Abstract

In 2017, NA62 recorded over a petabyte of raw data, collecting around a billion events per day of running. Data are collected in bursts of 3-5 seconds, producing output files of a few gigabytes. A typical run, a sequence of bursts with the same detector configuration and similar experimental conditions, contains 1500 bursts and constitutes the basic unit for offline data processing. A sample of 100 random bursts is used to make timing calibrations of all detectors, after which every burst in the run is reconstructed. Finally the reconstructed events are filtered by physics channel with an average reduction factor of 20, and data quality metrics are calculated. Initially a bespoke data processing solution was implemented using a simple finite state machine with limited production system functionality. In 2017, the ATLAS Tier-0 team offered the use of their production system, together with the necessary support. Data processing workflows were rewritten with better error-handling and I/O operations were minimised, the reconstruction software was improved and conditions data handling was changed to follow best practices suggested by the HEP Software Foundation conditions database working group. This contribution describes the experience gained in using these tools and methods for data-processing on a petabyte scale experiment.

Details

Title
Data Preparation for NA62
Author
Laycock, Paul
Section
T2 - Offline computing
Publication year
2019
Publication date
2019
Publisher
EDP Sciences
ISSN
21016275
e-ISSN
2100014X
Source type
Conference Paper
Language of publication
English
ProQuest document ID
2297141314
Copyright
© 2019. This work is licensed under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and conditions, you may use this content in accordance with the terms of the License.