Speaker
Wim Lavrijsen
(LBNL)
Description
The offline and high-level trigger software for the ATLAS experiment has now fully
migrated to a scheme which allows large tasks to be broken down into many
functionally independent components. These components can focus, for example, on
conditions or physics data access, on purely mathematical or combinatorial algorithms
or on providing detector-specific geometry and calibration information. In addition
to other advantages, the software components can be heavily re-used at different
levels (sub-detector tasks, event reconstruction, physics analysis) and on different
running conditions (LHC data, trigger regions, cosmics data) with only little
adaptations. A default setting therefore has to be provided for each component
allowing these adaptations to be made. End-user jobs contain many of these small
components, most of which the end-user is totally unaware. There is therefore a big
semantic discrepancy between how the end-user thinks about a specific job's
configuration and how the configuration is packaged with the individual components
making up the job. This paper presents a partly automated system which allows
component developers and aggregators to build a configuration ranging over all the
above levels, such that e.g. component developers can use a low-level configuration,
sub-detector coordinates work with functional sequences and the end user can think in
physics processes. This system of python-based job configurations is flexible but
easy to keep internally consistent and avoids possible clashes when a component is
re-used in a different context. The paper also presents a working system used to
configure the new ATLAS track reconstruction software.
Primary authors
Wim Lavrijsen
(LBNL)
Wolfgang Liebig
(CERN)
Co-authors
Andreas Salzburger
(University of Innsbruck)
David Rousseau
(LAL)
Paolo Calafiura
(LBNL)
Peter Loch
(University of Arizona)
