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Use Cases of Computational Reproducibility for Scientific Workflows at Exascale

Published 20 Apr 2018 in cs.DC | (1805.00967v1)

Abstract: 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.

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