The Rubin Observatory’s Legacy Survey of Space and Time DP0.2 processing campaign at CC-IN2P3

Author:

Le Boulc’h Quentin,Hernandez Fabio,Mainetti Gabriele

Abstract

The Vera C. Rubin Observatory, currently in construction in Chile, will start performing the Legacy Survey of Space and Time (LSST) in 2025 for 10 years. Its 8.4-meter telescope will survey the southern sky in less than 4 nights in six optical bands, and repeatedly generate about 2 000 exposures per night, corresponding to a data volume of about 20 TiB every night. Three data facilities are preparing to contribute to the production of the annual data releases: the US Data Facility will process 35% of the raw data, the UK data facility will process 25% of the raw data and the French data facility, operated by CC-IN2P3, will locally process the remaining 40% of the raw data. In the context of the Data Preview 0.2 (DP0.2), the Data Release Production pipelines have been executed on the DC-2 simulated dataset (generated by the Dark Energy Science Collaboration, DESC). This dataset includes 20 000 simulated exposures, representing 300 square degrees of Rubin images with a typical depth of 5 years. DP0.2 ran at the Interim Data Facility (based on Google cloud), and the full exercise was independently replicated at CC-IN2P3. During this exercise, 3 PiB of data and more than 200 million files were produced. In this contribution we will present a detailed description of the system that we set up to perform this processing campaign using CC-IN2P3’s computing and storage infrastructure. Several topics will be addressed: workflow generation and execution, batch job submission, memory and I/O requirements, etc. We will focus on the issues that arose during this campaign and how we addressed them and will present some perspectives after this exercise.

Publisher

EDP Sciences

Reference22 articles.

1. LSST: From Science Drivers to Reference Design and Anticipated Data Products

2. Jenness T., Bosch J.F., Salnikov A., Lust N.B., Pease N.M., Gower M., Kowalik M., Dubois-Felsmann G.P., Mueller F., Schellart P., The Vera C. Rubin Observatory Data Butler and pipeline execution system, in “Software and Cyberinfrastructure for Astronomy VII” (2022), Vol. 12189 of Proc. SPIE, p. 1218911, arXiv:2206.14941

3. Swinbank J., Axelrod T., Becker A., Becla J., Bellm E., Bosch J., Chiang H., Ciardi D., Connolly A., Dubois-Felsmann G. et al., LDM-151 - Data Management Science Pipelines Design (2020), Vera C. Rubin Observatory Data Management Controlled Document, https://ldm-151.lsst.io/

4. Bosch J. et al., An Overview of the LSST Image Processing Pipelines, in Astronomical Data Analysis Software and Systems XXVII, edited by Teuben P.J., Pound M.W., Thomas B.A., Warner E.M. (2019), Vol. 523 of ASP Conf. Ser., p. 521, arXiv:1812.03248

5. Gower M. et al., Adding Workflow Management Flexibility to LSST Pipelines Execution, in Astronomical Data Analysis Software and Systems XXXII (2023), Vol. in press of ASP Conf. Ser., arXiv:2211.15795

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