Dr Elizabeth Gallas: Publications

Collecting conditions usage metadata to optimize current and future ATLAS software and processing

Journal of Physics: Conference Series 898:4 (2017)

Authors:

L Rinaldi, D Barberis, A Formica, EJ Gallas, S Oda, G Rybkin, M Verducci

Abstract:

© Published under licence by IOP Publishing Ltd. Conditions data (for example: alignment, calibration, data quality) are used extensively in the processing of real and simulated data in ATLAS. The volume and variety of the conditions data needed by different types of processing are quite diverse, so optimizing its access requires a careful understanding of conditions usage patterns. These patterns can be quantified by mining representative log files from each type of processing and gathering detailed information about conditions usage for that type of processing into a central repository.

Evolution of ATLAS conditions data and its management for LHC Run-2

21ST INTERNATIONAL CONFERENCE ON COMPUTING IN HIGH ENERGY AND NUCLEAR PHYSICS (CHEP2015), PARTS 1-9 664 (2015) ARTN 042005

Authors:

Michael Boehler, Mikhail Borodin, Andrea Formica, Elizabeth Gallas, Voica Radescu

Designing a future Conditions Database based on LHC experience

21ST INTERNATIONAL CONFERENCE ON COMPUTING IN HIGH ENERGY AND NUCLEAR PHYSICS (CHEP2015), PARTS 1-9 664 (2015) ARTN 042015

Authors:

D Barberis, A Formica, EJ Gallas, G Govi, G Lehman Miotto, A Pfeiffer

Utility of collecting metadata to manage a large scale conditions database in ATLAS

20TH INTERNATIONAL CONFERENCE ON COMPUTING IN HIGH ENERGY AND NUCLEAR PHYSICS (CHEP2013), PARTS 1-6 513 (2014) ARTN 042020

Authors:

EJ Gallas, S Albrand, M Borodin, A Formica

Conditions and configuration metadata for the ATLAS experiment

Journal of Physics: Conference Series 396:PART 5 (2012)

Authors:

EJ Gallas, S Albrand, J Fulachier, F Lambert, KE Pachal, JCL Tseng, Q Zhang

Abstract:

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 a relational database storing directly extracted, refined, reduced, and derived information from system-specific database sources as well as information from non-database sources. This information facilitates a variety of unique dynamic interfaces and provides information to enhance the functionality of other systems. This presentation will give an overview of the components of the COMA system, enumerate its diverse data sources, and give examples of some of the interfaces it facilitates. We list important principles behind COMA schema and interface design, and how features of these principles create coherence and eliminate redundancy among the components of the overall system. In addition, we elucidate how interface logging data has been used to refine COMA content and improve the value and performance of end-user reports and browsers..

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