amrvac/AGILE-experimental
Mar 2026 – May 2026
2 Months active
Languages Used
Fortran
Technical Skills
Fortrannumerical methodsscientific computingparallel computingparallel programming
Olaf Willocx
PROFILE
Olaf Willocx
Contributed to the amrvac/AGILE-experimental repository by developing tracer support within the simulation framework, enabling initialization, tracking, and integration of tracer variables for enhanced observability in both hydrodynamic and magnetohydrodynamic contexts. Leveraged Fortran and numerical methods to unify tracer macros, improve build reliability, and expand end-to-end test coverage. Addressed a critical bug in NVIDIA’s mod_random module, stabilizing variance for stochastic initial conditions, and merged TRML model enhancements that introduced radiative cooling parameters, expanded testing, and improved logging. Increased simulation scalability by raising the maximum allowed neighbor processes, supporting larger-scale parallel runs and more robust scientific computing workflows.
Overall Statistics
Feature vs Bugs
67%Features
Repository Contributions
3Total
Bugs
1
Commits
3
Features
2
Lines of code
1,259
Activity Months2
Your Network
48 peopleShared Repositories
48
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Hector OlivaresMember
Johan HiddingMember
Leon OostrumMember
laurasootesMember
Work History
May 2026
2 Commits • 1 Features
May 1, 2026May 2026 monthly summary for amrvac/AGILE-experimental: Delivered two high-impact items with strong business value. Key accomplishments include a critical fix in NVIDIA mod_random sign-bit handling for left/right shift operators, improving variance of normals in stochastic initial conditions. Also merged TRML model enhancements into master, introducing radiative cooling parameters, expanded tests, and improved logging and observability. Additional improvements include precomputing 40 shear times for efficiency, adding lumi parameterization, and increasing the maximum allowed neighbor processes to 40 to support larger-scale runs. These efforts improved simulation fidelity, reproducibility, and performance, enabling more reliable physics studies and faster validation cycles.
2 Commits • 1 Features
May 1, 2026May 2026 monthly summary for amrvac/AGILE-experimental: Delivered two high-impact items with strong business value. Key accomplishments include a critical fix in NVIDIA mod_random sign-bit handling for left/right shift operators, improving variance of normals in stochastic initial conditions. Also merged TRML model enhancements into master, introducing radiative cooling parameters, expanded tests, and improved logging and observability. Additional improvements include precomputing 40 shear times for efficiency, adding lumi parameterization, and increasing the maximum allowed neighbor processes to 40 to support larger-scale runs. These efforts improved simulation fidelity, reproducibility, and performance, enabling more reliable physics studies and faster validation cycles.
May 2026
March 2026
1 Commits • 1 Features
Mar 1, 2026In March 2026, the AGILE-experimental project delivered significant enhancements to observability and validation by adding tracer support to the simulation framework, alongside build and test improvements that unify tracer-related macros and boost test coverage. This work lays groundwork for richer physics tracking and more robust validation across HD and MHD contexts.
March 2026
1 Commits • 1 Features
Mar 1, 2026In March 2026, the AGILE-experimental project delivered significant enhancements to observability and validation by adding tracer support to the simulation framework, alongside build and test improvements that unify tracer-related macros and boost test coverage. This work lays groundwork for richer physics tracking and more robust validation across HD and MHD contexts.
Activity
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Quality Metrics
Correctness86.6%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage33.4%
Skills & Technologies
Programming Languages
Fortran
Technical Skills
Fortrannumerical methodsparallel computingparallel programmingscientific computing
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