HPC-driven computational reproducibility in numerical relativity codes: A use case study with IllinoisGRMHD
Yufeng Luo, Qian Zhang, Roland Haas, Zachariah B. Etienne, Gabrielle, Allen

TL;DR
This study demonstrates that scientific results from the IllinoisGRMHD code in relativistic astrophysics can be reliably reproduced across different supercomputers and software versions, ensuring computational reproducibility in scientific computing.
Contribution
It provides a practical case study on achieving reproducibility in numerical relativity codes across diverse computing environments and software versions.
Findings
Reproduced results are consistent with original publication within round-off errors.
Reproducibility is maintained across different supercomputers (Expanse and Stampede2).
Updated code versions still reproduce previous results after bug fixes.
Abstract
Reproducibility of results is a cornerstone of the scientific method. Scientific computing encounters two challenges when aiming for this goal. Firstly, reproducibility should not depend on details of the runtime environment, such as the compiler version or computing environment, so results are verifiable by third-parties. Secondly, different versions of software code executed in the same runtime environment should produce consistent numerical results for physical quantities. In this manuscript, we test the feasibility of reproducing scientific results obtained using the IllinoisGRMHD code that is part of an open-source community software for simulation in relativistic astrophysics, the Einstein Toolkit. We verify that numerical results of simulating a single isolated neutron star with IllinoisGRMHD can be reproduced, and compare them to results reported by the code authors in 2015. We…
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Taxonomy
TopicsAdvanced Data Storage Technologies · Distributed and Parallel Computing Systems · Scientific Computing and Data Management
