Abstract
The ATLAS experiment will undergo a major upgrade to take advantage of the new conditions provided by the upgraded High-Luminosity LHC. The Trigger and Data Acquisition system (TDAQ) will record data at unprecedented rates: the detectors will be read out at 1 MHz generating around 5 TB/s of data. The Dataflow system (DF), component of TDAQ, introduces a novel design: readout data are buffered on persistent storage while the event filtering system analyses them to select 10000 events per second for a total recorded throughput of around 60 GB/s. This approach allows for decoupling the detector activity from the event selection process. New challenges then arise for DF: design and implement a distributed, reliable, persistent storage system supporting several TB/s of aggregated throughput while providing tens of PB of capacity. In this paper we first describe some of the challenges that DF is facing: data safety with persistent storage limitations, indexing of data at high-granularity in a highly-distributed system, and high-performance management of storage capacity. Then the ongoing R&D to address each of the them is presented and the performance achieved with a working prototype is shown.
Highlights
Over the few years the ATLAS experiment[1] at CERN will undergo a major upgrade to adapt and take advantage of the new conditions provided by the High-Luminosity LHC[2] (Phase-II upgrade)
The upgrade involves all detectors as well as the Trigger and Data Acquisition system[3] (TDAQ) which is responsible for collecting data from the detectors, selecting the interesting fraction of them, and recording the selected data
To benchmark Dataflow system (DF) two auxiliary applications are used to act as the Readout and the Event Filter systems
Summary
Over the few years the ATLAS experiment[1] at CERN will undergo a major upgrade to adapt and take advantage of the new conditions provided by the High-Luminosity LHC[2] (Phase-II upgrade). Overall DF is a large-capacity high-throughput distributed storage system indexing every detector data fragment, that needs to provide high service availability and data safety. A previous evaluation of the performance of distributed file systems for ATLAS DAQ[7] showed that these specific solutions do not provide all the requirements needed for DF.
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
