A5106031479- Distributed and Parallel Computing Systems
- Particle Detector Development and Performance
- Advanced Data Storage Technologies
- Scientific Computing and Data Management
- Particle physics theoretical and experimental studies
- Advanced Database Systems and Queries
- High-Energy Particle Collisions Research
- Advanced Computational Techniques and Applications
- Environmental Monitoring and Data Management
- Data Management and Algorithms
- Research Data Management Practices
- Superconducting Materials and Applications
- Computational Physics and Python Applications
Institut polytechnique de Grenoble
2025
Université Grenoble Alpes
2008-2025
Institut National de Physique Nucléaire et de Physique des Particules
2008-2025
Centre National de la Recherche Scientifique
2007-2025
Laboratoire de Physique Subatomique et de Cosmologie
2008-2024
Université Joseph Fourier
2006-2020
AMI is the main interface for searching ATLAS datasets using physics metadata criteria. has been implemented as a generic database management framework that allows parallel over many catalogues, which may have differing schema, and be distributed geographically, different RDBMS.
AMI was chosen as the ATLAS dataset selection interface in July 2006. It is main for searching data using physics metadata criteria. has been implemented a generic database management framework which allows parallel over many catalogues, may have differing schema. The features of web will be described; particular powerful graphic query builder. use XML/XLST technology ensures that all commands can used either on or from command line via service. We also describe overall architecture and...
In the ATLAS experiment, a system called COMA (Conditions/Configuration Metadata for ATLAS), has been developed to make globally important run-level metadata more readily accessible. It is based on relational database storing directly extracted, refined, reduced, and derived information from system-specific sources as well non-database sources. This facilitates variety of unique dynamic interfaces provides enhance functionality other systems.
The ATLAS Metadata Interface (AMI) is a mature application of more than 15 years existence. Mainly used by the experiment at CERN, it consists very generic tool ecosystem for metadata aggregation and cataloguing. We briefly describe architecture, main services benefits using AMI in big collaborations, especially high energy physics. focus on recent improvements, instance: lightweight clients (Python, JavaScript, C++), new smart task server system Web 2.0 framework simplifying development...
The "ATLAS Metadata Interface" framework (AMI) has been developed in the context of ATLAS, one largest scientific collaborations. AMI can be considered to a mature application, since its basic architecture maintained for over 10 years. In this paper we describe briefly and main uses within experiment (TagCollector release management Dataset Discovery). These two applications, which share almost 2000 registered users, are superficially quite different, however much code is shared they have...
The ATLAS Metadata Interface (AMI) is now a mature application. Over the years, number of users and provided functions has dramatically increased. It necessary to adapt hardware infrastructure in seamless way so that quality service re - mains high. We describe AMI evolution since its beginning being served by single MySQL backend database server current state having cluster virtual machines at French Tier1, an Oracle Lyon with complementary replication DB CERN back-up server.
The ATLAS Metadata Interface (AMI), a mature application of more than 10 years existence, is currently under adaptation to some recently available technologies. web interfaces, which previously manipulated XML documents using XSL transformations, are being migrated Asynchronous JavaScript (AJAX). Web development considerably simplified by the introduction framework based on JQuery and Twitter Bootstrap. Finally, AMI services an OpenStack cloud infrastructure.
ATLAS Metadata Interface (AMI) is a generic ecosystem for metadata aggregation, transformation and cataloging. Benefiting from 18 years of feedback in the LHC context, second major version was recently released. This paper describes design choices their benefits providing high-level metadata-dedicated features. In particular, Querying Language (MQL) - domain-specific language allowing to query databases without knowing relation between entities on AMI Web framework are described.
ATLAS Metadata Interface (AMI) is a generic ecosystem for metadata aggregation, transformation and cataloging. Each sub-system of the stack has recently been improved in order to acquire messaging/telemetry capabilities. This paper describes whole monitoring with Message Queuing Telemetry Transport (MQTT) protocol Node-RED, tool wiring together hardware/software devices. Finally, this shows how Node-RED used graphically define aggregation tasks, pipelined way, without introducing any single...
ATLAS Metadata Interface (AMI) is a generic ecosystem for metadata aggregation, transformation and cataloging. This paper describes how renewed architecture integration with modern technologies ease the usage deployment of complete AMI stack. It to deploy in Docker Compose or Kubernetes environment, particular emphasis on registration existing databases, addition more sources, generation high level Web search interfaces using dedicated wizards.
We update our CHEP06 [2] presentation on the ATLAS experiment software infrastructure used to build, validate, distribute, and document offline software. The collaboration's computational resources developers are distributed around globe in about 35 counties. code base is currently over 7 million source lines of 10,000+ C++ classes organized into 2,000 packages. More than 400 contribute each month. Since last report, we have developed a powerful, flexible system request versions be included...
AMI (ATLAS Metadata Interface) is a generic ecosystem for metadata aggregation, transformation and cataloguing. Often, it interesting to share up-to-date with other content services such as wikis. Here, the cross-domain solution implemented in Web Framework described: system of embeddable controls, communicating central service based on AJAX CORS technologies. The main available controls their basic usage are also described.
The ATLAS Metadata Interface ("AMI") was designed as a generic cataloguing system, and such it has found many uses in the experiment including software release management, tracking of reconstructed event sizes control dataset nomenclature. primary use AMI is to provide catalogue datasets (file collections) which searchable using physics criteria. In this paper we discuss various mechanisms used for filling file catalogues. By correlating information from different sources can derive...
ATLAS Metadata Interface (AMI) is a generic software ecosystem for metadata aggregation, transformation and cataloguing. Benefiting from about 20 years of feedback in the LHC context, second major version was released 2018. This paper describes how to install administrate AMI 2. A particular focus given registration existing databases AMI, adding additional and, finally, generation high level HTML 5 search interfaces using dedicated wizard.
This document describes the design principles of Metadata Querying Language (MQL) implemented in ATLAS Interface (AMI), a metadata-oriented domain-specific language allowing to query databases without knowing relation between tables. With this simplified yet generic grammar, MQL permits writing complex queries more simply than with Structured Query (SQL).
The distributed analysis system for the ATLAS experiment is described. Although under construction and design still evolving, major components have been identified. A generic service interface provides connection between a choice of user environments selection engines capable carrying out processing. Other services provide access to catalogs, files software.
The ATLAS Metadata Interface (AMI) is a mature application of more than 15 years existence. Mainly used by the experiment at CERN, it consists very generic tool ecosystem for metadata aggregation and cataloguing. AMI production system, therefore service must guarantee high level availability. We describe our monitoring administration systems, Jenkins-based strategy to dynamically test deploy cloud OpenStack nodes on demand.