Abstract
Bespoke Cost Monitoring software collates data on the performance of all aspects of the ATLAS experiment's High Level Trigger software. These data are exported for subsequent analysis offline, and are used to understand the resource usage of the individual trigger selections in terms of the amount of CPU time and the amount of raw detector data which was required to perform the selection. For the LHC's Run 3, the ATLAS High Level Trigger is re-implemented in a multi-threaded framework with both intra-event and inter-event algorithm parallelism. We will describe some of the complications and considerations which arise from monitoring event metrics in a highly parallel environment.
Highlights
The ATLAS experiment [1] at the LHC is a multipurpose particle detector designed to record physics events for a wide range of measurements and searches
The ATLAS Trigger system aims to select the data created by interesting collisions in real time
The High Level Trigger (HLT) software is based on top of the Athena [7] framework, which is used in the ATLAS Collaboration to perform physics simulation, reconstruction and data analysis
Summary
The ATLAS experiment [1] at the LHC is a multipurpose particle detector designed to record physics events for a wide range of measurements and searches. It consists of inner and muon tracking detectors, electromagnetic and hadronic calorimeters, and uses magnetic fields produced by solenoid and toroid magnets. The detector records the signals produced by the collisions delivered by the LHC at a rate of 40 MHz (for proton-proton data taking). Physics data is collected during time periods called Runs. Upgrade break takes place called “Long Shutdown”.
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