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[PRE REVIEW]: gpu-ISTL - Extending OPM Flow with GPU Linear Solvers #7524
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Five most similar historical JOSS papers: Ginkgo: A high performance numerical linear algebra library SPbLA: The Library of GPGPU-powered Sparse Boolean Linear Algebra Operations libCEED: Fast algebra for high-order element-based discretizations iharm3D: Vectorized General Relativistic Magnetohydrodynamics The 2DECOMP&FFT library: an update with new CPU/GPU capabilities |
@multitalentloes - Our apologies for the delay in getting this started. Something went wrong internally, but it's now fixed. |
I note that this is a very large repo. It appears that you are submitted a part of this for review, as an element of the full repo, but this is not completely clear. Can you identify the branch/files/etc that is the submitted contribution? Additionally, the paper is about 50% longer than recommended for a JOSS submission. I wonder if there's part of this that could be place in the documentation or repo, then pointed to there, rather than being in the paper? The performance case study perhaps? |
Hello Daniel, thank you very much for initiating the pre-review. The contributions described in this article predominantly reside in the
There are other minor parts of the repository which have been added to support the
Regarding the length of the article; I think the section demonstrating that the current framework can yield significant speedup over conventional processors when running OPM Flow makes an important point, so I would like to keep it in some shape or form. We can maybe move |
Submitting author: @multitalentloes (Tobias Meyer Andersen)
Repository: https://github.com/OPM/opm-simulators
Branch with paper.md (empty if default branch): joss_gpuistl_paper
Version: 2024.10
Editor: Pending
Reviewers: Pending
Managing EiC: Daniel S. Katz
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