topology. Since mid-February, a transfer volume of about 12 P...

  11. Benefits and performance of ATLAS approaches to utilizing opportunistic resources

    CERN Document Server

    Filip\\v{c}i\\v{c}, Andrej; The ATLAS collaboration

    2016-01-01

    ATLAS has been extensively exploring possibilities of using computing resources extending beyond conventional grid sites in the WLCG fabric to deliver as many computing cycles as possible and thereby enhance the significance of the Monte-Carlo samples to deliver better physics results. The difficulties of using such opportunistic resources come from architectural differences such as unavailability of grid services, the absence of network connectivity on worker nodes or inability to use standard authorization protocols. Nevertheless, ATLAS has been extremely successful in running production payloads on a variety of sites, thanks largely to the job execution workflow design in which the job assignment, input data provisioning and execution steps are clearly separated and can be offloaded to custom services. To transparently include the opportunistic sites in the ATLAS central production system, several models with supporting services have been developed to mimic the functionality of a full WLCG site. Some are e...

  12. Grid site testing for ATLAS with HammerCloud

    International Nuclear Information System (INIS)

    Elmsheuser, J; Hönig, F; Legger, F; LLamas, R Medrano; Sciacca, F G; Ster, D van der

    2014-01-01

    With the exponential growth of LHC (Large Hadron Collider) data in 2012, distributed computing has become the established way to analyze collider data. The ATLAS grid infrastructure includes more than 130 sites worldwide, ranging from large national computing centers to smaller university clusters. HammerCloud was previously introduced with the goals of enabling virtual organisations (VO) and site-administrators to run validation tests of the site and software infrastructure in an automated or on-demand manner. The HammerCloud infrastructure has been constantly improved to support the addition of new test workflows. These new workflows comprise e.g. tests of the ATLAS nightly build system, ATLAS Monte Carlo production system, XRootD federation (FAX) and new site stress test workflows. We report on the development, optimization and results of the various components in the HammerCloud framework.

  13. Grid Site Testing for ATLAS with HammerCloud

    CERN Document Server

    Elmsheuser, J; The ATLAS collaboration; Legger, F; Medrano LLamas, R; Sciacca, G; van der Ster, D

    2014-01-01

    With the exponential growth of LHC (Large Hadron Collider) data in 2012, distributed computing has become the established way to analyze collider data. The ATLAS grid infrastructure includes more than 130 sites worldwide, ranging from large national computing centers to smaller university clusters. HammerCloud was previously introduced with the goals of enabling VO- and site-administrators to run validation tests of the site and software infrastructure in an automated or on-demand manner. The HammerCloud infrastructure has been constantly improved to support the addition of new test work-flows. These new work-flows comprise e.g. tests of the ATLAS nightly build system, ATLAS MC production system, XRootD federation FAX and new site stress test work-flows. We report on the development, optimization and results of the various components in the HammerCloud framework.

  14. Grid Site Testing for ATLAS with HammerCloud

    CERN Document Server

    Elmsheuser, J; The ATLAS collaboration; Legger, F; Medrano LLamas, R; Sciacca, G; van der Ster, D

    2013-01-01

    With the exponential growth of LHC (Large Hadron Collider) data in 2012, distributed computing has become the established way to analyze collider data. The ATLAS grid infrastructure includes more than 130 sites worldwide, ranging from large national computing centers to smaller university clusters. HammerCloud was previously introduced with the goals of enabling VO- and site-administrators to run validation tests of the site and software infrastructure in an automated or on-demand manner. The HammerCloud infrastructure has been constantly improved to support the addition of new test work-flows. These new work-flows comprise e.g. tests of the ATLAS nightly build system, ATLAS MC production system, XRootD federation FAX and new site stress test work-flows. We report on the development, optimization and results of the various components in the HammerCloud framework.

  15. ATLAS Grid Data Processing: system evolution and scalability

    CERN Document Server

    Golubkov, D; The ATLAS collaboration; Klimentov, A; Minaenko, A; Nevski, P; Vaniachine, A; Walker, R

    2012-01-01

    The production system for Grid Data Processing handles petascale ATLAS data reprocessing and Monte Carlo activities. The production system empowered further data processing steps on the Grid performed by dozens of ATLAS physics groups with coordinated access to computing resources worldwide, including additional resources sponsored by regional facilities. The system provides knowledge management of configuration parameters for massive data processing tasks, reproducibility of results, scalable database access, orchestrated workflow and performance monitoring, dynamic workload sharing, automated fault tolerance and petascale data integrity control. The system evolves to accommodate a growing number of users and new requirements from our contacts in ATLAS main areas: Trigger, Physics, Data Preparation and Software & Computing. To assure scalability, the next generation production system architecture development is in progress. We report on scaling up the production system for a growing number of users provi...

  16. Rate Predictions and Trigger/DAQ Resource Monitoring in ATLAS

    CERN Document Server

    Schaefer, D M; The ATLAS collaboration

    2012-01-01

    Since starting in 2010, the Large Hadron Collider (LHC) has pro- duced collisions at an ever increasing rate. The ATLAS experiment successfully records the collision data with high eciency and excel- lent data quality. Events are selected using a three-level trigger system, where each level makes a more re ned selection. The level-1 trigger (L1) consists of a custom-designed hardware trigger which seeds two higher software based trigger levels. Over 300 triggers compose a trig- ger menu which selects physics signatures such as electrons, muons, particle jets, etc. Each trigger consumes computing resources of the ATLAS trigger system and oine storage. The LHC instantaneous luminosity conditions, desired physics goals of the collaboration, and the limits of the trigger infrastructure determine the composition of the ATLAS trigger menu. We describe a trigger monitoring frame- work for computing the costs of individual trigger algorithms such as data request rates and CPU consumption. This framework has been used...

  17. Evolution of User Analysis on the Grid in ATLAS

    CERN Document Server

    Legger, Federica; The ATLAS collaboration

    2016-01-01

    More than one thousand physicists analyse data collected by the ATLAS experiment at the Large Hadron Collider (LHC) at CERN through 150 computing facilities around the world. Efficient distributed analysis requires optimal resource usage and the interplay of several factors: robust grid and software infrastructures, system capability to adapt to different workloads. The continuous automatic validation of grid sites and the user support provided by a dedicated team of expert shifters have been proven to provide a solid distributed analysis system for ATLAS users. Based on the experience from the first run of the LHC, substantial improvements to the ATLAS computing system have been made to optimize both production and analysis workflows. These include the re-design of the production and data management systems, a new analysis data format and event model, and the development of common reduction and analysis frameworks. The impact of such changes on the distributed analysis system is evaluated. More than 100 mill...

  18. Bone age assessment in Hispanic children: digital hand atlas compared with the Greulich and Pyle (G&P) atlas

    Science.gov (United States)

    Fernandez, James Reza; Zhang, Aifeng; Vachon, Linda; Tsao, Sinchai

    2008-03-01

    Bone age assessment is most commonly performed with the use of the Greulich and Pyle (G&P) book atlas, which was developed in the 1950s. The population of theUnited States is not as homogenous as the Caucasian population in the Greulich and Pyle in the 1950s, especially in the Los Angeles, California area. A digital hand atlas (DHA) based on 1,390 hand images of children of different racial backgrounds (Caucasian, African American, Hispanic, and Asian) aged 0-18 years was collected from Children's Hospital Los Angeles. Statistical analysis discovered significant discrepancies exist between Hispanic and the G&P atlas standard. To validate the usage of DHA as a clinical standard, diagnostic radiologists performed reads on Hispanic pediatric hand and wrist computed radiography images using either the G&P pediatric radiographic atlas or the Children's Hospital Los Angeles Digital Hand Atlas (DHA) as reference. The order in which the atlas is used (G&P followed by DHA or vice versa) for each image was prepared before actual reading begins. Statistical analysis of the results was then performed to determine if a discrepancy exists between the two readings.

  19. Atlas of Yellowstone

    Science.gov (United States)

    Pierce, Kenneth L.; Marcus, A. W.; Meachan, J. E.; Rodman, A. W.; Steingisser, A. Y.; Allan, Stuart; West, Ross

    2012-01-01

    Established in 1872, Yellowstone National Park was the world’s first national park. In a fitting tribute to this diverse and beautiful region, the Atlas of Yellowstone is a compelling visual guide to this unique national park and its surrounding area. Ranging from art to wolves, from American Indians to the Yellowstone Volcano, and from geysers to population, each page explains something new about the dynamic forces shaping Yellowstone. Equal parts reference and travel guide, the Atlas of Yellowstone is an unsurpassed resource.

  20. LUCID in ATLAS

    CERN Document Server

    Groth-Jensen, J; The ATLAS collaboration

    2009-01-01

    This talk is to be given at the workshop DIFF2010 : Diffractive and electromagnetic processes at the LHC , early January next year. The aim of the talk is to give a overview/status update of the LUCID detector in ATLAS. As such the presentation will be focused on the design and current layout of the detector - with emphasis on the hardware side. The first few slides will be used to give an overview of the location, design and layout LUCID with respect to ATLAS. Afterwards some hardware issues will be address and finally some results from first LHC data will be shown.

  1. ATLAS Forward Proton Detector

    CERN Document Server

    Grieco, Chiara; The ATLAS collaboration

    2018-01-01

    The aim of the ATLAS Forward Proton (AFP) detector system is the measurement of protons scattered diffractively or electromagnetically at very small angles. The full two-arm setup was installed during the 2016/2017 EYETS. This allows measurements of processes with two forward protons: central diffraction, exclusive production, and two-photon processes. In 2017, AFP participated in the ATLAS high-luminosity data taking on the day-by-day basis. In addition, several special runs with reduced luminosity were taken. The poster will present the AFP detectors and the lessons learned from the last year operation and some performance from 2016 and 2017.

  2. The Herschel ATLAS

    Science.gov (United States)

    Eales, S.; Dunne, L.; Clements, D.; Cooray, A.; De Zotti, G.; Dye, S.; Ivison, R.; Jarvis, M.; Lagache, G.; Maddox, S.; hide

    2010-01-01

    The Herschel ATLAS is the largest open-time key project that will be carried out on the Herschel Space Observatory. It will survey 570 sq deg of the extragalactic sky, 4 times larger than all the other Herschel extragalactic surveys combined, in five far-infrared and submillimeter bands. We describe the survey, the complementary multiwavelength data sets that will be combined with the Herschel data, and the six major science programs we are undertaking. Using new models based on a previous submillimeter survey of galaxies, we present predictions of the properties of the ATLAS sources in other wave bands.

  3. Data intensive ATLAS workflows in the Cloud

    CERN Document Server

    Rzehorz, Gerhard Ferdinand; The ATLAS collaboration

    2018-01-01

    From 2025 onwards, the ATLAS collaboration at the Large Hadron Collider (LHC) at CERN will experience a massive increase in data quantity as well as complexity. Including mitigating factors, the prevalent computing power by that time will only fulfil one tenth of the requirement. This contribution will focus on Cloud computing as an approach to help overcome this challenge by providing flexible hardware that can be configured to the specific needs of a workflow. Experience with Cloud computing exists, but there is a large uncertainty if and to which degree it can be able to reduce the burden by 2025. In order to understand and quantify the benefits of Cloud computing, the "Workflow and Infrastructure Model" was created. It estimates the viability of Cloud computing by combining different inputs from the workflow side with infrastructure specifications. The model delivers metrics that enable the comparison of different Cloud configurations as well as different Cloud offerings with each other. A wide range of r...

  4. The ATLAS Data Management Software Engineering Process

    CERN Document Server

    Lassnig, M; The ATLAS collaboration; Stewart, G A; Barisits, M; Beermann, T; Vigne, R; Serfon, C; Goossens, L; Nairz, A; Molfetas, A

    2014-01-01

    Rucio is the next-generation data management system of the ATLAS experiment. The software engineering process to develop Rucio is fundamentally different to existing software development approaches in the ATLAS distributed computing community. Based on a conceptual design document, development takes place using peer-reviewed code in a test-driven environment. The main objectives are to ensure that every engineer understands the details of the full project, even components usually not touched by them, that the design and architecture are coherent, that temporary contributors can be productive without delay, that programming mistakes are prevented before being committed to the source code, and that the source is always in a fully functioning state. This contribution will illustrate the workflows and products used, and demonstrate the typical development cycle of a component from inception to deployment within this software engineering process. Next to the technological advantages, this contribution will also hi...

  5. The ATLAS Data Management Software Engineering Process

    CERN Document Server

    Lassnig, M; The ATLAS collaboration; Stewart, G A; Barisits, M; Beermann, T; Vigne, R; Serfon, C; Goossens, L; Nairz, A

    2013-01-01

    Rucio is the next-generation data management system of the ATLAS experiment. The software engineering process to develop Rucio is fundamentally different to existing software development approaches in the ATLAS distributed computing community. Based on a conceptual design document, development takes place using peer-reviewed code in a test-driven environment. The main objectives are to ensure that every engineer understands the details of the full project, even components usually not touched by them, that the design and architecture are coherent, that temporary contributors can be productive without delay, that programming mistakes are prevented before being committed to the source code, and that the source is always in a fully functioning state. This contribution will illustrate the workflows and products used, and demonstrate the typical development cycle of a component from inception to deployment within this software engineering process. Next to the technological advantages, this contribution will also hi...

  6. Status of the ATLAS control system upgrade

    International Nuclear Information System (INIS)

    Munson, F.H.; Ferraretto, M.; Rutherford, B.

    1992-01-01

    Certain components of the ATLAS control system are two generations behind today's technology. It has been decided to upgrade the control system. in part, by replacing Digital Equipment Corporation (DEC) PDP-11 computers with present-day VAX technology. Two primary goals have been defined for the upgraded control system. The first of these goals is to keep additional ''in-house'' written software to a minimum, while providing the portability necessary to ensure the continued use of existing software. In an attempt to achieve this goal, commercially-available software has been utilized to provide a foundation for the final control-system configuration. The second goal is to develop the new control system, while not interfering with accelerator operations. This paper describes some of the motivation for upgrading the ATLAS control system, the basic features of the new control system, and the present status of the system's development

  7. ATLAS Transition Radiation Tracker - large piece

    CERN Multimedia

    2006-01-01

    The ATLAS transition radiation tracker is made of 300'000 straw tubes, up to 144cm long. Filled with a gas mixture and threaded with a wire, each straw is a complete mini-detector in its own right. An electric field is applied between the wire and the outside wall of the straw. As particles pass through, they collide with atoms in the gas, knocking out electrons. The avalanche of electrons is detected as an electrical signal on the wire in the centre. The tracker plays two important roles. Firstly, it makes more position measurements, giving more dots for the computers to join up to recreate the particle tracks. Also, together with the ATLAS calorimeters, it distinguishes between different types of particles depending on whether they emit radiation as they make the transition from the surrounding foil into the straws.

  8. Test Management Framework for the ATLAS Experiment

    CERN Document Server

    Kazarov, Andrei; The ATLAS collaboration; Avolio, Giuseppe

    2018-01-01

    Test Management Framework for the Data Acquisition of the ATLAS Experiment Data Acquisition (DAQ) of the ATLAS experiment is a large distributed and inhomogeneous system: it consists of thousands of interconnected computers and electronics devices that operate coherently to read out and select relevant physics data. Advanced diagnostics capabilities of the TDAQ control system are a crucial feature which contributes significantly to smooth operation and fast recovery in case of the problems and, finally, to the high efficiency of the whole experiment. The base layer of the verification and diagnostic functionality is a test management framework. We have developed a flexible test management system that allows the experts to define and configure tests for different components, indicate follow-up actions to test failures and describe inter-dependencies between DAQ or detector elements. This development is based on the experience gained with the previous test system that was used during the first three years of th...

  9. Recently Published Lectures and Tutorials for ATLAS

    CERN Multimedia

    J. Herr

    2006-01-01

    As reported in the September 2004 ATLAS eNews, the Web Lecture Archive Project, a collaboration between the University of Michigan and CERN, has developed a synchronized system for recording and publishing educational multimedia presentations, using the Web as medium. The current system, including future developments for the project and the field in general, was recently presented at the CHEP 2006 conference in Mumbai, India. The relevant presentations and papers can be found here: The Web Lecture Archive Project A Web Lecture Capture System with Robotic Speaker Tracking This year, the University of Michigan team has been asked to record and publish all ATLAS Plenary sessions, as well as a large number of Physics and Computing tutorials. A significant amount of this material has already been published and can be accessed via the links below. All lectures can be viewed on any major platform with any common internet browser, either via streaming or local download (for limited bandwidth). Please enjoy the l...

  10. Recently Published Lectures and Tutorials for ATLAS

    CERN Multimedia

    Goldfarb, S.

    2006-01-01

    As reported in the September 2004 ATLAS eNews, the Web Lecture Archive Project, WLAP, a collaboration between the University of Michigan and CERN, has developed a synchronized system for recording and publishing educational multimedia presentations, using the Web as medium. The current system, including future developments for the project and the field in general, was recently presented at the CHEP 2006 conference in Mumbai, India. The relevant presentations and papers can be found here: The Web Lecture Archive Project. A Web Lecture Capture System with Robotic Speaker Tracking This year, the University of Michigan team has been asked to record and publish all ATLAS Plenary sessions, as well as a large number of Physics and Computing tutorials. A significant amount of this material has already been published and can be accessed via the links below. All lectures can be viewed on any major platform with any common internet browser, either via streaming or local download (for limited bandwidth). Please e...

  11. ATLAS Transition Radiation Tracker - small piece

    CERN Multimedia

    2006-01-01

    The ATLAS transition radiation tracker is made of 300'000 straw tubes, up to 144cm long. Filled with a gas mixture and threaded with a wire, each straw is a complete mini-detector in its own right. An electric field is applied between the wire and the outside wall of the straw. As particles pass through, they collide with atoms in the gas, knocking out electrons. The avalanche of electrons is detected as an electrical signal on the wire in the centre. The tracker plays two important roles. Firstly, it makes more position measurements, giving more dots for the computers to join up to recreate the particle tracks. Also, together with the ATLAS calorimeters, it distinguishes between different types of particles depending on whether they emit radiation as they make the transition from the surrounding foil into the straws.

  12. The ATLAS Distributed Data Management System & Databases

    CERN Document Server

    Garonne, V; The ATLAS collaboration; Barisits, M; Beermann, T; Vigne, R; Serfon, C

    2013-01-01

    The ATLAS Distributed Data Management (DDM) System is responsible for the global management of petabytes of high energy physics data. The current system, DQ2, has a critical dependency on Relational Database Management Systems (RDBMS), like Oracle. RDBMS are well-suited to enforcing data integrity in online transaction processing applications, however, concerns have been raised about the scalability of its data warehouse-like workload. In particular, analysis of archived data or aggregation of transactional data for summary purposes is problematic. Therefore, we have evaluated new approaches to handle vast amounts of data. We have investigated a class of database technologies commonly referred to as NoSQL databases. This includes distributed filesystems, like HDFS, that support parallel execution of computational tasks on distributed data, as well as schema-less approaches via key-value stores, like HBase. In this talk we will describe our use cases in ATLAS, share our experiences with various databases used ...

  13. An integrated overview of metadata in ATLAS

    International Nuclear Information System (INIS)

    Gallas, E J; Malon, D; Hawkings, R J; Albrand, S; Torrence, E

    2010-01-01

    Metadata (data about data) arise in many contexts, from many diverse sources, and at many levels in ATLAS. Familiar examples include run-level, luminosity-block-level, and event-level metadata, and, related to processing and organization, dataset-level and file-level metadata, but these categories are neither exhaustive nor orthogonal. Some metadata are known a priori, in advance of data taking or simulation; other metadata are known only after processing, and occasionally, quite late (e.g., detector status or quality updates that may appear after initial reconstruction is complete). Metadata that may seem relevant only internally to the distributed computing infrastructure under ordinary conditions may become relevant to physics analysis under error conditions ('What can I discover about data I failed to process?'). This talk provides an overview of metadata and metadata handling in ATLAS, and describes ongoing work to deliver integrated metadata services in support of physics analysis.

  14. Using containers with ATLAS offline software

    CERN Document Server

    Vogel, Marcelo; The ATLAS collaboration; Heinrich, Lukas; Stewart, Graeme

    2017-01-01

    Title: Using containers with ATLAS offline software Marcelo Vogel, Bergische Universitaet Wuppertal Graeme Stewart, University of Glasgow Johannes Elmsheuser, Brookhaven National Laboratory Lukas Heinrich, New York University Abstract: This paper describes the deployment of ATLAS offline software in containers for software development and the use in production jobs on the grid - such as event generation, simulation, reconstruction and physics derivations - and in physics analysis. For this we are using Docker and Singularity which are both lightweight virtualization technologies to encapsulates a piece of software inside a complete file system. The deployment of offline releases via containers removes the interdependence between the runtime environment needed for job execution and the configuration of a computing site’s worker nodes. Once the two are decoupled from each other, sites can upgrade their nodes whenever and however they see fit. Docker or Singularity will provide a uniform runtime environment fo...

  15. Multi-threaded ATLAS simulation on Intel Knights Landing processors

    Science.gov (United States)

    Farrell, Steven; Calafiura, Paolo; Leggett, Charles; Tsulaia, Vakhtang; Dotti, Andrea; ATLAS Collaboration

    2017-10-01

    The Knights Landing (KNL) release of the Intel Many Integrated Core (MIC) Xeon Phi line of processors is a potential game changer for HEP computing. With 72 cores and deep vector registers, the KNL cards promise significant performance benefits for highly-parallel, compute-heavy applications. Cori, the newest supercomputer at the National Energy Research Scientific Computing Center (NERSC), was delivered to its users in two phases with the first phase online at the end of 2015 and the second phase now online at the end of 2016. Cori Phase 2 is based on the KNL architecture and contains over 9000 compute nodes with 96GB DDR4 memory. ATLAS simulation with the multithreaded Athena Framework (AthenaMT) is a good potential use-case for the KNL architecture and supercomputers like Cori. ATLAS simulation jobs have a high ratio of CPU computation to disk I/O and have been shown to scale well in multi-threading and across many nodes. In this paper we will give an overview of the ATLAS simulation application with details on its multi-threaded design. Then, we will present a performance analysis of the application on KNL devices and compare it to a traditional x86 platform to demonstrate the capabilities of the architecture and evaluate the benefits of utilizing KNL platforms like Cori for ATLAS production.

  16. Multiple brain atlas database and atlas-based neuroimaging system.

    Science.gov (United States)

    Nowinski, W L; Fang, A; Nguyen, B T; Raphel, J K; Jagannathan, L; Raghavan, R; Bryan, R N; Miller, G A

    1997-01-01

    For the purpose of developing multiple, complementary, fully labeled electronic brain atlases and an atlas-based neuroimaging system for analysis, quantification, and real-time manipulation of cerebral structures in two and three dimensions, we have digitized, enhanced, segmented, and labeled the following print brain atlases: Co-Planar Stereotaxic Atlas of the Human Brain by Talairach and Tournoux, Atlas for Stereotaxy of the Human Brain by Schaltenbrand and Wahren, Referentially Oriented Cerebral MRI Anatomy by Talairach and Tournoux, and Atlas of the Cerebral Sulci by Ono, Kubik, and Abernathey. Three-dimensional extensions of these atlases have been developed as well. All two- and three-dimensional atlases are mutually preregistered and may be interactively registered with an actual patient's data. An atlas-based neuroimaging system has been developed that provides support for reformatting, registration, visualization, navigation, image processing, and quantification of clinical data. The anatomical index contains about 1,000 structures and over 400 sulcal patterns. Several new applications of the brain atlas database also have been developed, supported by various technologies such as virtual reality, the Internet, and electronic publishing. Fusion of information from multiple atlases assists the user in comprehensively understanding brain structures and identifying and quantifying anatomical regions in clinical data. The multiple brain atlas database and atlas-based neuroimaging system have substantial potential impact in stereotactic neurosurgery and radiotherapy by assisting in visualization and real-time manipulation in three dimensions of anatomical structures, in quantitative neuroradiology by allowing interactive analysis of clinical data, in three-dimensional neuroeducation, and in brain function studies.

  17. TU-AB-BRA-02: An Efficient Atlas-Based Synthetic CT Generation Method

    International Nuclear Information System (INIS)

    Han, X

    2016-01-01

    Purpose: A major obstacle for MR-only radiotherapy is the need to generate an accurate synthetic CT (sCT) from MR image(s) of a patient for the purposes of dose calculation and DRR generation. We propose here an accurate and efficient atlas-based sCT generation method, which has a computation speed largely independent of the number of atlases used. Methods: Atlas-based sCT generation requires a set of atlases with co-registered CT and MR images. Unlike existing methods that align each atlas to the new patient independently, we first create an average atlas and pre-align every atlas to the average atlas space. When a new patient arrives, we compute only one deformable image registration to align the patient MR image to the average atlas, which indirectly aligns the patient to all pre-aligned atlases. A patch-based non-local weighted fusion is performed in the average atlas space to generate the sCT for the patient, which is then warped back to the original patient space. We further adapt a PatchMatch algorithm that can quickly find top matches between patches of the patient image and all atlas images, which makes the patch fusion step also independent of the number of atlases used. Results: Nineteen brain tumour patients with both CT and T1-weighted MR images are used as testing data and a leave-one-out validation is performed. Each sCT generated is compared against the original CT image of the same patient on a voxel-by-voxel basis. The proposed method produces a mean absolute error (MAE) of 98.6±26.9 HU overall. The accuracy is comparable with a conventional implementation scheme, but the computation time is reduced from over an hour to four minutes. Conclusion: An average atlas space patch fusion approach can produce highly accurate sCT estimations very efficiently. Further validation on dose computation accuracy and using a larger patient cohort is warranted. The author is a full time employee of Elekta, Inc.

  18. Overview of ATLAS PanDA Workload Management

    Science.gov (United States)

    Maeno, T.; De, K.; Wenaus, T.; Nilsson, P.; Stewart, G. A.; Walker, R.; Stradling, A.; Caballero, J.; Potekhin, M.; Smith, D.; ATLAS Collaboration

    2011-12-01

    The Production and Distributed Analysis System (PanDA) plays a key role in the ATLAS distributed computing infrastructure. All ATLAS Monte-Carlo simulation and data reprocessing jobs pass through the PanDA system. We will describe how PanDA manages job execution on the grid using dynamic resource estimation and data replication together with intelligent brokerage in order to meet the scaling and automation requirements of ATLAS distributed computing. PanDA is also the primary ATLAS system for processing user and group analysis jobs, bringing further requirements for quick, flexible adaptation to the rapidly evolving analysis use cases of the early datataking phase, in addition to the high reliability, robustness and usability needed to provide efficient and transparent utilization of the grid for analysis users. We will describe how PanDA meets ATLAS requirements, the evolution of the system in light of operational experience, how the system has performed during the first LHC data-taking phase and plans for the future.

  19. Overview of ATLAS PanDA Workload Management

    International Nuclear Information System (INIS)

    Maeno, T.; De, K.; Wenaus, T.; Nilsson, P.; Stewart, G.A.; Walker, R.; Stradling, A.; Caballero, J.; Potekhin, M.; Smith, D.

    2011-01-01

    The Production and Distributed Analysis System (PanDA) plays a key role in the ATLAS distributed computing infrastructure. All ATLAS Monte-Carlo simulation and data reprocessing jobs pass through the PanDA system. We will describe how PanDA manages job execution on the grid using dynamic resource estimation and data replication together with intelligent brokerage in order to meet the scaling and automation requirements of ATLAS distributed computing. PanDA is also the primary ATLAS system for processing user and group analysis jobs, bringing further requirements for quick, flexible adaptation to the rapidly evolving analysis use cases of the early datataking phase, in addition to the high reliability, robustness and usability needed to provide efficient and transparent utilization of the grid for analysis users. We will describe how PanDA meets ATLAS requirements, the evolution of the system in light of operational experience, how the system has performed during the first LHC data-taking phase and plans for the future.

  20. The observer's sky atlas

    CERN Document Server

    Karkoschka, E

    2007-01-01

    This title includes a short introduction to observing, a thorough description of the star charts and tables, a glossary and much more. It is perfect for both the beginner and seasoned observer. It is fully revised edition of a best-selling and highly-praised sky atlas.

  1. ATLAS solenoid operates underground

    CERN Multimedia

    2006-01-01

    A new phase for the ATLAS collaboration started with the first operation of a completed sub-system: the Central Solenoid. Teams monitoring the cooling and powering of the ATLAS solenoid in the control room. The solenoid was cooled down to 4.5 K from 17 to 23 May. The first current was established the same evening that the solenoid became cold and superconductive. 'This makes the ATLAS Central Solenoid the very first cold and superconducting magnet to be operated in the LHC underground areas!', said Takahiko Kondo, professor at KEK. Though the current was limited to 1 kA, the cool-down and powering of the solenoid was a major milestone for all of the control, cryogenic, power and vacuum systems-a milestone reached by the hard work and many long evenings invested by various teams from ATLAS, all of CERN's departments and several large and small companies. Since the Central Solenoid and the barrel liquid argon (LAr) calorimeter share the same cryostat vacuum vessel, this achievement was only possible in perfe...

  2. The ATLAS event filter

    CERN Document Server

    Beck, H P; Boissat, C; Davis, R; Duval, P Y; Etienne, F; Fede, E; Francis, D; Green, P; Hemmer, F; Jones, R; MacKinnon, J; Mapelli, Livio P; Meessen, C; Mommsen, R K; Mornacchi, Giuseppe; Nacasch, R; Negri, A; Pinfold, James L; Polesello, G; Qian, Z; Rafflin, C; Scannicchio, D A; Stanescu, C; Touchard, F; Vercesi, V

    1999-01-01

    An overview of the studies for the ATLAS Event Filter is given. The architecture and the high level design of the DAQ-1 prototype is presented. The current status if the prototypes is briefly given. Finally, future plans and milestones are given. (11 refs).

  3. Tema-atlas

    DEFF Research Database (Denmark)

    Jensen, Ole Michael; Olsen, S.

    I dette tema-atlas viser forskere på By og Byg, hvordan registre over befolkning, bygninger og forbrug kan overføres til kort ved hjælp af GIS-teknologi. Atlasset er samtidig en illustration af de muligheder, som tegner sig i kommunerne for at udnytte eksisterende registre i forbindelse med...

  4. Taus at ATLAS

    Energy Technology Data Exchange (ETDEWEB)

    Demers, Sarah M. [Yale Univ., New Haven, CT (United States). Dept. of Physics

    2017-12-06

    The grant "Taus at ATLAS" supported the group of Sarah Demers at Yale University over a period of 8.5 months, bridging the time between her Early Career Award and her inclusion on Yale's grant cycle within the Department of Energy's Office of Science. The work supported the functioning of the ATLAS Experiment at CERN's Large Hadron Collider and the analysis of ATLAS data. The work included searching for the Higgs Boson in a particular mode of its production (with a W or Z boson) and decay (to a pair of tau leptons.) This was part of a broad program of characterizing the Higgs boson as we try to understand this recently discovered particle, and whether or not it matches our expectations within the current standard model of particle physics. In addition, group members worked with simulation to understand the physics reach of planned upgrades to the ATLAS experiment. Supported group members include postdoctoral researcher Lotte Thomsen and graduate student Mariel Pettee.

  5. ATLAS Experiment Brochure - French

    CERN Multimedia

    2018-01-01

    ATLAS is one of the four major experiments at the Large Hadron Collider at CERN. It is a general-purpose particle physics experiment run by an international collaboration, and is designed to exploit the full discovery potential and the huge range of physics opportunities that the LHC provides.

  6. ATLAS Experiment Brochure - Turkish

    CERN Multimedia

    AUTHOR|(CDS)2081027

    2018-01-01

    ATLAS is one of the four major experiments at the Large Hadron Collider at CERN. It is a general-purpose particle physics experiment run by an international collaboration, and is designed to exploit the full discovery potential and the huge range of physics opportunities that the LHC provides.

  7. ATLAS Experiment Brochure - Hebrew

    CERN Multimedia

    AUTHOR|(CDS)2081027

    2018-01-01

    ATLAS is one of the four major experiments at the Large Hadron Collider at CERN. It is a general-purpose particle physics experiment run by an international collaboration, and is designed to exploit the full discovery potential and the huge range of physics opportunities that the LHC provides.

  8. ATLAS Experiment Brochure - Italian

    CERN Multimedia

    2018-01-01

    ATLAS is one of the four major experiments at the Large Hadron Collider at CERN. It is a general-purpose particle physics experiment run by an international collaboration, and is designed to exploit the full discovery potential and the huge range of physics opportunities that the LHC provides.

  9. ATLAS Experiment Brochure - German

    CERN Multimedia

    AUTHOR|(CDS)2081027

    2018-01-01

    ATLAS is one of the four major experiments at the Large Hadron Collider at CERN. It is a general-purpose particle physics experiment run by an international collaboration, and is designed to exploit the full discovery potential and the huge range of physics opportunities that the LHC provides.

  10. ATLAS Experiment Brochure - Japanese

    CERN Multimedia

    Anthony, Katarina

    2018-01-01

    ATLAS is one of the four major experiments at the Large Hadron Collider at CERN. It is a general-purpose particle physics experiment run by an international collaboration, and is designed to exploit the full discovery potential and the huge range of physics opportunities that the LHC provides.

  11. ATLAS Experiment Brochure - Portuguese

    CERN Multimedia

    AUTHOR|(CDS)2081027

    2018-01-01

    ATLAS is one of the four major experiments at the Large Hadron Collider at CERN. It is a general-purpose particle physics experiment run by an international collaboration, and is designed to exploit the full discovery potential and the huge range of physics opportunities that the LHC provides.

  12. ATLAS Experiment Brochure - Czech

    CERN Multimedia

    AUTHOR|(CDS)2081027

    2018-01-01

    ATLAS is one of the four major experiments at the Large Hadron Collider at CERN. It is a general-purpose particle physics experiment run by an international collaboration, and is designed to exploit the full discovery potential and the huge range of physics opportunities that the LHC provides.

  13. ATLAS Experiment Brochure - Dutch

    CERN Multimedia

    AUTHOR|(CDS)2081027

    2018-01-01

    ATLAS is one of the four major experiments at the Large Hadron Collider at CERN. It is a general-purpose particle physics experiment run by an international collaboration, and is designed to exploit the full discovery potential and the huge range of physics opportunities that the LHC provides.

  14. ATLAS Experiment Brochure - Romanian

    CERN Multimedia

    AUTHOR|(CDS)2081027

    2018-01-01

    ATLAS is one of the four major experiments at the Large Hadron Collider at CERN. It is a general-purpose particle physics experiment run by an international collaboration, and is designed to exploit the full discovery potential and the huge range of physics opportunities that the LHC provides.

  15. ATLAS Experiment Brochure - Serbian

    CERN Multimedia

    2018-01-01

    ATLAS is one of the four major experiments at the Large Hadron Collider at CERN. It is a general-purpose particle physics experiment run by an international collaboration, and is designed to exploit the full discovery potential and the huge range of physics opportunities that the LHC provides.

  16. ATLAS Pixel Detector Upgrade

    CERN Document Server

    Flick, T; The ATLAS collaboration

    2009-01-01

    The first upgrade for higher luminosity at LHC for the ATLAS pixel detector is the insertion of a forth layer, the IBL. The talk gives an overview about what the IBL is and how it will be set up, as well as to give a status of the research and develoment work.

  17. Prime wires for ATLAS

    CERN Multimedia

    2003-01-01

    In an award ceremony on 3 September, ATLAS honoured the French company Axon Cable for its special coaxial cables, which were purpose-built for the Liquid Argon calorimeter modules. Working for CERN since the 1970s, Axon' Cable received the ATLAS supplier award last week for its contribution to the liquid argon calorimeter cables of ATLAS (LAL/Orsay, France and University of Victoria, Canada), started in 1996. Its two sets of minicoaxial cables, called harnesses "A" and "B", are designed to function in the harsh conditions in the liquid argon (at 90 Kelvin or -183°C) and under extreme radiation (up to several Mrads). The cables are mainly used for the readout of the calorimeters, and are connected to the outside world by 114 signal feedthroughs with 1920 channels each. The signal from the detectors is transmitted directly without any amplification, which imposes tight restrictions on the impedance and on the signal propagation time of the cables. Peter Jenni, ATLAS spokesperson, gives the award for best s...

  18. ATLAS Detector Upgrade Prospects

    International Nuclear Information System (INIS)

    Dobre, M

    2017-01-01

    After the successful operation at the centre-of-mass energies of 7 and 8 TeV in 2010-2012, the LHC was ramped up and successfully took data at the centre-of-mass energies of 13 TeV in 2015 and 2016. Meanwhile, plans are actively advancing for a series of upgrades of the accelerator, culminating roughly ten years from now in the high-luminosity LHC (HL-LHC) project, which will deliver of the order of five times the LHC nominal instantaneous luminosity along with luminosity levelling. The ultimate goal is to extend the dataset from about few hundred fb −1 expected for LHC running by the end of 2018 to 3000 fb −1 by around 2035 for ATLAS and CMS. The challenge of coping with the HL-LHC instantaneous and integrated luminosity, along with the associated radiation levels, requires further major changes to the ATLAS detector. The designs are developing rapidly for a new all-silicon tracker, significant upgrades of the calorimeter and muon systems, as well as improved triggers and data acquisition. ATLAS is also examining potential benefits of extensions to larger pseudorapidity, particularly in tracking and muon systems. This report summarizes various improvements to the ATLAS detector required to cope with the anticipated evolution of the LHC luminosity during this decade and the next. A brief overview is also given on physics prospects with a pp centre-of-mass energy of 14 TeV. (paper)

  19. ATLAS Experiment Brochure

    CERN Multimedia

    AUTHOR|(INSPIRE)INSPIRE-00085461

    2016-01-01

    ATLAS is one of the four major experiments at the Large Hadron Collider at CERN. It is a general-purpose particle physics experiment run by an international collaboration, and is designed to exploit the full discovery potential and the huge range of physics opportunities that the LHC provides.

  20. ATLAS starts moving in

    CERN Multimedia

    2004-01-01

    The first large active detector component was lowered into the ATLAS cavern on 1 March. It consisted of the 8 modules forming the lower part of the central barrel of the tile hadronic calorimeter. The work of assembling the barrel, which comprises 64 modules, started the following day.

  1. A thermosiphon for ATLAS

    CERN Multimedia

    Rosaria Marraffino

    2013-01-01

    A new thermosiphon cooling system, designed for the ATLAS silicon detectors by CERN’s EN-CV team in collaboration with the experiment, will replace the current system in the next LHC run in 2015. Using the basic properties of density difference and making gravity do the hard work, the thermosiphon promises to be a very reliable solution that will ensure the long-term stability of the whole system.   Former compressor-based cooling system of the ATLAS inner detectors. The system is currently being replaced by the innovative thermosiphon. (Photo courtesy of Olivier Crespo-Lopez). Reliability is the major issue for the present cooling system of the ATLAS silicon detectors. The system was designed 13 years ago using a compressor-based cooling cycle. “The current cooling system uses oil-free compressors to avoid fluid pollution in the delicate parts of the silicon detectors,” says Michele Battistin, EN-CV-PJ section leader and project leader of the ATLAS thermosiphon....

  2. South Baltic Wind Atlas

    DEFF Research Database (Denmark)

    Pena Diaz, Alfredo; Hahmann, Andrea N.; Hasager, Charlotte Bay

    A first version of a wind atlas for the South Baltic Sea has been developed using the WRF mesoscale model and verified by data from tall Danish and German masts. Six different boundary-layer parametrization schemes were evaluated by comparing the WRF results to the observed wind profiles at the m...

  3. Prototype ATLAS straw tracker

    CERN Multimedia

    Laurent Guiraud

    1998-01-01

    This is an early prototype of the straw tracking device for the ATLAS detector at CERN. This detector will be part of the LHC project, scheduled to start operation in 2008. The straw tracker will consist of thousands of gas-filled straws, each containing a wire, allowing the tracks of particles to be followed.

  4. Top Physics at Atlas

    CERN Document Server

    Romano, M; The ATLAS collaboration

    2013-01-01

    This talk is an overview of recent results on top-quark physics obtained by the ATLAS collaboration from the analysis of p-p collisions at 7 and 8 TeV at the Large Hadron Collider. Total and differential top pair cross section, single top cross section and mass measurements are presented.

  5. ATLAS fast physics monitoring

    Indian Academy of Sciences (India)

    The ATLAS Collaboration has set up a framework to automatically process the rapidly growing dataset and produce performance and physics plots for the most interesting analyses. The system is designed to give fast feedback. The histograms are produced within hours of data reconstruction (2–3 days after data taking).

  6. MRI-based treatment planning with pseudo CT generated through atlas registration.

    Science.gov (United States)

    Uh, Jinsoo; Merchant, Thomas E; Li, Yimei; Li, Xingyu; Hua, Chiaho

    2014-05-01

    To evaluate the feasibility and accuracy of magnetic resonance imaging (MRI)-based treatment planning using pseudo CTs generated through atlas registration. A pseudo CT, providing electron density information for dose calculation, was generated by deforming atlas CT images previously acquired on other patients. The authors tested 4 schemes of synthesizing a pseudo CT from single or multiple deformed atlas images: use of a single arbitrarily selected atlas, arithmetic mean process using 6 atlases, and pattern recognition with Gaussian process (PRGP) using 6 or 12 atlases. The required deformation for atlas CT images was derived from a nonlinear registration of conjugated atlas MR images to that of the patient of interest. The contrasts of atlas MR images were adjusted by histogram matching to reduce the effect of different sets of acquisition parameters. For comparison, the authors also tested a simple scheme assigning the Hounsfield unit of water to the entire patient volume. All pseudo CT generating schemes were applied to 14 patients with common pediatric brain tumors. The image similarity of real patient-specific CT and pseudo CTs constructed by different schemes was compared. Differences in computation times were also calculated. The real CT in the treatment planning system was replaced with the pseudo CT, and the dose distribution was recalculated to determine the difference. The atlas approach generally performed better than assigning a bulk CT number to the entire patient volume. Comparing atlas-based schemes, those using multiple atlases outperformed the single atlas scheme. For multiple atlas schemes, the pseudo CTs were similar to the real CTs (correlation coefficient, 0.787-0.819). The calculated dose distribution was in close agreement with the original dose. Nearly the entire patient volume (98.3%-98.7%) satisfied the criteria of chi-evaluation (pediatric brain tumor patients. The doses calculated from pseudo CTs agreed well with those from real CTs

  7. ATLAS. LHC experiments

    International Nuclear Information System (INIS)

    Anon.

    1995-01-01

    In Greek mythology, Atlas was a Titan who had to hold up the heavens with his hands as a punishment for having taken part in a revolt against the Olympians. For LHC, the ATLAS detector will also have an onerous physics burden to bear, but this is seen as a golden opportunity rather than a punishment. The major physics goal of CERN's LHC proton-proton collider is the quest for the long-awaited£higgs' mechanism which drives the spontaneous symmetry breaking of the electroweak Standard Model picture. The large ATLAS collaboration proposes a large general-purpose detector to exploit the full discovery potential of LHC's proton collisions. LHC will provide proton-proton collision luminosities at the aweinspiring level of 1034 cm2 s~1, with initial running in at 1033. The ATLAS philosophy is to handle as many signatures as possible at all luminosity levels, with the initial running providing more complex possibilities. The ATLAS concept was first presented as a Letter of Intent to the LHC Committee in November 1992. Following initial presentations at the Evian meeting (Towards the LHC Experimental Programme') in March of that year, two ideas for generalpurpose detectors, the ASCOT and EAGLE schemes, merged, with Friedrich Dydak (MPI Munich) and Peter Jenni (CERN) as ATLAS cospokesmen. Since the initial Letter of Intent presentation, the ATLAS design has been optimized and developed, guided by physics performance studies and the LHC-oriented detector R&D programme (April/May, page 3). The overall detector concept is characterized by an inner superconducting solenoid (for inner tracking) and large superconducting air-core toroids outside the calorimetry. This solution avoids constraining the calorimetry while providing a high resolution, large acceptance and robust detector. The outer magnet will extend over a length of 26 metres, with an outer diameter of almost 20 metres. The total weight of the detector is 7,000 tonnes. Fitted with its end

  8. New format for ATLAS e-news

    CERN Multimedia

    Pauline Gagnon

    ATLAS e-news got a new look! As of November 30, 2007, we have a new format for ATLAS e-news. Please go to: http://atlas-service-enews.web.cern.ch/atlas-service-enews/index.html . ATLAS e-news will now be published on a weekly basis. If you are not an ATLAS colaboration member but still want to know how the ATLAS experiment is doing, we will soon have a version of ATLAS e-news intended for the general public. Information will be sent out in due time.

  9. 18 December 2012 -Portuguese President of FCT M. Seabra visiting the Computing Centre with IT Department Head F. Hemmer, ATLAS experimental area with Collaboration Spokesperson F. Gianotti and A. Henriques Correia, in the LHC tunnel at Point 2 and CMS experimental area with Deputy Spokesperson J. Varela, signing an administrative agreement with Director-General R. Heuer; LIP President J. M. Gago and Delegate to CERN Council G. Barreia present.

    CERN Multimedia

    Samuel Morier-Genoud

    2012-01-01

    18 December 2012 -Portuguese President of FCT M. Seabra visiting the Computing Centre with IT Department Head F. Hemmer, ATLAS experimental area with Collaboration Spokesperson F. Gianotti and A. Henriques Correia, in the LHC tunnel at Point 2 and CMS experimental area with Deputy Spokesperson J. Varela, signing an administrative agreement with Director-General R. Heuer; LIP President J. M. Gago and Delegate to CERN Council G. Barreia present.

  10. 10 September 2013 - Italian Minister for Economic Development F. Zanonato visiting the ATLAS cavern with Collaboration Spokesperson D. Charlton and Italian scientists F. Gianotti and A. Di Ciaccio; signing the guest book with CERN Director-General R. Heuer and Director for Research and Scientific Computing S. Bertolucci; in the LHC tunnel with S. Bertolucci, Technology Deputy Department Head L. Rossi and Engineering Department Head R. Saban; visiting CMS cavern with Scientists G. Rolandi and P. Checchia.

    CERN Multimedia

    Jean-Claude Gadmer

    2013-01-01

    10 September 2013 - Italian Minister for Economic Development F. Zanonato visiting the ATLAS cavern with Collaboration Spokesperson D. Charlton and Italian scientists F. Gianotti and A. Di Ciaccio; signing the guest book with CERN Director-General R. Heuer and Director for Research and Scientific Computing S. Bertolucci; in the LHC tunnel with S. Bertolucci, Technology Deputy Department Head L. Rossi and Engineering Department Head R. Saban; visiting CMS cavern with Scientists G. Rolandi and P. Checchia.

  11. Spracovanie dát na experimente ATLAS

    Czech Academy of Sciences Publication Activity Database

    Marčišovský, Michal; Kubeš, T.; Chudoba, Jiří

    2008-01-01

    Roč. 58, č. 6 (2008), 354-359 ISSN 0009-0700 R&D Projects: GA MŠk LA08032 Institutional research plan: CEZ:AV0Z10100502 Keywords : Atlas * computing * DCS * Grid Subject RIV: BF - Elementary Particles and High Energy Physics

  12. Discrete event simulation of the ATLAS second level trigger

    International Nuclear Information System (INIS)

    Vermeulen, J.C.; Dankers, R.J.; Hunt, S.; Harris, F.; Hortnagl, C.; Erasov, A.; Bogaerts, A.

    1998-01-01

    Discrete event simulation is applied for determining the computing and networking resources needed for the ATLAS second level trigger. This paper discusses the techniques used and some of the results obtained so far for well defined laboratory configurations and for the full system

  13. Discovery of SM Higgs Boson in ATLAS Experiment

    Indian Academy of Sciences (India)

    IAS Admin

    ics, Higgs boson, particle detec- tors, trigger, grid computing. Discovery of SM Higgs Boson in ATLAS Experiment. Prafulla Kumar Behera. Prafulla Kumar Behera is an experimental high energy physicist at the. IITM, Chennai. He has participated in many large-scale collider experiments namely. BELLE at Japan, BABAR.

  14. Evolution of the Argonne Tandem Linear Accelerator System (ATLAS) control system

    International Nuclear Information System (INIS)

    Power, M.; Munson, F.

    2012-01-01

    Given that the Argonne Tandem Linear Accelerator System (ATLAS) recently celebrated its 25. anniversary, this paper will explore the past, present, and future of the ATLAS Control System, and how it has evolved along with the accelerator and control system technology. ATLAS as we know it today, originated with a Tandem Van de Graff in the sixties. With the addition of the Booster section in the late seventies, came the first computerized control. ATLAS itself was placed into service on June 25, 1985, and was the world's first superconducting linear accelerator for ions. Since its dedication as a National User Facility, more than a thousand experiments by more than 2,000 users worldwide, have taken advantage of the unique capabilities it provides. Today, ATLAS continues to be a user facility for physicists who study the particles that form the heart of atoms. Its most recent addition, CARIBU (Californium Rare Isotope Breeder Upgrade), creates special beams that feed into ATLAS. ATLAS is similar to a living organism, changing and responding to new technological challenges and research needs. As it continues to evolve, so does the control system: from the original days using a DEC PDP-11/34 computer and two CAMAC crates, to a DEC Alpha computer running Vsystem software and more than twenty CAMAC crates, to distributed computers and VME systems. Future upgrades are also in the planning stages that will continue to evolve the control system. (authors)

  15. IT Infrastructure Design and Implementation Considerations for the ATLAS TDAQ System

    CERN Document Server

    Dobson, M; The ATLAS collaboration; Caramarcu, C; Dumitru, I; Valsan, L; Darlea, G L; Bujor, F; Bogdanchikov, A G; Korol, A A; Zaytsev, A S; Ballestrero, S

    2013-01-01

    This paper gives a thorough overview of the ATLAS TDAQ SysAdmin group activities which deals with administration of the TDAQ computing environment supporting Front End detector hardware, Data Flow, Event Filter and other subsystems of the ATLAS detector operating on the LHC accelerator at CERN. The current installation consists of approximately 1500 netbooted nodes managed by more than 60 dedicated servers, a high performance centralized storage system, about 50 multi-screen user interface systems installed in the control rooms and various hardware and critical service monitoring machines. In the final configuration, the online computer farm will be capable of hosting tens of thousands applications running simultaneously. The ATLAS TDAQ computing environment is now serving more than 3000 users subdivided into approximately 300 categories in correspondence with their roles in the system. The access and role management system is custom built on top of an LDAP schema. The engineering infrastructure of the ATLAS ...

  16. ATLAS BigPanDA Monitoring

    CERN Document Server

    Padolski, Siarhei; The ATLAS collaboration; Klimentov, Alexei; Korchuganova, Tatiana

    2017-01-01

    BigPanDA monitoring is a web based application which provides various processing and representation of the Production and Distributed Analysis (PanDA) system objects states. Analyzing hundreds of millions of computation entities such as an event or a job BigPanDA monitoring builds different scale and levels of abstraction reports in real time mode. Provided information allows users to drill down into the reason of a concrete event failure or observe system bigger picture such as tracking the computation nucleus and satellites performance or the progress of whole production campaign. PanDA system was originally developed for the Atlas experiment and today effectively managing more than 2 million jobs per day distributed over 170 computing centers worldwide. BigPanDA is its core component commissioned in the middle of 2014 and now is the primary source of information for ATLAS users about state of their computations and the source of decision support information for shifters, operators and managers. In this wor...

  17. ATLAS BigPanDA Monitoring

    CERN Document Server

    Padolski, Siarhei; The ATLAS collaboration

    2017-01-01

    BigPanDA monitoring is a web-based application that provides various processing and representation of the Production and Distributed Analysis (PanDA) system objects states. Analysing hundreds of millions of computation entities such as an event or a job BigPanDA monitoring builds different scale and levels of abstraction reports in real time mode. Provided information allows users to drill down into the reason of a concrete event failure or observe system bigger picture such as tracking the computation nucleus and satellites performance or the progress of whole production campaign. PanDA system was originally developed for the Atlas experiment and today effectively managing more than 2 million jobs per day distributed over 170 computing centers worldwide. BigPanDA is its core component commissioned in the middle of 2014 and now is the primary source of information for ATLAS users about state of their computations and the source of decision support information for shifters, operators and managers. In this work...

  18. ATLAS data sonification: a new interface for musical expression and public interaction

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00345031; The ATLAS collaboration; Goldfarb, Steven

    2017-01-01

    The goal of this project is to transform ATLAS data into sound and explore how ATLAS audio can be a source of inspiration and education for musicians and for the general public. Real-time ATLAS data is sonified and streamed as music on a dedicated website. Listeners may be motivated to learn more about the ATLAS experiment and composers have the opportunity to explore the physics in the collision data through a new medium. The ATLAS collaboration has shared its expertise and access to the live data stream from which the live event displays are generated. This talk tells the story of a long journey from the hallways of CERN where the project collaboration began to the halls of the Montreux Jazz Festival where harmonies were performed. The mapping of the data to sound will be outlined and interactions with musicians and contributions to conferences dedicated to human-computer interaction will also be discussed.

  19. ATLAS B-physics potential

    International Nuclear Information System (INIS)

    Smizanska, M.

    2001-01-01

    Studies since 1993 have demonstrated the ability of ATLAS to pursue a wide B physics program. This document presents the latest performance studies with special stress on lepton identification. B-decays containing several leptons in ATLAS statistically dominate the high-precision measurements. We present new results on physics simulations of CP violation measurements in the B s 0 → J/Ψphi decay and on a novel ATLAS programme on beauty production in central proton-proton collisions of LHC

  20. The ATLAS hadronic tau trigger

    International Nuclear Information System (INIS)

    Shamim, Mansoora

    2012-01-01

    The extensive tau physics programs of the ATLAS experiment relies heavily on trigger to select hadronic decays of tau lepton. Such a trigger is implemented in ATLAS to efficiently collect signal events, while keeping the rate of multi-jet background within the allowed bandwidth. This contribution summarizes the performance of the ATLAS hadronic tau trigger system during 2011 data taking period and improvements implemented for the 2012 data collection.

  1. ATLAS Point-1 System Administration Group

    CERN Multimedia

    Marc Dobson

    2007-01-01

    Hello, my name is Joe Blog and I am about to go on shift at ATLAS. When I enter the control room shown below with my CERN ID card, I go to the subsystem desk for which I am responsible. This is the first shift of the run period and there is a login window displayed on the screens. I just need to hit return and the control room desktop is started. Before I can do anything I must give my credentials in the shifter window which is then synchronised with the shift plan. After that I have access to all the allowed commands and can start preparing for the run. In order not to forget any steps I consult the documentation on how to prepare for a run on the Point-1 web. I can also check what the general status is for the ATLAS online computing farm, the sub-detectors and the LHC by using the utilities provided. ATLAS Control Room. The situation described is made up but the conditions are real. But the control room that the shifters and general public see is only the tip of the iceberg. Behind these tools lie the...

  2. Prompt data reconstruction at the ATLAS experiment

    International Nuclear Information System (INIS)

    Andrew Stewart, Graeme; Boyd, Jamie; Unal, Guillaume; Firmino da Costa, João; Tuggle, Joseph

    2012-01-01

    The ATLAS experiment at the LHC collider recorded more than 5 fb −1 data of pp collisions at a centre-of-mass energy of 7 TeV during 2011. The recorded data are promptly reconstructed in two steps at a large computing farm at CERN to provide fast access to high quality data for physics analysis. In the first step, a subset of the data, corresponding to the express stream and having 10Hz of events, is processed in parallel with data taking. Data quality, detector calibration constants, and the beam spot position are determined using the reconstructed data within 48 hours. In the second step all recorded data are processed with the updated parameters. The LHC significantly increased the instantaneous luminosity and the number of interactions per bunch crossing in 2011; the data recording rate by ATLAS exceeds 400 Hz. To cope with these challenges the performance and reliability of the ATLAS reconstruction software have been improved. In this paper we describe how the prompt data reconstruction system quickly and stably provides high quality data to analysers.

  3. Analysis of empty ATLAS pilot jobs

    CERN Document Server

    Love, Peter; The ATLAS collaboration

    2016-01-01

    The pilot model used by the ATLAS production system has been in use for many years. The model has proven to be a success with many advantages over push models. However one of the negative side-effects of using a pilot model is the presence of 'empty pilots' running on sites which consume a small amount of walltime and not running a useful payload job. The impact on a site can be significant with previous studies showing a total 0.5% walltime usage with no benefit to either the site or to ATLAS. Another impact is the number of empty pilots being processed by a site's Compute Element and batch system which can be 5% of the total number of pilots being handled. In this paper we review the latest statistics using both ATLAS and site data and highlight edge cases where the number of empty pilots dominate. We also study the effect of tuning the pilot factories to reduce the number of empty pilots.

  4. Organization and management of ATLAS nightly builds

    International Nuclear Information System (INIS)

    Luehring, F; Obreshkov, E; Quarrie, D; Rybkine, G; Undrus, A

    2010-01-01

    The automated multi-platform software nightly build system is a major component in the ATLAS collaborative software organization, validation and code approval schemes. Code developers from ATLAS participating Institutes spread all around the world use about 30 branches of nightly releases for testing new packages, verification of patches to existing software, and migration to new platforms and compilers. The nightly releases lead up to, and are the basis of, stable software releases used for data processing worldwide. The ATLAS nightly builds are managed by the fully automated NICOS framework on the computing farm with 44 powerful multiprocessor nodes. The ATN test tool is embedded within the nightly system and provides results shortly after full compilations complete. Other test frameworks are synchronized with NICOS jobs and run larger scale validation jobs using the nightly releases. NICOS web pages dynamically provide information about the progress and results of the builds. For faster feedback, E-mail notifications about nightly releases problems are automatically distributed to the developers responsible.

  5. Taking ATLAS to new heights

    CERN Document Server

    Abha Eli Phoboo, ATLAS experiment

    2013-01-01

    Earlier this month, 51 members of the ATLAS collaboration trekked up to the highest peak in the Atlas Mountains, Mt. Toubkal (4,167m), in North Africa.    The physicists were in Marrakech, Morocco, attending the ATLAS Overview Week (7 - 11 October), which was held for the first time on the African continent. Around 300 members of the collaboration met to discuss the status of the LS1 upgrades and plans for the next run of the LHC. Besides the trek, 42 ATLAS members explored the Saharan sand dunes of Morocco on camels.  Photos courtesy of Patrick Jussel.

  6. Continuous software quality analysis for the ATLAS experiment

    CERN Document Server

    Washbrook, Andrew; The ATLAS collaboration

    2017-01-01

    The software for the ATLAS experiment on the Large Hadron Collider at CERN has evolved over many years to meet the demands of Monte Carlo simulation, particle detector reconstruction and data analysis. At present over 3.8 million lines of C++ code (and close to 6 million total lines of code) are maintained by an active worldwide developer community. In order to run the experiment software efficiently at hundreds of computing centres it is essential to maintain a high level of software quality standards. The methods proposed to improve software quality practices by incorporating checks into the new ATLAS software build infrastructure.

  7. Evolution of user analysis on the grid in ATLAS

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00218990; The ATLAS collaboration; Dewhurst, Alastair

    2017-01-01

    More than one thousand physicists analyse data collected by the ATLAS experiment at the Large Hadron Collider (LHC) at CERN through 150 computing facilities around the world. Efficient distributed analysis requires optimal resource usage and the interplay of several factors: robust grid and software infrastructures, and system capability to adapt to different workloads. The continuous automatic validation of grid sites and the user support provided by a dedicated team of expert shifters have been proven to provide a solid distributed analysis system for ATLAS users. Typical user workflows on the grid, and their associated metrics, are discussed. Measurements of user job performance and typical requirements are also shown.

  8. The SysteMHC Atlas project.

    Science.gov (United States)

    Shao, Wenguang; Pedrioli, Patrick G A; Wolski, Witold; Scurtescu, Cristian; Schmid, Emanuel; Vizcaíno, Juan A; Courcelles, Mathieu; Schuster, Heiko; Kowalewski, Daniel; Marino, Fabio; Arlehamn, Cecilia S L; Vaughan, Kerrie; Peters, Bjoern; Sette, Alessandro; Ottenhoff, Tom H M; Meijgaarden, Krista E; Nieuwenhuizen, Natalie; Kaufmann, Stefan H E; Schlapbach, Ralph; Castle, John C; Nesvizhskii, Alexey I; Nielsen, Morten; Deutsch, Eric W; Campbell, David S; Moritz, Robert L; Zubarev, Roman A; Ytterberg, Anders Jimmy; Purcell, Anthony W; Marcilla, Miguel; Paradela, Alberto; Wang, Qi; Costello, Catherine E; Ternette, Nicola; van Veelen, Peter A; van Els, Cécile A C M; Heck, Albert J R; de Souza, Gustavo A; Sollid, Ludvig M; Admon, Arie; Stevanovic, Stefan; Rammensee, Hans-Georg; Thibault, Pierre; Perreault, Claude; Bassani-Sternberg, Michal; Aebersold, Ruedi; Caron, Etienne

    2018-01-04

    Mass spectrometry (MS)-based immunopeptidomics investigates the repertoire of peptides presented at the cell surface by major histocompatibility complex (MHC) molecules. The broad clinical relevance of MHC-associated peptides, e.g. in precision medicine, provides a strong rationale for the large-scale generation of immunopeptidomic datasets and recent developments in MS-based peptide analysis technologies now support the generation of the required data. Importantly, the availability of diverse immunopeptidomic datasets has resulted in an increasing need to standardize, store and exchange this type of data to enable better collaborations among researchers, to advance the field more efficiently and to establish quality measures required for the meaningful comparison of datasets. Here we present the SysteMHC Atlas (https://systemhcatlas.org), a public database that aims at collecting, organizing, sharing, visualizing and exploring immunopeptidomic data generated by MS. The Atlas includes raw mass spectrometer output files collected from several laboratories around the globe, a catalog of context-specific datasets of MHC class I and class II peptides, standardized MHC allele-specific peptide spectral libraries consisting of consensus spectra calculated from repeat measurements of the same peptide sequence, and links to other proteomics and immunology databases. The SysteMHC Atlas project was created and will be further expanded using a uniform and open computational pipeline that controls the quality of peptide identifications and peptide annotations. Thus, the SysteMHC Atlas disseminates quality controlled immunopeptidomic information to the public domain and serves as a community resource toward the generation of a high-quality comprehensive map of the human immunopeptidome and the support of consistent measurement of immunopeptidomic sample cohorts. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  9. High-Performance Scalable Information Service for the ATLAS Experiment

    International Nuclear Information System (INIS)

    Kolos, S; Boutsioukis, G; Hauser, R

    2012-01-01

    The ATLAS[1] experiment is operated by a highly distributed computing system which is constantly producing a lot of status information which is used to monitor the experiment operational conditions as well as to assess the quality of the physics data being taken. For example the ATLAS High Level Trigger(HLT) algorithms are executed on the online computing farm consisting from about 1500 nodes. Each HLT algorithm is producing few thousands histograms, which have to be integrated over the whole farm and carefully analyzed in order to properly tune the event rejection. In order to handle such non-physics data the Information Service (IS) facility has been developed in the scope of the ATLAS Trigger and Data Acquisition (TDAQ)[2] project. The IS provides a high-performance scalable solution for information exchange in distributed environment. In the course of an ATLAS data taking session the IS handles about a hundred gigabytes of information which is being constantly updated with the update interval varying from a second to a few tens of seconds. IS provides access to any information item on request as well as distributing notification to all the information subscribers. In the latter case IS subscribers receive information within a few milliseconds after it was updated. IS can handle arbitrary types of information, including histograms produced by the HLT applications, and provides C++, Java and Python API. The Information Service is a unique source of information for the majority of the online monitoring analysis and GUI applications used to control and monitor the ATLAS experiment. Information Service provides streaming functionality allowing efficient replication of all or part of the managed information. This functionality is used to duplicate the subset of the ATLAS monitoring data to the CERN public network with a latency of a few milliseconds, allowing efficient real-time monitoring of the data taking from outside the protected ATLAS network. Each information

  10. Generating patient specific pseudo-CT of the head from MR using atlas-based regression

    International Nuclear Information System (INIS)

    Sjölund, J; Forsberg, D; Andersson, M; Knutsson, H

    2015-01-01

    Radiotherapy planning and attenuation correction of PET images require simulation of radiation transport. The necessary physical properties are typically derived from computed tomography (CT) images, but in some cases, including stereotactic neurosurgery and combined PET/MR imaging, only magnetic resonance (MR) images are available. With these applications in mind, we describe how a realistic, patient-specific, pseudo-CT of the head can be derived from anatomical MR images. We refer to the method as atlas-based regression, because of its similarity to atlas-based segmentation. Given a target MR and an atlas database comprising MR and CT pairs, atlas-based regression works by registering each atlas MR to the target MR, applying the resulting displacement fields to the corresponding atlas CTs and, finally, fusing the deformed atlas CTs into a single pseudo-CT. We use a deformable registration algorithm known as the Morphon and augment it with a certainty mask that allows a tailoring of the influence certain regions are allowed to have on the registration. Moreover, we propose a novel method of fusion, wherein the collection of deformed CTs is iteratively registered to their joint mean and find that the resulting mean CT becomes more similar to the target CT. However, the voxelwise median provided even better results; at least as good as earlier work that required special MR imaging techniques. This makes atlas-based regression a good candidate for clinical use. (paper)

  11. Atlas selection for hippocampus segmentation: Relevance evaluation of three meta-information parameters.

    Science.gov (United States)

    Dill, Vanderson; Klein, Pedro Costa; Franco, Alexandre Rosa; Pinho, Márcio Sarroglia

    2018-04-01

    Current state-of-the-art methods for whole and subfield hippocampus segmentation use pre-segmented templates, also known as atlases, in the pre-processing stages. Typically, the input image is registered to the template, which provides prior information for the segmentation process. Using a single standard atlas increases the difficulty in dealing with individuals who have a brain anatomy that is morphologically different from the atlas, especially in older brains. To increase the segmentation precision in these cases, without any manual intervention, multiple atlases can be used. However, registration to many templates leads to a high computational cost. Researchers have proposed to use an atlas pre-selection technique based on meta-information followed by the selection of an atlas based on image similarity. Unfortunately, this method also presents a high computational cost due to the image-similarity process. Thus, it is desirable to pre-select a smaller number of atlases as long as this does not impact on the segmentation quality. To pick out an atlas that provides the best registration, we evaluate the use of three meta-information parameters (medical condition, age range, and gender) to choose the atlas. In this work, 24 atlases were defined and each is based on the combination of the three meta-information parameters. These atlases were used to segment 352 vol from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Hippocampus segmentation with each of these atlases was evaluated and compared to reference segmentations of the hippocampus, which are available from ADNI. The use of atlas selection by meta-information led to a significant gain in the Dice similarity coefficient, which reached 0.68 ± 0.11, compared to 0.62 ± 0.12 when using only the standard MNI152 atlas. Statistical analysis showed that the three meta-information parameters provided a significant improvement in the segmentation accuracy. Copyright © 2018 Elsevier Ltd

  12. Spinal canal stenosis at the level of Atlas

    Directory of Open Access Journals (Sweden)

    Suchanda Bhattacharjee

    2011-01-01

    Full Text Available We report here a rare case of high cervical stenosis at the level of atlas who presented with progressively deteriorating quadriparesis and respiratory distress. A 10-year-old boy presented with above symptoms of one-year duration with a preceding history of trivial trauma prior to onset of such symptoms. Cervical spine MRI revealed a significant stenosis at the level of atlas from the posterior side with a syrinx extending above and below. High-resolution computed tomography of the above level yielded an ill-defined osseous bar compressing the canal at the level of C 1 posterior arch, which appeared bifid in the midline. The patient was immediately taken up for surgery in view of his respiratory complaints. The child showed an excellent recovery after excision of the posterior arch of atlas and removal of the compressing osseous structure.

  13. Data Federation Strategies for ATLAS using XRootD

    CERN Document Server

    Gardner, R; The ATLAS collaboration; Duckeck, G; Elmsheuser, J; Hanushevski, A; Hönig, F; Iven, J; Legger, F; Vukotic, I; Yang, W

    2014-01-01

    In the past year the ATLAS Collaboration accelerated its program to federate data storage resources using an architecture based on XRootD with its attendant redirection and storage integration services. The main goal of the federation is an improvement in the data access experience for the end user while allowing more efficient and intelligent use of computing resources. Along with these advances come integration with existing ATLAS production services (PanDA and its pilot services) and data management services (DQ2, and in the next generation, Rucio). Functional testing of the federation has been integrated into the standard ATLAS and WLCG monitoring frameworks and a dedicated set of tools provides high granularity information on its current and historical usage. We use a federation topology designed to search from the site's local storage outward to its region and to globally distributed storage resources. We describe programmatic testing of various federation access modes including direct access over the w...

  14. Data Federation Strategies for ATLAS using XRootD

    CERN Document Server

    Gardner, R; The ATLAS collaboration; Duckeck, G; Elmsheuser, J; Hanushevski, A; Hönig, F; Iven, J; Legger, F; Vukotic, I; Yang, W

    2013-01-01

    In the past year the ATLAS Collaboration accelerated its program to federate data storage resources using an architecture based on XRootD with its attendant redirection and storage integration services. The main goal of the federation is an improvement in the data access experience for the end user while allowing more efficient and intelligent use of computing resources. Along with these advances come integration with existing ATLAS production services (PanDA and its pilot services) and data management services (DQ2, and in the next generation, Rucio). Functional testing of the federation has been integrated into the standard ATLAS and WLCG monitoring frameworks and a dedicated set of tools provides high granularity information on its current and historical usage. We use a federation topology designed to search from the site's local storage outward to its region and to globally distributed storage resources. We describe programmatic testing of various federation access modes including direct access over the w...

  15. Analysis facility infrastructure (Tier-3) for ATLAS experiment

    CERN Document Server

    González de la Hoza, S; Ros, E; Sánchez, J; Amorós, G; Fassi, F; Fernández, A; Kaci, M; Lamas, A; Salt, J

    2008-01-01

    In the ATLAS computing model the tiered hierarchy ranged from the Tier-0 (CERN) down to desktops or workstations (Tier-3). The focus on defining the roles of each tiered component has evolved with the initial emphasis on the Tier-0 and Tier-1 definition and roles. The various LHC (Large Hadron Collider) projects, including ATLAS, then evolved the tiered hierarchy to include Tier-2’s (Regional centers) as part of their projects. Tier-3 centres, on the other hand, have been defined as whatever an institution could construct to support their Physics goals using institutional and otherwise leveraged resources and therefore have not been considered to be part of the official ATLAS computing resources. However, Tier-3 centres are going to exist and will have implications on how the computing model should support ATLAS physicists. Tier-3 users will want to access LHC data and simulations and will want to enable their resources to support their analysis and simulation work. This document will define how IFIC (Insti...

  16. ATLAS copies its first PetaByte out of CERN

    CERN Multimedia

    M. Branco; P. Salgado; L. Goossens; A. Nairz

    2006-01-01

    On 6th August ATLAS reached a major milestone for its Distributed Data Management project - copying its first PetaByte (1015 Bytes) of data out from CERN to computing centers around the world. This achievement is part of the so-called 'Tier-0 exercise' running since 19th June, where simulated fake data is used to exercise the expected data flow within the CERN computing centre and out over the Grid to the Tier-1 computing centers as would happen during the real data taking. The expected rate of data output from CERN when the detector is running at full trigger rate is 780 MB/s shared among 10 external Tier-1 sites(*), amounting to around 8 PetaBytes per year. The idea of the exercise was to try to reach this data rate and sustain it for as long as possible. The exercise was run as part of the LCG's Service Challenges and allowed ATLAS to test successfully the integration of ATLAS software with the LCG middleware services that are used for low level cataloging and the actual data movement. When ATLAS is produ...

  17. The Human Cell Atlas.

    Science.gov (United States)

    Regev, Aviv; Teichmann, Sarah A; Lander, Eric S; Amit, Ido; Benoist, Christophe; Birney, Ewan; Bodenmiller, Bernd; Campbell, Peter; Carninci, Piero; Clatworthy, Menna; Clevers, Hans; Deplancke, Bart; Dunham, Ian; Eberwine, James; Eils, Roland; Enard, Wolfgang; Farmer, Andrew; Fugger, Lars; Göttgens, Berthold; Hacohen, Nir; Haniffa, Muzlifah; Hemberg, Martin; Kim, Seung; Klenerman, Paul; Kriegstein, Arnold; Lein, Ed; Linnarsson, Sten; Lundberg, Emma; Lundeberg, Joakim; Majumder, Partha; Marioni, John C; Merad, Miriam; Mhlanga, Musa; Nawijn, Martijn; Netea, Mihai; Nolan, Garry; Pe'er, Dana; Phillipakis, Anthony; Ponting, Chris P; Quake, Stephen; Reik, Wolf; Rozenblatt-Rosen, Orit; Sanes, Joshua; Satija, Rahul; Schumacher, Ton N; Shalek, Alex; Shapiro, Ehud; Sharma, Padmanee; Shin, Jay W; Stegle, Oliver; Stratton, Michael; Stubbington, Michael J T; Theis, Fabian J; Uhlen, Matthias; van Oudenaarden, Alexander; Wagner, Allon; Watt, Fiona; Weissman, Jonathan; Wold, Barbara; Xavier, Ramnik; Yosef, Nir

    2017-12-05

    The recent advent of methods for high-throughput single-cell molecular profiling has catalyzed a growing sense in the scientific community that the time is ripe to complete the 150-year-old effort to identify all cell types in the human body. The Human Cell Atlas Project is an international collaborative effort that aims to define all human cell types in terms of distinctive molecular profiles (such as gene expression profiles) and to connect this information with classical cellular descriptions (such as location and morphology). An open comprehensive reference map of the molecular state of cells in healthy human tissues would propel the systematic study of physiological states, developmental trajectories, regulatory circuitry and interactions of cells, and also provide a framework for understanding cellular dysregulation in human disease. Here we describe the idea, its potential utility, early proofs-of-concept, and some design considerations for the Human Cell Atlas, including a commitment to open data, code, and community.

  18. ATLAS Upgrade Programme

    CERN Document Server

    Hillier, S J; The ATLAS collaboration

    2012-01-01

    With the already outstanding LHC luminosity performance, and planned LHC upgrades in the upcoming shutdowns, it is expected that within a short time-scale, the general purpose LHC experiments will have to cope with luminosities beyond their original design. In order to maintain detector performance and sensitivity to expected and new physics processes, ATLAS has defined a continuous upgrade programme which foresees staged enhancements during the next 10 years of operation, and then more widespread changes before the transition to the highest luminosities after 2022. This talk will describe several components of the ATLAS upgrade, focusing in particular on the Inner Detector and Trigger. The Inner Detector faces two challenges in the higher luminosity environment: high particle multiplicities and increased radiation dose. These will be addressed in the short term by a new layer of Pixel detectors, and in the long term by a complete replacement. The Trigger faces an increasingly difficult task of distinguishing...

  19. ATLAS IBL operational experience

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00237659; The ATLAS collaboration

    2017-01-01

    The Insertable B-Layer (IBL) is the inner most pixel layer in the ATLAS experiment, which was installed at 3.3 cm radius from the beam axis in 2014 to improve the tracking performance. To cope with the high radiation and hit occupancy due to proximity to the interaction point, a new read-out chip and two different silicon sensor technologies (planar and 3D) have been developed for the IBL. After the long shut-down period over 2013 and 2014, the ATLAS experiment started data-taking in May 2015 for Run-2 of the Large Hadron Collider (LHC). The IBL has been operated successfully since the beginning of Run-2 and shows excellent performance with the low dead module fraction, high data-taking efficiency and improved tracking capability. The experience and challenges in the operation of the IBL is described as well as its performance.

  20. The ATLAS Tau Trigger

    International Nuclear Information System (INIS)

    Rados, Petar Kevin

    2013-06-01

    The tau lepton plays a crucial role in understanding particle physics at the Tera scale. One of the most promising probes of the Higgs boson coupling to fermions is with detector signatures involving taus. In addition, many theories beyond the Standard Model, such as supersymmetry and exotic particles (W' and Z'), predict new physics with large couplings to taus. The ability to trigger on hadronic tau decays is therefore critical to achieving the physics goals of the ATLAS experiment. The higher instantaneous luminosities of proton-proton collisions achieved by the Large Hadron Collider (LHC) in 2012 resulted in a larger probability of overlap (pile-up) between bunch crossings, and so it was critical for ATLAS to have an effective tau trigger strategy. The details of this strategy are summarized in this paper, and the results of the latest performance measurements are presented. (authors)

  1. Analysis Streamlining in ATLAS

    CERN Document Server

    Heinrich, Lukas; The ATLAS collaboration

    2018-01-01

    We present recent work within the ATLAS collaboration centrally provide tools to facilitate analysis management and highly automated container-based analysis execution in order to both enable non-experts to benefit from these best practices as well as the collaboration to track and re-execute analyses indpendently, e.g. during their review phase. Through integration with the ATLAS GLANCE system, users can request a pre-configured, but customizable version control setup, including continuous integration for automated build and testing as well as continuous Linux Container image building for software preservation purposes. As analyses typically require many individual steps, analysis workflow pipelines can then be defined using such images and the yadage workflow description language. The integration into the workflow exection service REANA allows the interactive or automated reproduction of the main analysis results by orchestrating a large number of container jobs using the Kubernetes. For long-term archival,...

  2. Jet physics in ATLAS

    CERN Multimedia

    CERN. Geneva

    2012-01-01

    Measurements of hadronic jets provide tests of strong interactions which are interesting both in their own right and as backgrounds to many New Physics searches. It is also through tests of Quantum Chromodynamics that new physics may be discovered. The extensive dataset recorded with the ATLAS detector throughout the 7 TeV centre-of-mass LHC operation period allows QCD to be probed at distances never reached before. We present a review of selected ATLAS jet performance and physics measurements, together with results from new physics searches using the 2011 dataset. They include studies of the underlying event and fragmentation models, measurements of the inclusive jet, dijet and multijet cross sections, parton density functions, heavy flavours, jet shape, mass and substructure. Searches for new physics in monojet, dijet and photon-jet final states are also presented.

  3. Jet substructure in ATLAS

    CERN Document Server

    Miller, David W

    2011-01-01

    Measurements are presented of the jet invariant mass and substructure in proton-proton collisions at $\\sqrt{s} = 7$ TeV with the ATLAS detector using an integrated luminosity of 37 pb$^{-1}$. These results exercise the tools for distinguishing the signatures of new boosted massive particles in the hadronic final state. Two "fat" jet algorithms are used, along with the filtering jet grooming technique that was pioneered in ATLAS. New jet substructure observables are compared for the first time to data at the LHC. Finally, a sample of candidate boosted top quark events collected in the 2010 data is analyzed in detail for the jet substructure properties of hadronic "top-jets" in the final state. These measurements demonstrate not only our excellent understanding of QCD in a new energy regime but open the path to using complex jet substructure observables in the search for new physics.

  4. Teaching atlas of mammography

    International Nuclear Information System (INIS)

    Tabar, L.; Dean, P.B.

    1985-01-01

    The illustrated case reports in this teaching atlas cover practically the entire range of possible pathological changes and are based on in-patient case material and 80,000 screening documents. The two basic approaches, - detection and analysis of changes -, are taught comprehensively and in great detail. A systematic procedure for analysing the mammographies, in order to detect even the very least changes, and its practical application is explained using mammographies showing unclear findings at first sight. A system of coordinates is presented which allows precise localisation of the changes. Exercises for practising the technique of identifying the pathological changes round up the methodolical chapters. Additional imaging technical enhancements and detail enlargements are of great help in interpreting the findings. The specific approach adopted for this teaching atlas is a 'reverse procedure', which leaves the beaten track and starts with analysing the mammographies and evaluating the radiographic findings, in order to finally derive the diagnosis. (orig./CB) [de

  5. Multiatlas whole heart segmentation of CT data using conditional entropy for atlas ranking and selection

    Energy Technology Data Exchange (ETDEWEB)

    Zhuang, Xiahai, E-mail: zhuangxiahai@sjtu.edu.cn; Qian, Xiaohua [SJTU-CU International Cooperative Research Center, Department of Engineering Mechanics, School of Naval Architecture Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240 (China); Bai, Wenjia; Shi, Wenzhe; Rueckert, Daniel [Biomedical Image Analysis Group, Department of Computing, Imperial College London, 180 Queens Gate, London SW7 2AZ (United Kingdom); Song, Jingjing; Zhan, Songhua [Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai 201203 (China); Lian, Yanyun [Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai 201210 (China)

    2015-07-15

    Purpose: Cardiac computed tomography (CT) is widely used in clinical diagnosis of cardiovascular diseases. Whole heart segmentation (WHS) plays a vital role in developing new clinical applications of cardiac CT. However, the shape and appearance of the heart can vary greatly across different scans, making the automatic segmentation particularly challenging. The objective of this work is to develop and evaluate a multiatlas segmentation (MAS) scheme using a new atlas ranking and selection algorithm for automatic WHS of CT data. Research on different MAS strategies and their influence on WHS performance are limited. This work provides a detailed comparison study evaluating the impacts of label fusion, atlas ranking, and sizes of the atlas database on the segmentation performance. Methods: Atlases in a database were registered to the target image using a hierarchical registration scheme specifically designed for cardiac images. A subset of the atlases were selected for label fusion, according to the authors’ proposed atlas ranking criterion which evaluated the performance of each atlas by computing the conditional entropy of the target image given the propagated atlas labeling. Joint label fusion was used to combine multiple label estimates to obtain the final segmentation. The authors used 30 clinical cardiac CT angiography (CTA) images to evaluate the proposed MAS scheme and to investigate different segmentation strategies. Results: The mean WHS Dice score of the proposed MAS method was 0.918 ± 0.021, and the mean runtime for one case was 13.2 min on a workstation. This MAS scheme using joint label fusion generated significantly better Dice scores than the other label fusion strategies, including majority voting (0.901 ± 0.276, p < 0.01), locally weighted voting (0.905 ± 0.0247, p < 0.01), and probabilistic patch-based fusion (0.909 ± 0.0249, p < 0.01). In the atlas ranking study, the proposed criterion based on conditional entropy yielded a performance curve

  6. Boosted tops at ATLAS

    CERN Document Server

    Villaplana, M; The ATLAS collaboration

    2011-01-01

    A sample of candidate events for highly boosted top quarks is selected following the standard ATLAS selection for semi-leptonic ttbar events plus a requirement that the invariant mass of the reconstructed ttbar pair is greater than 700 GeV. Event displays are presented for the most promising candidates, as well as quantitative results for observables designed to isolate a boosted top quark signal.

  7. The ATLAS simulation infrastructure

    Czech Academy of Sciences Publication Activity Database

    Aad, G.; Abbott, B.; Abdallah, J.; Bazalová, Magdalena; Böhm, Jan; Chudoba, Jiří; Gallus, Petr; Gunther, Jaroslav; Havránek, Miroslav; Hruška, I.; Jahoda, M.; Juránek, Vojtěch; Kepka, Oldřich; Kupčo, Alexander; Kůs, Vlastimil; Kvasnička, Jiří; Lipinský, L.; Lokajíček, Miloš; Marčišovský, Michal; Mikeštíková, Marcela; Myška, Miroslav; Němeček, Stanislav; Panušková, M.; Popule, Jiří; Růžička, Pavel; Schovancová, Jaroslava; Šícho, Petr; Staroba, Pavel; Šťastný, Jan; Taševský, Marek; Tic, Tomáš; Tomášek, Lukáš; Tomášek, Michal; Valenta, J.; Vrba, Václav

    2010-01-01

    Roč. 70, č. 3 (2010), s. 823-874 ISSN 1434-6044 R&D Projects: GA MŠk LC527; GA MŠk LA08015; GA MŠk LA08032 Institutional research plan: CEZ:AV0Z10100502 Keywords : ATLAS * simulation Subject RIV: BF - Elementary Particles and High Energy Physics Impact factor: 3.248, year: 2010 http://arxiv.org/pdf/1005.4568

  8. The atlas detector

    International Nuclear Information System (INIS)

    Perrodo, P.

    2001-01-01

    The ATLAS detector, one of the two multi-purpose detectors at the Large Hadron Collider at CERN, is currently being built in order to meet the first proton-proton collisions in time. A description of the detector components will be given, corresponding to the most up to date design and status of construction, completed with test beam results and performances of the first serial modules. (author)

  9. Exotics searches in ATLAS

    CERN Document Server

    Wang, Renjie; The ATLAS collaboration

    2017-01-01

    Many theories beyond the Standard Model predict new physics accessible by the LHC. The ATLAS experiment all have rigorous search programs ongoing with the aim to find indications for new physics involving state of the art analysis techniques. This talk reports on new results obtained using the pp collision data sample collected in 2015 and 2016 at the LHC with a centre-of-mass energy of 13 TeV.

  10. Higgs results from ATLAS

    International Nuclear Information System (INIS)

    Chen, Xin

    2016-01-01

    The updated Higgs measurements in various search channels with ATLAS Run 1 data are reviewed. Both the Standard Model (SM) Higgs results, such as H → γγ, ZZ, WW, ττ, μμ, bb-bar, and Beyond Standard Model (BSM) results, such as the charged Higgs, Higgs invisible decay and tensor couplings, are summarized. Prospects for future Higgs searches are briefly discussed

  11. The ATLAS TRT electronics

    OpenAIRE

    Çetin, Serkant Ali; ATLAS Collaboration

    2008-01-01

    The ATLAS inner detector consists of three sub-systems: the pixel detector spanning the radius range 4cm-20cm, the semiconductor tracker at radii from 30 to 52 cm, and the transition radiation tracker (TRT), tracking from 56 to 107 cm. The TRT provides a combination of continuous tracking with many projective measurements based on individual drift tubes (or straws) and of electron identification based on transition radiation from fibres or foils interleaved between the straws themselves. This...

  12. Atlas de fitoplancton marino.

    OpenAIRE

    Amaya, Oscar; Alvarado, Yaneth; Chávez, Isaias; Ruíz, Gerrado; Lopez, Douglas

    2014-01-01

    En El Salvador existe un fenómeno natural que afecta a las costas marítimas que son los fitoplancton; mediante el cual se expone el Atlas de fitoplancton marino que contiene 100 p. con imágenes, mapas, etc., con el fin de dar a conocer más de 200 especies de fitoplancton identificada hasta el momento, algunos son tóxicas, inocuas y nocivas.

  13. The SysteMHC Atlas project

    DEFF Research Database (Denmark)

    Shao, Wenguang; Pedrioli, Patrick G. A.; Wolski, Witold

    2018-01-01

    consisting of consensus spectra calculated from repeat measurements of the same peptide sequence, and links to other proteomics and immunology databases. The SysteMHC Atlas project was created and will be further expanded using a uniform and open computational pipeline that controls the quality of peptide......-scale generation of immunopeptidomic datasets and recent developments in MS-based peptide analysis technologies now support the generation of the required data. Importantly, the availability of diverse immunopeptidomic datasets has resulted in an increasing need to standardize, store and exchange this type of data...

  14. ATLAS Detector Upgrade Prospects

    CERN Document Server

    Dobre, Monica; The ATLAS collaboration

    2016-01-01

    After the successful operation at the center-of-mass energies of 7 and 8 TeV in 2010 - 2012, the LHC is ramped up and successfully took data at the center-of-mass energies of 13 TeV in 2015. Meanwhile, plans are actively advancing for a series of upgrades of the accelerator, culminating roughly ten years from now in the high-luminosity LHC (HL-LHC) project, delivering of the order of five times the LHC nominal instantaneous luminosity along with luminosity leveling. The ultimate goal is to extend the dataset from about few hundred fb−1 expected for LHC running to 3000 fb−1 by around 2035 for ATLAS and CMS. The challenge of coping with the HL-LHC instantaneous and integrated luminosity, along with the associated radiation levels, requires further major changes to the ATLAS detector. The designs are developing rapidly for a new all-silicon tracker, significant upgrades of the calorimeter and muon systems, as well as improved triggers and data acquisition. ATLAS is also examining potential benefits of extens...

  15. ATLAS detector upgrade prospects

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00184940; The ATLAS collaboration

    2017-01-01

    After the successful operation at the centre-of-mass energies of 7 and 8 TeV in 2010-2012, the LHC is ramped up and successfully took data at the centre-of-mass energies of 13 TeV in 2015. Meanwhile, plans are actively advancing for a series of upgrades of the accelerator, culminating roughly ten years from now in the high-luminosity LHC (HL-LHC) project, delivering of the order of five times the LHC nominal instantaneous luminosity along with luminosity levelling. The ultimate goal is to extend the dataset from about few hundred fb$^{-1}$ expected for LHC running to 3000 fb $^{-1}$ by around 2035 for ATLAS and CMS. The challenge of coping with the HL-LHC instantaneous and integrated luminosity, along with the associated radiation levels, requires further major changes to the ATLAS detector. The designs are developing rapidly for a new all-silicon tracker, significant upgrades of the calorimeter and muon systems, as well as improved triggers and data acquisition. ATLAS is also examining potential benefits of ...

  16. ATLAS Upgrade Plans

    CERN Document Server

    Hopkins, W; The ATLAS collaboration

    2014-01-01

    After the successful LHC operation at the center-of-mass energies of 7 and 8 TeV in 2010-2012, plans are actively advancing for a series of upgrades of the accelerator, culminating roughly ten years from now in the high-luminosity LHC (HL-LHC) project, delivering of the order of five times the LHC nominal instantaneous luminosity along with luminosity leveling. The final goal is to extend the dataset from about few hundred fb−1 expected for LHC running to 3000/fb by around 2035 for ATLAS and CMS. In parallel, the experiments need to be keep lockstep with the accelerator to accommodate running beyond the nominal luminosity this decade. Current planning in ATLAS envisions significant upgrades to the detector during the consolidation of the LHC to reach full LHC energy and further upgrades. The challenge of coping with the HL-LHC instantaneous and integrated luminosity, along with the associated radiation levels, requires further major changes to the ATLAS detector. The designs are developing rapidly for a new...

  17. ATLAS overview week highlights

    CERN Multimedia

    D. Froidevaux

    2005-01-01

    A warm and early October afternoon saw the beginning of the 2005 ATLAS overview week, which took place Rue de La Montagne Sainte-Geneviève in the heart of the Quartier Latin in Paris. All visitors had been warned many times by the ATLAS management and the organisers that the premises would be the subject of strict security clearance because of the "plan Vigipirate", which remains at some level of alert in all public buildings across France. The public building in question is now part of the Ministère de La Recherche, but used to host one of the so-called French "Grandes Ecoles", called l'Ecole Polytechnique (in France there is only one Ecole Polytechnique, whereas there are two in Switzerland) until the end of the seventies, a little while after it opened its doors also to women. In fact, the setting chosen for this ATLAS overview week by our hosts from LPNHE Paris has turned out to be ideal and the security was never an ordeal. For those seeing Paris for the first time, there we...

  18. Clean tracks for ATLAS

    CERN Multimedia

    2006-01-01

    First cosmic ray tracks in the integrated ATLAS barrel SCT and TRT tracking detectors. A snap-shot of a cosmic ray event seen in the different layers of both the SCT and TRT detectors. The ATLAS Inner Detector Integration Team celebrated a major success recently, when clean tracks of cosmic rays were detected in the completed semiconductor tracker (SCT) and transition radiation tracker (TRT) barrels. These tracking tests come just months after the successful insertion of the SCT into the TRT (See Bulletin 09/2006). The cosmic ray test is important for the experiment because, after 15 years of hard work, it is the last test performed on the fully assembled barrel before lowering it into the ATLAS cavern. The two trackers work together to provide millions of channels so that particles' tracks can be identified and measured with great accuracy. According to the team, the preliminary results were very encouraging. After first checks of noise levels in the final detectors, a critical goal was to study their re...

  19. ATLAS Silicon Microstrip Tracker

    CERN Document Server

    Haefner, Petra; The ATLAS collaboration

    2010-01-01

    The SemiConductor Tracker (SCT), made up from silicon micro-strip detectors is the key precision tracking device in ATLAS, one of the experiments at CERN LHC. The completed SCT is in very good shape: 99.3% of the SCT strips are operational, noise occupancy and hit efficiency exceed the design specifications. In the talk the current status of the SCT will be reviewed. We will report on the operation of the detector and observed problems, with stress on the sensor and electronics performance. TWEPP Summary In December 2009 the ATLAS experiment at the CERN Large Hadron Collider (LHC) recorded the first proton- proton collisions at a centre-of-mass energy of 900 GeV and this was followed by the unprecedented energy of 7 TeV in March 2010. The SemiConductor Tracker (SCT) is the key precision tracking device in ATLAS, made up from silicon micro-strip detectors processed in the planar p-in-n technology. The signal from the strips is processed in the front-end ASICS ABCD3TA, working in the binary readout mode. Data i...

  20. ATLAS Data Challenges - A Collaborative Worldwide Activity

    CERN Multimedia

    Poulard, G

    The goals of the ATLAS Data Challenges (DC) are the validation of the Computing Model, of the complete software suite, of the data model, and to ensure the correctness of the technical choices to be made. It is understood that these Data Challenges should be of increasing complexity and that their results will be used as input for a Computing TDR and for preparing an MoU in due time. A major feature of the current computing activities (DC1) in ATLAS is the preparation and deployment of the software required for the production of large event samples for the High Level Trigger (HLT) and physics communities, and the actual production of those samples. It should be noted that it is not an option to "run everything at CERN" even if we wanted to; the resources are not available at CERN to carry out the production on a reasonable time-scale. We have therefore had to face the great challenge of organising and then carrying out this large-scale production at a significant number of sites around the world. However, th...