Evolution of grid-wide access to database resident information in ATLAS using Frontier
Journal of Physics: Conference Series 396:PART 5 (2012)
Abstract:
The ATLAS experiment deployed Frontier technology worldwide during the initial year of LHC collision data taking to enable user analysis jobs running on the Worldwide LHC Computing Grid to access database resident data. Since that time, the deployment model has evolved to optimize resources, improve performance, and streamline maintenance of Frontier and related infrastructure. In this presentation we focus on the specific changes in the deployment and improvements undertaken, such as the optimization of cache and launchpad location, the use of RPMs for more uniform deployment of underlying Frontier related components, improvements in monitoring, optimization of fail-over, and an increasing use of a centrally managed database containing site specific information (for configuration of services and monitoring). In addition, analysis of Frontier logs has allowed us a deeper understanding of problematic queries and understanding of use cases. Use of the system has grown beyond user analysis and subsystem specific tasks such as calibration and alignment, extending into production processing areas, such as initial reconstruction and trigger reprocessing. With a more robust and tuned system, we are better equipped to satisfy the still growing number of diverse clients and the demands of increasingly sophisticated processing and analysis..Using TAGs to speed up the ATLAS analysis process
Journal of Physics: Conference Series 331:PART 3 (2011)
Abstract:
In the ATLAS experiment, Tag Data, or short TAG, are event-level metadata -thumbnail information about events to support efficient identification and selection of events of interest to a given analysis. TAG quantities range from detector status and trigger information to basic physics quantities, e. g. the number of loose electrons candidates and kinematic information for a limited number of these candidates sorted by their transverse momentum. The average TAG size per event is around 1kB, which is a factor 100 smaller than the Analysis Object Data (AOD) used for physics analysis. TAGs are primarily produced from AODs and stored in ROOT files. For easier access and usability TAGs are also stored in a database. Queries to the database can produce again TAG files. In a standard ATLAS analysis job, TAGs can be used to preselect events based on the TAG quantities before accessing the full AOD content. This allows for a significant speed up of the processing time. This paper will discuss the different analysis work flows using TAGs and compare them with other analysis work flows within ATLAS. Further, the performance for preselecting events using either directly AODs or TAG files is measured and compared. Peak performance is estimated on a single machine with local disk access, while more realistic performance is estimated using Grid like data access.Metadata aided run selection at ATLAS
Journal of Physics: Conference Series 331:PART 4 (2011)
Abstract:
Management of the large volume of data collected by any large scale scientific experiment requires the collection of coherent metadata quantities, which can be used by reconstruction or analysis programs and/or user interfaces, to pinpoint collections of data needed for specific purposes. In the ATLAS experiment at the LHC, we have collected metadata from systems storing non-event-wise data (Conditions) into a relational database. The Conditions metadata (COMA) database tables not only contain conditions known at the time of event recording, but also allow for the addition of conditions data collected as a result of later analysis of the data (such as improved measurements of beam conditions or assessments of data quality). A new web based interface called "runBrowser" makes these Conditions Metadata available as a Run based selection service. runBrowser, based on PHP and JavaScript, uses jQuery to present selection criteria and report results. It not only facilitates data selection by conditions attributes, but also gives the user information at each stage about the relationship between the conditions chosen and the remaining conditions criteria available. When a set of COMA selections are complete, runBrowser produces a human readable report as well as an XML file in a standardized ATLAS format. This XML can be saved for later use or refinement in a future runBrowser session, shared with physics/detector groups, or used as input to ELSSI (event level Metadata browser) or other ATLAS run or event processing services.The D0 Run IIb luminosity measurement
Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 698 (2013) 208-223
Abstract:
An assessment of the recorded integrated luminosity is presented for data collected with the D0 detector at the Fermilab Tevatron Collider from June 2006 to September 2011 (Run IIb). In addition, a measurement of the effective cross-section for inelastic interactions, also referred to as the luminosity constant, is reported. This measurement incorporates new features that lead to a substantial improvement in the precision of the result. A luminosity constant of σLM=48.3±1.9±0.6mb is obtained, where the first uncertainty is due to the accuracy of the inelastic cross-section used by both CDF and D0, and the second uncertainty is due to D0 sources. The recorded luminosity for the highest ET jet trigger is Lrec=9. 2±0.4fb-1, with a relative uncertainty of 4.3%. © 2012 Elsevier B.V.Top quark search with the D0 1992-1993 data sample
Physical Review D 52:9 (1995) 4877-4919