DOE OSTI · 2578686
HPC-driven computational reproducibility in numerical relativity codes: a use case study with IllinoisGRMHD
Abstract
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 produceconsistent numerical results for physical quantities. In this manuscript, we test the feasibility of reproducing scientific results obtained using theIllinoisGRMHDcode that is part of an open-source community software for simulation in relativistic astrophysics, theEinstein Toolkit. We verify that numerical results of simulating a single isolated neutron star withIllinoisGRMHDcan be reproduced, and compare them to results reported by the code authors in 2015. We use two different supercomputers: Expanse at SDSC, and Stampede2 at TACC. By compiling the source code archived along with the paper on both Expanse and Stampede2, we find thatIllinoisGRMHDreproduces results published in its announcement paper up to errors comparable to round-off level changes in initial data parameters. We also verify that a current version ofIllinoisGRMHDreproduces these results once we account for bug fixes which have occurred since the original publication.
Explore related subjects
Keep this discovery
Explore connections, maps & timelines
Luo, Yufeng (ORCID:0000000246230683), Zhang, Qian (ORCID:0000000315497358), Haas, Roland (ORCID:0000000314246178), Etienne, Zachariah (ORCID:0000000268389185), Allen, Gabrielle (ORCID:0000000331065360). 2023-12-22. HPC-driven computational reproducibility in numerical relativity codes: a use case study with IllinoisGRMHD. https://doi.org/10.1088/1361-6382%2Fad13c5
Cite the original work for its findings. Save a collection to share your selection of sources.