Published August 22, 2019 | Version v0.2
Dataset Open

Cloud-Repro: Reproducible Workflow on a Public Cloud for Computational Fluid Dynamics

  • 1. The George Washington University

Description

In a new effort to make our research transparent and reproducible by others, we developed a workflow to run computational studies on a public cloud. It uses Docker containers to create an image of the application software stack. We also adopt several tools that facilitate creating and managing virtual machines on compute nodes and submitting jobs to these nodes. The configuration files for these tools are part of an expanded "reproducibility package" that includes workflow definitions for cloud computing, in addition to input files and instructions. This facilitates re-creating the cloud environment to re-run the computations under the same conditions.

The present Zenodo dataset contains all secondary data required to reproduce the figures of the manuscript ("Reproducible Workflow on a Public Cloud for Computational Fluid Dynamics") without running the CFD simulations again.

Notes

Corresponds to GitHub repository https://github.com/barbagroup/cloud-repro, plus secondary data files (not version-controlled). Funded by NSF Grant No. CCF-1747669.

Files

cloud-repro.zip

Files (13.1 GB)

Name Size Download all
md5:5790c7e5e64cab4bc683cff6a47a20f0
13.1 GB Preview Download