COOL, LCG conditions database for the LHC experiments: Development and deployment status

Valassi, A.; Basset, Romain; Clemencic, M.; Pucciani, Gianni; Schmidt, Sven; Wache, M.

doi:10.1109/nssmic.2008.4774995

Cited by 16 publications

(7 citation statements)

References 2 publications

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“…The precision of measurements of the leakage current read with the power supply units was improved during LHC Run 2. The raw leakage current data measured by both the HVPP4 system and the power supplies are stored in the COOL database [53].…”

Section: Outer Pixel Layers and Disks 441 Measurement Subsystemsmentioning

confidence: 99%

Measurements of sensor radiation damage in the ATLAS inner detector using leakage currents

Aad

Abbott

et al. 2021

J. Inst.

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The ATLAS CollaborationNon-ionizing energy loss causes bulk damage to the silicon sensors of the ATLAS pixel and strip detectors. This damage has important implications for data-taking operations, charged-particle track reconstruction, detector simulations, and physics analysis. This paper presents simulations and measurements of the leakage current in the ATLAS pixel detector and semiconductor tracker as a function of location in the detector and time, using data collected in Run 1 (2010)(2011)(2012) and Run 2 (2015-2018) of the Large Hadron Collider. The extracted fluence shows a much stronger | |-dependence in the innermost layers than is seen in simulation. Furthermore, the overall fluence on the second innermost layer is significantly higher than in simulation, with better agreement in layers at higher radii. These measurements are important for validating the simulation models and can be used in part to justify safety factors for future detector designs and interventions.

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Section: Outer Pixel Layers and Disks 441 Measurement Subsystemsmentioning

confidence: 99%

Measurements of sensor radiation damage in the ATLAS inner detector using leakage currents

Aad

Abbott

et al. 2021

J. Inst.

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“…It is foreseen to store in the TriggerDB all versions of configurations that have been used for data taking and those prepared for simulation and test runs. The unique integer key (the Master Key) that identifies a certain configuration will be transfered to the conditions database of the experiment [4]. This Master Key provides the unique reference to a configuration and can therefore be used to retrieve the configuration at a later stage.…”

Section: Jinst 1 P05004mentioning

confidence: 99%

A configuration system for the ATLAS trigger

et al. 2006

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The ATLAS detector at CERN's Large Hadron Collider will be exposed to proton-proton collisions from beams crossing at 40 MHz that have to be reduced to the few 100 Hz allowed by the storage systems. A three-level trigger system has been designed to achieve this goal. We describe the configuration system under construction for the ATLAS trigger chain. It provides the trigger system with all the parameters required for decision taking and to record its history. The same system configures the event reconstruction, Monte Carlo simulation and data analysis, and provides tools for accessing and manipulating the configuration data in all contexts.

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“…These data are essential for the processing of physics data, in order to reconstruct events optimally and to exploit the full detector's potential. In the ATLAS experiment [1] at the LHC these data are stored in relational DB (Oracle), using a model based on the LCG Conditions database infrastructure and the COOL API, both developed mainly by CERN IT [2]. During data processing these Conditions data are accessed worldwide by thousands of jobs in parallel, which requires a solid architecture for their distribution and access.…”

Section: Introductionmentioning

confidence: 99%

An Information Aggregation and Analytics System for ATLAS Frontier

et al. 2020

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ATLAS event processing requires access to centralized database systems where information about calibrations, detector status and data-taking conditions are stored. This processing is done on more than 150 computing sites on a world-wide computing grid which are able to access the database using the Squid-Frontier system. Some processing workflows have been found which overload the Frontier system due to the Conditions data model currently in use, specifically because some of the Conditions data requests have been found to have a low caching efficiency. The underlying cause is that non-identical requests as far as the caching are actually retrieving a much smaller number of unique payloads. While ATLAS is undertaking an adiabatic transition during the LHC Long Shutdown 2 and Run 3 from the current COOL Conditions data model to a new data model called CREST for Run 4, it is important to identify the problematic Conditions queries with low caching efficiency and work with the detector subsystems to improve the storage of such data within the current data model. For this purpose ATLAS put together an information aggregation and analytics system. The system is based on aggregated data from the Squid-Frontier logs using the Elasticsearch technology. This paper§ describes the components of this analytics system from the server based on Flask/Celery application to the user interface and how we use Spark SQL functionalities to filter data for making plots, storing the caching efficiency results into a Elasticsearch database and finally deploying the package via a Docker container.

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COOL, LCG conditions database for the LHC experiments: Development and deployment status

Abstract: -

Cited by 16 publications

References 2 publications

Measurements of sensor radiation damage in the ATLAS inner detector using leakage currents

Measurements of sensor radiation damage in the ATLAS inner detector using leakage currents

A configuration system for the ATLAS trigger

An Information Aggregation and Analytics System for ATLAS Frontier

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