Adrian Chitan

The ATLAS Trigger and Data Acquisition (TDAQ) is a large, distributed system composed of several thousands interconnected computers and tens of thousands software processes (applications). Applications produce a large amount of operational messages at the order of 104 messages per second, which need to be reliably stored and delivered to TDAQ operators in a quasi real-time manner, and also be available for post-mortem analysis by experts.

Abstract The ATLAS experiment at the Large Hadron Collider (LHC) operated very successfully in the years 2008 to 2013, a period identified as Run 1. ATLAS achieved an overall data-taking efficiency of 94%, largely constrained by the irreducible dead-time introduced to accommodate the limitations of the detector read-out electronics. Out of the 6% dead-time only about 15% could be attributed to the central trigger and DAQ system, and out of these, a negligible fraction was due to the Control and Configuration sub-system. Despite these achievements, and in order to improve the efficiency of the whole DAQ system in Run 2 (2015-2018), the first long LHC shutdown (2013-2014) was used to carry out a complete revision of the control and configuration software. The goals were three-fold: properly accommodate additional requirements that could not be seamlessly included during steady operation of the system; re-factor software that had been repeatedly modified to include new features, thus becoming less maintainable; and seize the opportunity of modernizing software written even before Run 1, thus profiting from the rapid evolution in IT technologies. This upgrade was carried out retaining the important constraint of minimally impacting the mode of operation of the system and public APIs, in order to maximize the acceptance of the changes by the large user community. This paper presents, using a few selected examples, how the work was approached and which new technologies were introduced into the ATLAS DAQ system, and how they were performing in course of Run 2. Despite these being specific to this system, many solutions can be considered and adapted to different distributed DAQ systems.

The ATLAS experiment at the Large Hadron Collider (LHC) operated very successfully in the years 2008 to 2018, in two periods identified as Run 1 and Run 2. ATLAS achieved an overall data-taking efficiency of 94%, largely constrained by the irreducible dead-time introduced to accommodate the limitations of the detector read-out electronics. Out of the 6% dead-time only about 15% could be attributed to the central trigger and DAQ system, and out of these, a negligible fraction was due to the Control and Configuration subsystem. Despite these achievements, and in order to improve even more the already excellent efficiency of the whole DAQ system in the coming Run 3, a new campaign of software updates was launched for the second long LHC shutdown (LS2). This paper presents, using a few selected examples, how the work was approached and which new technologies were introduced into the ATLAS Control and Configuration software. Despite these being specific to this system, many solutions can be considered and adapted to different distributed DAQ systems.