Melissa: coordinating large-scale ensemble runs for deep learning and sensitivity analyses

C Fortran Python Submitted 17 February 2023 • Published 16 June 2023
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Editor: @diehlpk (all papers)
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Authors

Marc Schouler (0000-0002-3708-4135), Robert Alexander Caulk (0000-0001-5618-8629), Lucas Meyer (0000-0001-5386-5997), Théophile Terraz, Christoph Conrads, Sebastian Friedemann, Achal Agarwal (0000-0002-3216-4769), Juan Manuel Baldonado, Bartłomiej Pogodziński, Anna Sekuła (0000-0003-3524-3160), Alejandro Ribes, Bruno Raffin

Citation

Schouler et al., (2023). Melissa: coordinating large-scale ensemble runs for deep learning and sensitivity analyses. Journal of Open Source Software, 8(86), 5291, https://doi.org/10.21105/joss.05291

@article{Schouler2023, doi = {10.21105/joss.05291}, url = {https://doi.org/10.21105/joss.05291}, year = {2023}, publisher = {The Open Journal}, volume = {8}, number = {86}, pages = {5291}, author = {Schouler, Marc and Caulk, Robert Alexander and Meyer, Lucas and Terraz, Théophile and Conrads, Christoph and Friedemann, Sebastian and Agarwal, Achal and Baldonado, Juan Manuel and Pogodziński, Bartłomiej and Sekuła, Anna and Ribes, Alejandro and Raffin, Bruno}, title = {Melissa: coordinating large-scale ensemble runs for deep learning and sensitivity analyses}, journal = {Journal of Open Source Software} }
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supercomputing sensitivity analysis deep learning distributed systems orchestration

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ISSN 2475-9066