amrvac/AGILE-experimental
Nov 2024 – Jun 2025
4 Months active
Languages Used
FortranMakefileMarkdownPerlPythonShellTOMLMake
Technical Skills
Code FormattingCode RefactoringDebuggingFinite Volume MethodFortranFortran Programming
Johan Hidding
PROFILE
Johan Hidding
Jorrit Hidding modernized and stabilized the amrvac/AGILE-experimental repository by overhauling its build system, centralizing physics modules, and enhancing configuration management. He introduced a schema-driven configuration system using Python and TOML, enabling robust type checking and clearer error handling. His work included integrating NVIDIA GPU acceleration and OpenACC support, consolidating build directories, and improving test reliability. By refactoring Fortran modules and streamlining Makefile workflows, Jorrit reduced technical debt and improved maintainability. These changes enabled reproducible performance testing, faster iteration on physics features, and more reliable CI, reflecting a deep, systematic approach to scientific software engineering and high-performance computing.
Overall Statistics
Feature vs Bugs
70%Features
Repository Contributions
43Total
Bugs
3
Commits
43
Features
7
Lines of code
5,243
Activity Months4
Your Network
57 people
Work History
June 2025
16 Commits • 3 Features
Jun 1, 2025June 2025 monthly summary for amrvac/AGILE-experimental focused on stabilizing the build/test system, modernizing and centralizing physics modules, and cleaning the codebase to improve maintainability and reliability. Delivered concrete features, improved testability, and reduced CI noise, enabling faster iteration on the physics subsystem and RT3D integrations.
16 Commits • 3 Features
Jun 1, 2025June 2025 monthly summary for amrvac/AGILE-experimental focused on stabilizing the build/test system, modernizing and centralizing physics modules, and cleaning the codebase to improve maintainability and reliability. Delivered concrete features, improved testability, and reduced CI noise, enabling faster iteration on the physics subsystem and RT3D integrations.
June 2025
May 2025
8 Commits • 2 Features
May 1, 2025May 2025 was focused on enhancing configurability, GPU acceleration readiness, and build reliability for amrvac/AGILE-experimental. Key advances include migrating to a schema-driven configuration system using config_schema.toml and a generalized config_reader.py, with new Option and Value types that support selectable parameters, stronger type checking, and improved error messages. This work reduces configuration errors and enables more robust experimentation workflows. NVIDIA GPU acceleration support was added, including architecture definitions and build integration to enable GPU-enabled computations within the AGILE framework, with optional OpenMP/OpenACC modes and architecture-specific flag loading for scalable performance. Build reliability was improved through targeted fixes: corrected quoting of fypp string arguments to prevent parsing errors, and aligning make help with the README to ensure accurate guidance. The changes collectively improve runtime configurability, performance potential on GPU-backed workloads, and overall development efficiency.
May 2025
8 Commits • 2 Features
May 1, 2025May 2025 was focused on enhancing configurability, GPU acceleration readiness, and build reliability for amrvac/AGILE-experimental. Key advances include migrating to a schema-driven configuration system using config_schema.toml and a generalized config_reader.py, with new Option and Value types that support selectable parameters, stronger type checking, and improved error messages. This work reduces configuration errors and enables more robust experimentation workflows. NVIDIA GPU acceleration support was added, including architecture definitions and build integration to enable GPU-enabled computations within the AGILE framework, with optional OpenMP/OpenACC modes and architecture-specific flag loading for scalable performance. Build reliability was improved through targeted fixes: corrected quoting of fypp string arguments to prevent parsing errors, and aligning make help with the README to ensure accurate guidance. The changes collectively improve runtime configurability, performance potential on GPU-backed workloads, and overall development efficiency.
April 2025
8 Commits • 1 Features
Apr 1, 2025Monthly summary for 2025-04 focusing on AGILE Build System Modernization and Baseline Integration in amrvac/AGILE-experimental. Delivered a migration-friendly build workflow, consolidated build directories, and baseline integration to enable reproducible performance comparisons. Contributions include new Makefiles, improved configuration parsing, GNU compatibility fixes, and targeted codebase cleanup. This work reduces build friction, speeds validation of changes, and lays groundwork for future optimizations. Notable commits include: c67aaefc3e388da7a06862f3bdd8f2583a3dab9c (create makefile for migrating to new build), 9047d53b1547df01a9a3cb8f403843a6cb0d3fc6 (first sketch of a new build system), 1bcb4c42c87b2425027df491eb77a4103d0d857d (add AGILE_baseline to migration; tweak makefiles), 242615ef773f10a4666dfade3a7fca0295f993b1 (fixes new build scripts to make AGILE_baseline compile on GNU), 332bc56e0c0dd4c217184b8d8b53971c4481b1c9 (remove spurious RECIPEPREFIX lines from partial make files), a9f2f8487bede014d23502289bacc0d271b6a3ba (use global build dir; parse amrvac.par with f90nml; store debug/compile flags in build_dir; add checks for fypp/fortdepend; flatten directories; implement clean), 8800539fee0d840a31b3ce379945df4bf7a248b5 (remove completed TODOs).
8 Commits • 1 Features
Apr 1, 2025Monthly summary for 2025-04 focusing on AGILE Build System Modernization and Baseline Integration in amrvac/AGILE-experimental. Delivered a migration-friendly build workflow, consolidated build directories, and baseline integration to enable reproducible performance comparisons. Contributions include new Makefiles, improved configuration parsing, GNU compatibility fixes, and targeted codebase cleanup. This work reduces build friction, speeds validation of changes, and lays groundwork for future optimizations. Notable commits include: c67aaefc3e388da7a06862f3bdd8f2583a3dab9c (create makefile for migrating to new build), 9047d53b1547df01a9a3cb8f403843a6cb0d3fc6 (first sketch of a new build system), 1bcb4c42c87b2425027df491eb77a4103d0d857d (add AGILE_baseline to migration; tweak makefiles), 242615ef773f10a4666dfade3a7fca0295f993b1 (fixes new build scripts to make AGILE_baseline compile on GNU), 332bc56e0c0dd4c217184b8d8b53971c4481b1c9 (remove spurious RECIPEPREFIX lines from partial make files), a9f2f8487bede014d23502289bacc0d271b6a3ba (use global build dir; parse amrvac.par with f90nml; store debug/compile flags in build_dir; add checks for fypp/fortdepend; flatten directories; implement clean), 8800539fee0d840a31b3ce379945df4bf7a248b5 (remove completed TODOs).
April 2025
November 2024
11 Commits • 1 Features
Nov 1, 2024November 2024 focused on reliability and maintainability of the FiniteVolumeAll workflow in amrvac/AGILE-experimental. Delivered a high-impact OpenACC parallelization bug fix and completed a comprehensive module cleanup/refactor to reduce technical debt, improving both runtime correctness and future maintainability. These efforts strengthen simulation stability, ease onboarding for new contributors, and lay groundwork for scalable parallelization work across the repository.
November 2024
11 Commits • 1 Features
Nov 1, 2024November 2024 focused on reliability and maintainability of the FiniteVolumeAll workflow in amrvac/AGILE-experimental. Delivered a high-impact OpenACC parallelization bug fix and completed a comprehensive module cleanup/refactor to reduce technical debt, improving both runtime correctness and future maintainability. These efforts strengthen simulation stability, ease onboarding for new contributors, and lay groundwork for scalable parallelization work across the repository.
Activity
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Quality Metrics
Correctness83.4%
Maintainability84.8%
Architecture80.8%
Performance73.4%
AI Usage20.0%
Skills & Technologies
Programming Languages
FortranGitMakeMakefileMarkdownPerlPythonShellTOML
Technical Skills
Build AutomationBuild SystemBuild System ConfigurationBuild System ManagementBuild SystemsCode CleanupCode FormattingCode MigrationCode RefactoringConfiguration ManagementData ValidationDebuggingError HandlingFinite Volume MethodFortran
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