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Samurai
The main goal of samurai is to provide a new data structure based on intervals and algebra of sets to handle efficiently adaptive mesh refinement methods based on a cartesian grid. Such an approach has to be versatile enough to handle both AMR and multi-resolution methods.
Overview
Repository
License
OSS::BSD
Documentation
Discussion
1. Exascale Bottlenecks Addressed
B6 Data management B7 Exascale algorithms B9 Resilience, robustness and accuracy B10 Scientific productivity B11 Reproducibility and replicability
2. Criteria Evaluation
2.1. Packaging
Software should be packaged (preferably using Spack or Guix package formats) and published in public repositories.
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Packages exist
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Available in Spack
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Available in Guix-HPC
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Docker image available
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Apptainer/Singularity available
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Spack: github.com/spack/spack
2.2. Testing & CI/CD
Software should include validation tests triggered through automated mechanisms.
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Unit tests exist
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Continuous Integration configured
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CI runs on each release
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Benchmarking tests exist
2.3. Repository & Contributions
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Public source repository available
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Supports contributions via pull requests
Repository: github.com/hpc-maths/samurai
2.4. License
Sources should be published under a clearly-identified free software license.
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License clearly stated
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FLOSS license (FSF/OSI conformant)
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SPDX identifiers used
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REUSE compliant
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BSD
2.5. Documentation
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Documentation exists
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Easily browsable online
Documentation: hpc-math-samurai.readthedocs.io/