Open Access
Issue |
EPJ Web of Conf.
Volume 295, 2024
26th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2023)
|
|
---|---|---|
Article Number | 04049 | |
Number of page(s) | 8 | |
Section | Distributed Computing | |
DOI | https://doi.org/10.1051/epjconf/202429504049 | |
Published online | 06 May 2024 |
- Z. Ivezic et al., Astrophys. J. 873, 111 (2019) [CrossRef] [Google Scholar]
- T. Jenness, J.F. Bosch, A. Salnikov, N.B. Lust, N.M. Pease, M. Gower, M. Kowalik, G.P. Dubois-Felsmann, F. Mueller, P. Schellart, 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 [Google Scholar]
- J. Swinbank, T. Axelrod, A. Becker, J. Becla, E. Bellm, J. Bosch, H. Chiang, D. Ciardi, A. Connolly, G. Dubois-Felsmann et al., LDM-151 - Data Management Science Pipelines Design (2020), Vera C. Rubin Observatory Data Management Controlled Document, https://ldm-151.lsst.io/ [Google Scholar]
- J. Bosch et al., An Overview of the LSST Image Processing Pipelines, in Astronomical Data Analysis Software and Systems XXVII, edited by P.J. Teuben, M.W. Pound, B.A. Thomas, E.M. Warner (2019), Vol. 523 of ASP Conf. Ser., p. 521, arXiv:1812.03248 [Google Scholar]
- M. Gower 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 [Google Scholar]
- W. O’Mullane, RTN-001 - Data Preview 0: Definition and planning. (2021), Vera C. Rubin Observatory Technical Note, https://rtn-001.lsst.io/ [Google Scholar]
- G. Mainetti, F. Hernandez, F. Jammes, Q. Le Boulc’h, Experience deploying an analysis facility for the Rubin Observatory’s Legacy Survey of Space and Time (LSST) data, in Proc. of CHEP 2023 (to appear) [Google Scholar]
- W. O’Mullane, Y. Alsayyad, H.F. Chiang, F. Economou, M. Graham, L. Guy, H. Lin, F. Mueller, T. Jenness, C. Slater et al., RTN-041 - Data Preview 0.2 and Operations rehearsal for DRP. (2023), Vera C. Rubin Observatory Technical Note, https://rtn-041.lsst.io/ [Google Scholar]
- LSST Dark Energy Science Collaboration et al., arXiv e-prints (2021), arXiv:2101.04855 [Google Scholar]
- Y. Babuji, A. Woodard, Z. Li, D.S. Katz, B. Clifford, R. Kumar, L. Lacinski, R. Chard, J. Wozniak, I. Foster et al., Parsl: Pervasive Parallel Programming in Python, in 28th ACM International Symposium on High-Performance Parallel and Distributed Computing (HPDC) (2019), https://doi.org/10.1145/3307681.3325400 [Google Scholar]
- Slurm Workload Manager, https://slurm.schedmd.com [Google Scholar]
- https://github.com/LSSTDESC/gen3_workflow [Google Scholar]
- https://github.com/lsst-dm/dp02-processing/ [Google Scholar]
- F. Hernandez, Q. Le Boulc’h, J. Bosch, H.F. Chiang, J. Chiang, T. Jenness, B. White, RTN-029 - Procedure for creating a butler repository at FrDF for Data Preview 0.2 (2022), Vera C. Rubin Observatory Technical Note, https://rtn-029.lsst.io/ [Google Scholar]
- Apptainer, https://apptainer.org [Google Scholar]
- CernVM-FS, https://cernvm.cern.ch/fs [Google Scholar]
- CephFS, https://docs.ceph.com/en/latest/cephfs/ [Google Scholar]
- PostgreSQL relational database, https://www.postgresql.org [Google Scholar]
- T. Jenness, DMTN-177 - Limiting Registry Access During Workflow Execution (2023), Vera C. Rubin Observatory Data Management Technical Note, https://dmtn-177. lsst.io/ [Google Scholar]
- SQLite, https://www.sqlite.org [Google Scholar]
- T. Mkrtchyan, O. Adeyemi, P. Fuhrmann, V. Garonne, D. Litvintsev, A. Millar, A. Rossi, M. Sahakyan, J. Starek, S. Yasar, dCache - storage for advanced scientific use cases and beyond, in EPJ Web of Conferences (2019), Vol. 214, p. 04042 [Google Scholar]
- E. Karavakis, W. Guan, Z. Yang, T. Maeno, W. Torre, J. Adelman-McCarthy, F. Barreiro Megino, K. De, R. Dubois, M. Gower et al., Integrating the PanDA Workload Management System with the Vera C. Rubin Observatory, in Proc. of CHEP 2023 (to appear) [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.