ATLAS HL-LHC Demonstrators with Data Carousel: Data-on-Demand and Tape Smart Writing
Abstract:
The High Luminosity upgrade to the LHC (HL-LHC) is expected to
deliver scientific data at the multi-exabyte scale. To tackle this unprecedented
data storage challenge, the ATLAS experiment initiated the Data Carousel
project in 2018. Data Carousel is a tape-driven workflow in which bulk pro-
duction campaigns with input data resident on tape are executed by staging and
promptly processing a sliding window to disk buffer such that only a small frac-
tion of inputs are pinned on disk at any one time. Put in ATLAS production
before Run3, Data Carousel continues to be our focus for seeking new opportu-
nities in disk space savings, and enhancing tape usage throughout the ATLAS
Distributed Computing (ADC) environment. These efforts are highlighted by
two recent ATLAS HL-LHC demonstrator projects: data-on-demand and tape
smart writing. In this paper, we will discuss the recent studies and outcomes
from these projects. The research was conducted together with site experts at CERN and Tier-1 centers.
deliver scientific data at the multi-exabyte scale. To tackle this unprecedented
data storage challenge, the ATLAS experiment initiated the Data Carousel
project in 2018. Data Carousel is a tape-driven workflow in which bulk pro-
duction campaigns with input data resident on tape are executed by staging and
promptly processing a sliding window to disk buffer such that only a small frac-
tion of inputs are pinned on disk at any one time. Put in ATLAS production
before Run3, Data Carousel continues to be our focus for seeking new opportu-
nities in disk space savings, and enhancing tape usage throughout the ATLAS
Distributed Computing (ADC) environment. These efforts are highlighted by
two recent ATLAS HL-LHC demonstrator projects: data-on-demand and tape
smart writing. In this paper, we will discuss the recent studies and outcomes
from these projects. The research was conducted together with site experts at CERN and Tier-1 centers.
| Zugehörige Institution(en) am KIT | Scientific Computing Center (SCC) |
| Publikationstyp | Zeitschriftenaufsatz |
| Publikationsjahr | 2025 |
| Sprache | Englisch |
| Identifikator | ISSN: 2100-014X KITopen-ID: 1000188061 |
| Erschienen in | EPJ Web of Conferences |
| Verlag | EDP Sciences |
| Band | 337 |
| Seiten | Art.-Nr.: 01350 |
| Bemerkung zur Veröffentlichung | 27th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2024), Krakow, 19th-25th October 2024 |
| Vorab online veröffentlicht am | 07.10.2025 |
| Nachgewiesen in | Scopus OpenAlex |