The ATLAS Data Carousel Project Status

Mikhail Borodin,Alessandro Di Girolamo,Siarhei Padolski,Edward Karavakis,Tatiana Korchuganova,Mario Lassnig,Xin Zhao,Tadashi Maeno,Alexei Klimentov,C Biscarat,G.A Stewart,S Roiser,B Hegner,S Campana,C.I Rovelli

doi:10.1051/epjconf/202125102006

Abstract

The High Luminosity upgrade to the LHC, which aims for a tenfold increase in the luminosity of proton-proton collisions at an energy of 14 TeV, is expected to start operation in 2028/29 and will deliver an unprecedented volume of scientific data at the multi-exabyte scale. This amount of data has to be stored, and the corresponding storage system must ensure fast and reliable data delivery for processing by scientific groups distributed all over the world. The present LHC computing and data management model will not be able to provide the required infrastructure growth, even taking into account the expected hardware technology evolution. To address this challenge, the Data Carousel R&D project was launched by the ATLAS experiment in the fall of 2018. State-of-the-art data and workflow management technologies are under active development, and their current status is presented here.

Highlights

The overarching common challenge for particle physics experiments is data handling
Technologies that will address the High Luminosity LHC (HL-LHC) computing challenges may be applicable to other scientific communities, such as SKAO, DUNE, Vera Rubin Observatory, BELLE II, and JUNO for the management of large-scale data volumes
Tasks were released only when most of the input data were staged-in from tape storage, which led to a significant delay before processing could start and required huge disk caches for the entire processing period. Intelligent Data Delivery Service (iDDS) propagates the detailed information on the input data status from Rucio to the Job Execution and Definition Interface (JEDI), as shown in Figure 4, and allows JEDI to incrementally release tasks so that tasks can start processing even if input data are only partially staged-in. iDDS has been in production since the middle of 2020, and it has solved the issue with the delayed processing in bulk reprocessing campaigns

Summary

Introduction

The overarching common challenge for particle physics experiments is data handling. The evolution of the computing facilities and the way storage will be organized and consolidated, will play a key role in how the possible shortage of resources will be addressed by the LHC [1] experiments. To address the HL-LHC distributed data handling challenge ATLAS [2] has launched the Data Carousel R&D project to study the feasibility of getting input data from tape directly for various ATLAS workflows. The Data Carousel is the orchestration between the workflow management systems ProdSys and PanDA [3][4], the distributed data management (DDM) system Rucio [5], and the tape services. Phase III: Run Data Carousel at scale in production for the selected workflows with an ultimate goal to have it operational before LHC Run 3 in 2022. Derivation production was demonstrated at small scale, and it will be in full production in 2021

ATLAS Run 2 data reprocessing in Data Carousel mode

New distributed software components

Distributed data management

Improvements on tape systems from sites

Summary and future plans