Abstract
Over the next few years, the LHC will prepare for the upcoming High-Luminosity upgrade in which it is expected to deliver ten times more pp collisions. This will create a harsher radiation environment and higher detector occupancy. In this context, the ATLAS experiment, one of the general purpose experiments at the LHC, plans substantial upgrades to the detectors and to the trigger system in order to efficiently select events. Similarly, the Data Acquisition System (DAQ) will have to redesign the data-flow architecture to accommodate for the large increase in event and data rates. The Phase-II DAQ design involves a large distributed storage system that buffers data read out from the detector, while a computing farm (Event Filter) analyzes and selects the most interesting events. This system will have to handle 5.2 TB/s of input data for an event rate of 1 MHz and provide access to 3 TB/s of these data to the filtering farm. A possible implementation for such a design is based on distributed file systems (DFS) which are becoming ubiquitous among the big data industry. Features of DFS such as replication strategies and smart placement policies match the distributed nature and the requirements of the new data-flow system. This paper presents an up-to-date performance evaluation of some of the DFS currently available: GlusterFS, HadoopFS and CephFS. After characterization of the future data-flow systems workload, we report on small-scale raw performance and scalability studies. Finally, we conclude on the suitability of such systems to the tight constraints expected for the ATLAS experiment in phase-II and, in general, what benefits the HEP community can take from these storage technologies.
Highlights
The Large Hadron Collider (LHC) is a particle accelerator that collides proton bunches at a design center-of-mass energy of 14 TeV and at a rate of 40 MHz
The Dataflow system is responsible for buffering, transporting and formatting the event data, acting as an interface between the Readout and the trigger systems
A more refined selection is applied by the Event Filter (EF) which takes as input the L0 events stored in the Dataflow system
Summary
The Large Hadron Collider (LHC) is a particle accelerator that collides proton bunches at a design center-of-mass energy of 14 TeV and at a rate of 40 MHz. KEYWORDS Distributed file systems · storage technologies · software-defined storage · ATLAS Data Acquisition · Dataflow 2. Phase-II TDAQ Architecture In order to take advantage of the full potential of the HL-LHC the trigger and data acquisition systems of the ATLAS experiment will be completely redesigned. The Dataflow system is responsible for buffering, transporting and formatting the event data, acting as an interface between the Readout and the trigger systems.
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