Use Cases of Computational Reproducibility for Scientific Workflows at Exascale

Use Cases of Computational Reproducibility for Scientific Workflows at Exascale

We propose an approach for improved reproducibility that includes capturing and relating provenance characteristics and performance metrics, in a hybrid queriable system, the ProvEn server. The system capabilities are illustrated on two use cases: scientific reproducibility of results in the ACME cl...

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Hauptverfasser: Pouchard, Line, Baldwin, Sterling, Elsethagen, Todd, Gamboa, Carlos, Jha, Shantenu, Raju, Bibi, Stephan, Eric, Tang, Li, Van Dam, Kerstin Kleese
Format: Artikel
Sprache:eng
Schlagworte:
Computer Science - Distributed, Parallel, and Cluster Computing
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Zusammenfassung:We propose an approach for improved reproducibility that includes capturing and relating provenance characteristics and performance metrics, in a hybrid queriable system, the ProvEn server. The system capabilities are illustrated on two use cases: scientific reproducibility of results in the ACME climate simulations and performance reproducibility in molecular dynamics workflows on HPC computing platforms.
DOI:10.48550/arxiv.1805.00967