LLNL/sundials
Dec 2024 – Sep 2025
5 Months active
Languages Used
CC++CMakeLaTeXMarkdownPythonreStructuredTextFortran
Technical Skills
Build System ConfigurationCC++Numerical AnalysisODE SolversSoftware Development
Daniel R. Reynolds
PROFILE
Daniel R. Reynolds
Over five months, Reynolds contributed to the LLNL/sundials repository by developing adaptive multi-rate integration methods and expanding command-line configurability across solver modules. He implemented adaptive MRI solvers in ARKODE, enhancing modeling flexibility and robustness, and introduced runtime SetOptions to streamline solver parameter tuning. Reynolds also centralized validation logic for vector operations, improved error messaging in CMake build configurations, and maintained project governance through documentation and authorship updates. His work involved C, C++, and Python, with a focus on numerical analysis, build system configuration, and scripting. These contributions improved reliability, maintainability, and user experience for scientific computing workflows.
Overall Statistics
Feature vs Bugs
63%Features
Repository Contributions
8Total
Bugs
3
Commits
8
Features
5
Lines of code
48,117
Activity Months5
Your Network
9 peopleSame Organization
@smu.edu2
Work History
September 2025
2 Commits • 1 Features
Sep 1, 20252025-09 monthly summary for LLNL/sundials: Key features delivered and significant fixes focusing on MRI-HTol adaptivity and project governance.
2 Commits • 1 Features
Sep 1, 20252025-09 monthly summary for LLNL/sundials: Key features delivered and significant fixes focusing on MRI-HTol adaptivity and project governance.
September 2025
August 2025
1 Commits • 1 Features
Aug 1, 2025Monthly summary for 2025-08 focusing on key accomplishments and business value in the LLNL/sundials repository. The month centered on delivering a high-impact feature that enhances configurability and experiment throughput across solver modules.
August 2025
1 Commits • 1 Features
Aug 1, 2025Monthly summary for 2025-08 focusing on key accomplishments and business value in the LLNL/sundials repository. The month centered on delivering a high-impact feature that enhances configurability and experiment throughput across solver modules.
February 2025
1 Commits
Feb 1, 2025February 2025: In LLNL/sundials, focused on robustness of data visualization tooling. Key deliverable: fixed the Python plotting script by removing an erroneous data-dimension sanity check that misvalidated dimensions for both serial and parallel outputs, ensuring correct processing across configurations. This was implemented in commit e5dfac9a4af86c5480734aa8428c7c7277f00ae8. Overall, improved reliability of plots and reduced downstream debugging, delivering business value by ensuring accurate data representation across output configurations. Technologies demonstrated include Python scripting, debugging, and Git workflows, with attention to cross-config validation.
1 Commits
Feb 1, 2025February 2025: In LLNL/sundials, focused on robustness of data visualization tooling. Key deliverable: fixed the Python plotting script by removing an erroneous data-dimension sanity check that misvalidated dimensions for both serial and parallel outputs, ensuring correct processing across configurations. This was implemented in commit e5dfac9a4af86c5480734aa8428c7c7277f00ae8. Overall, improved reliability of plots and reduced downstream debugging, delivering business value by ensuring accurate data representation across output configurations. Technologies demonstrated include Python scripting, debugging, and Git workflows, with attention to cross-config validation.
February 2025
January 2025
2 Commits • 2 Features
Jan 1, 2025January 2025 monthly summary for LLNL/sundials (ARKODE): Key features delivered include contributor attribution documentation updates across README.md, the ARKODE guide (Landing.rst, conf.py), and LaTeX/texinfo cover pages recognizing Mustafa Aggul as a contributor for the ARKODE LSRKStep module, and a refactor to centralize N_Vector validation checks within ARKODE to improve validation clarity and maintainability. No major bugs were reported this month. Overall impact: enhanced contributor recognition, streamlined validation logic, and improved codebase maintainability, contributing to faster feature delivery and reduced risk in future ARKODE changes. Technologies demonstrated: multi-format documentation (Markdown, reStructuredText, LaTeX/texinfo), git-based collaboration, refactoring, and N_Vector API understanding.
January 2025
2 Commits • 2 Features
Jan 1, 2025January 2025 monthly summary for LLNL/sundials (ARKODE): Key features delivered include contributor attribution documentation updates across README.md, the ARKODE guide (Landing.rst, conf.py), and LaTeX/texinfo cover pages recognizing Mustafa Aggul as a contributor for the ARKODE LSRKStep module, and a refactor to centralize N_Vector validation checks within ARKODE to improve validation clarity and maintainability. No major bugs were reported this month. Overall impact: enhanced contributor recognition, streamlined validation logic, and improved codebase maintainability, contributing to faster feature delivery and reduced risk in future ARKODE changes. Technologies demonstrated: multi-format documentation (Markdown, reStructuredText, LaTeX/texinfo), git-based collaboration, refactoring, and N_Vector API understanding.
December 2024
2 Commits • 1 Features
Dec 1, 2024December 2024 monthly summary for LLNL/sundials focused on reliability improvements and solver capability expansion. Delivered explicit configuration feedback to prevent build-time failures and expanded adaptive MRI capabilities within ARKODE, strengthening both developer experience and modeling versatility. Outcomes include clearer error messaging for CUDA/extended precision incompatibilities and adaptive multi-rate MRI methods (MRI-GARK, MRI-SR, MERK) with validation tests.
2 Commits • 1 Features
Dec 1, 2024December 2024 monthly summary for LLNL/sundials focused on reliability improvements and solver capability expansion. Delivered explicit configuration feedback to prevent build-time failures and expanded adaptive MRI capabilities within ARKODE, strengthening both developer experience and modeling versatility. Outcomes include clearer error messaging for CUDA/extended precision incompatibilities and adaptive multi-rate MRI methods (MRI-GARK, MRI-SR, MERK) with validation tests.
December 2024
Activity
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Quality Metrics
Correctness93.8%
Maintainability92.6%
Architecture90.0%
Performance82.6%
AI Usage20.0%
Skills & Technologies
Programming Languages
CC++CMakeCUDAFortranHIPLaTeXMakefileMarkdownPython
Technical Skills
API DesignAdaptive Time SteppingAuthorship UpdatesBug FixingBuild System ConfigurationCC ProgrammingC++C/C++ DevelopmentCode RefactoringCommand-Line Interface DevelopmentConfiguration ManagementCopyright ManagementDocumentationError Control
Repositories Contributed To
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