Reproduced Computational Results Report for “Ginkgo: A Modern Linear Operator Algebra Framework for High Performance Computing”

Journal Article · 15 February 2022 · ACM Transactions on Mathematical Software

DOI: https://doi.org/10.1145/3480936 · OSTI ID:1860819

Balos, Cody J. ^[1]

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1. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

The article titled “Ginkgo: A Modern Linear Operator Algebra Framework for High Performance Computing” by Anzt et al. presents a modern, linear operator centric, C++ library for sparse linear algebra. Experimental results in the article demonstrate that Ginkgo is a flexible and user-friendly framework capable of achieving high-performance on state-of-the-art GPU architectures. In this report, the Ginkgo library is installed and a subset of the experimental results are reproduced. Specifically, the experiment that shows the achieved memory bandwidth of the Ginkgo Krylov linear solvers on NVIDIA A100 and AMD MI100 GPUs is redone and the results are compared to what presented in the published article. Upon completion of the comparison, the published results are deemed reproducible.

• Research Organization: Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States); Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
• Sponsoring Organization: USDOE National Nuclear Security Administration (NNSA); USDOE Office of Science (SC)
• Grant/Contract Number: AC05-00OR22725; AC52-07NA27344
• OSTI ID: 1860819
• Report Number(s): LLNL-JRNL-823784; 1036924
• Journal Information: ACM Transactions on Mathematical Software, Journal Name: ACM Transactions on Mathematical Software Journal Issue: 1 Vol. 48; ISSN 0098-3500
• Publisher: Association for Computing MachineryCopyright Statement
• Country of Publication: United States
• Language: English