Design of a Resilient, High-Throughput, Persistent Storage System for the ATLAS Phase-II DAQ System
1 University of Liverpool, The Oliver Lodge, Oxford St, Liverpool L69 7ZE, United Kingdom
2 European Laboratory for Particle Physics (CERN), Geneva 23, CH-1211, Switzerland
3 Instituto de Ciencias de la Computación UBA-CONICET, Ciudad Universitaria, CABA, Argentina
4 Università degli Studi di Pavia and INFN, Via Agostino Bassi, 6, Pavia, Italy
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Published online: 23 August 2021
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.
© The Authors, published by EDP Sciences, 2021
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