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)
Reviewers: @acrlakshman (all reviews), @NoujoudNader (all reviews)

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 = {Marc Schouler and Robert Alexander Caulk and Lucas Meyer and Théophile Terraz and Christoph Conrads and Sebastian Friedemann and Achal Agarwal and Juan Manuel Baldonado and Bartłomiej Pogodziński and Anna Sekuła and Alejandro Ribes and Bruno Raffin}, 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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