amrvac/AGILE-experimental
Jan 2025 – May 2026
12 Months active
Languages Used
FortranShellYAMLmakefileMakefileMakePythonbash
Technical Skills
Build SystemsCUDAHigh-Performance ComputingFortranGPU ComputingOpenACC
Leon Oostrum
PROFILE
Leon Oostrum
Over the past year, contributed to the amrvac/AGILE-experimental repository by engineering high-performance computing features and robust build automation for GPU-accelerated scientific simulations. Leveraging Fortran, OpenACC, and shell scripting, delivered scalable parallel computing workflows, modernized CI pipelines, and enhanced compatibility across Cray, LUMI, and NVHPC environments. Work included refactoring core routines for GPU offload, implementing MPI wrappers for safer parallel I/O, and optimizing build systems for cross-platform reliability. Addressed compiler-specific bugs, improved test coverage with GPU-enabled CI, and restructured adaptive mesh refinement for multi-GPU stability. These efforts enabled larger, more reliable simulations and streamlined deployment across diverse HPC clusters.
Overall Statistics
Feature vs Bugs
46%Features
Repository Contributions
67Total
Bugs
15
Commits
67
Features
13
Lines of code
83,124
Activity Months12
Your Network
58 peopleShared Repositories
48
Chun XiaMember
A KellyMember
AsteryMember
beatriceMember
Hao WuMember
Hector OlivaresMember
Johan HiddingMember
laurasootesMember
Leon OostrumMember
Work History
May 2026
2 Commits • 1 Features
May 1, 2026May 2026 monthly summary for amrvac/AGILE-experimental: Delivered GPU-accelerated testing workflows to leverage GPU resources and standardize tests for GPU environments, including improved handling of OPENACC and LUMI compatibility. Implemented a self-hosted GPU runner workflow to accelerate GPU-enabled CI. Harmonized test settings with normal builds by using arch instead of ARCH and removing explicit OPENACC arg handling. Minor CI robustness improvements to accommodate LUMI constraints and arch-based launcher selection. These changes reduce test cycles, improve resource utilization, and enhance coverage for GPU workflows.
2 Commits • 1 Features
May 1, 2026May 2026 monthly summary for amrvac/AGILE-experimental: Delivered GPU-accelerated testing workflows to leverage GPU resources and standardize tests for GPU environments, including improved handling of OPENACC and LUMI compatibility. Implemented a self-hosted GPU runner workflow to accelerate GPU-enabled CI. Harmonized test settings with normal builds by using arch instead of ARCH and removing explicit OPENACC arg handling. Minor CI robustness improvements to accommodate LUMI constraints and arch-based launcher selection. These changes reduce test cycles, improve resource utilization, and enhance coverage for GPU workflows.
May 2026
April 2026
1 Commits
Apr 1, 2026April 2026 monthly summary focusing on HPC AMR stability on LUMI. Delivered fixes to multi-GPU AMR naming clashes and restructured AMR subroutines to improve stability, scalability, and maintainability in amrvac/AGILE-experimental. Key changes include unique device allocatable naming to overcome Cray/OpenACC issues, removal of local associates from AMR subroutines, and refactoring contained subroutines to module-level implementations. Also fixed an off-by-one error in AMR data exchange, reducing boundary-related instability.
April 2026
1 Commits
Apr 1, 2026April 2026 monthly summary focusing on HPC AMR stability on LUMI. Delivered fixes to multi-GPU AMR naming clashes and restructured AMR subroutines to improve stability, scalability, and maintainability in amrvac/AGILE-experimental. Key changes include unique device allocatable naming to overcome Cray/OpenACC issues, removal of local associates from AMR subroutines, and refactoring contained subroutines to module-level implementations. Also fixed an off-by-one error in AMR data exchange, reducing boundary-related instability.
February 2026
3 Commits • 2 Features
Feb 1, 2026February 2026 – amrvac/AGILE-experimental: Delivered build-time flexibility and scalable MPI networking to support larger HPC workloads. Key outcomes include two features: 1) MPI Wrappers Compile Flag – introduces a compile-time flag to optionally enable MPI wrappers, enabling builds with or without MPI wrappers across environments. 2) Connectivity and MPI Networking Enhancements – increases the connectivity module max_size to 9,000,000 and adds NIC selection plus updated environment modules for compatibility, improving data handling and network performance. These changes enhance deployment consistency and scalability across clusters. No explicit major bug fixes were recorded this month; the focus was on feature delivery, performance tuning, and environment readiness. Business value: easier cross-environment builds, better utilization of large datasets, and more reliable MPI communication. Technologies/skills demonstrated: MPI, compile-time flags, NIC-aware networking, HPC modules, shell scripting, and environment management.
3 Commits • 2 Features
Feb 1, 2026February 2026 – amrvac/AGILE-experimental: Delivered build-time flexibility and scalable MPI networking to support larger HPC workloads. Key outcomes include two features: 1) MPI Wrappers Compile Flag – introduces a compile-time flag to optionally enable MPI wrappers, enabling builds with or without MPI wrappers across environments. 2) Connectivity and MPI Networking Enhancements – increases the connectivity module max_size to 9,000,000 and adds NIC selection plus updated environment modules for compatibility, improving data handling and network performance. These changes enhance deployment consistency and scalability across clusters. No explicit major bug fixes were recorded this month; the focus was on feature delivery, performance tuning, and environment readiness. Business value: easier cross-environment builds, better utilization of large datasets, and more reliable MPI communication. Technologies/skills demonstrated: MPI, compile-time flags, NIC-aware networking, HPC modules, shell scripting, and environment management.
February 2026
January 2026
2 Commits
Jan 1, 2026Monthly summary for 2026-01 focusing on NVHPC MPI wrapper compatibility fix in amrvac/AGILE-experimental. Implemented a wrapper layer to mitigate NVHPC-specific issues in parallel communication and safe file I/O, replacing direct MPI calls with wrappers and adding dedicated wrappers for MPI_FILE_READ and MPI_FILE_READ_AT under NVHPC 25.3. These changes enhance stability and reliability of large-scale simulations in NVHPC environments and lay groundwork for easier future NVHPC compatibility.
January 2026
2 Commits
Jan 1, 2026Monthly summary for 2026-01 focusing on NVHPC MPI wrapper compatibility fix in amrvac/AGILE-experimental. Implemented a wrapper layer to mitigate NVHPC-specific issues in parallel communication and safe file I/O, replacing direct MPI calls with wrappers and adding dedicated wrappers for MPI_FILE_READ and MPI_FILE_READ_AT under NVHPC 25.3. These changes enhance stability and reliability of large-scale simulations in NVHPC environments and lay groundwork for easier future NVHPC compatibility.
December 2025
1 Commits • 1 Features
Dec 1, 2025Month 2025-12: Monthly summary for amrvac/AGILE-experimental. Key features delivered: LUMI/Cray HPC compatibility and performance optimization; device-side MPI size parameter updates, increased grid neighbor capacity, and explicit OpenACC vectorization; Cray-specific inlining strategy adjustments to improve compilation reliability and runtime performance. Major bugs fixed: Cray compilation and runtime issues addressed through inlining and acceleration work, including making idecode a vector routine, vectorizing elemental functions, acc routine adjustments for usr_refine_grid, forced inlining of skip_direction, removal of redundant checks, and increasing max_blocks to stabilize runs on LUMI. Overall impact and accomplishments: Enhanced portability, scalability, and reliability on Cray-based systems, enabling larger simulations and more robust performance testing on the LUMI system. Technologies/skills demonstrated: MPI tuning for Cray, OpenACC optimization and vectorization, explicit inlining/acc routine control, device-side parameter management, and Cray-specific compilation workflows.
1 Commits • 1 Features
Dec 1, 2025Month 2025-12: Monthly summary for amrvac/AGILE-experimental. Key features delivered: LUMI/Cray HPC compatibility and performance optimization; device-side MPI size parameter updates, increased grid neighbor capacity, and explicit OpenACC vectorization; Cray-specific inlining strategy adjustments to improve compilation reliability and runtime performance. Major bugs fixed: Cray compilation and runtime issues addressed through inlining and acceleration work, including making idecode a vector routine, vectorizing elemental functions, acc routine adjustments for usr_refine_grid, forced inlining of skip_direction, removal of redundant checks, and increasing max_blocks to stabilize runs on LUMI. Overall impact and accomplishments: Enhanced portability, scalability, and reliability on Cray-based systems, enabling larger simulations and more robust performance testing on the LUMI system. Technologies/skills demonstrated: MPI tuning for Cray, OpenACC optimization and vectorization, explicit inlining/acc routine control, device-side parameter management, and Cray-specific compilation workflows.
December 2025
September 2025
5 Commits • 1 Features
Sep 1, 2025Monthly performance summary for 2025-09 (amrvac/AGILE-experimental). Focused on delivering robust HPC-ready changes for Cray/LUMI environments, improving CI reliability, and tightening code quality to increase maintainability and reproducibility of performance experiments.
September 2025
5 Commits • 1 Features
Sep 1, 2025Monthly performance summary for 2025-09 (amrvac/AGILE-experimental). Focused on delivering robust HPC-ready changes for Cray/LUMI environments, improving CI reliability, and tightening code quality to increase maintainability and reproducibility of performance experiments.
July 2025
17 Commits • 2 Features
Jul 1, 2025July 2025 monthly summary focusing on GPU-enabled performance, reliability, and maintainability improvements across the AGILE-experimental project. Key changes include GPU-accelerated ghost cell exchange with an initialization overhaul, corrected time integration initialization, fix for preprocessor directive alignment, and CI/build system modernization across multiple compilers and environments. These efforts deliver faster, scalable simulations on GPUs, consistent behavior across NVHPC/OpenMPI versions, and stronger code quality and validation in CI.
17 Commits • 2 Features
Jul 1, 2025July 2025 monthly summary focusing on GPU-enabled performance, reliability, and maintainability improvements across the AGILE-experimental project. Key changes include GPU-accelerated ghost cell exchange with an initialization overhaul, corrected time integration initialization, fix for preprocessor directive alignment, and CI/build system modernization across multiple compilers and environments. These efforts deliver faster, scalable simulations on GPUs, consistent behavior across NVHPC/OpenMPI versions, and stronger code quality and validation in CI.
July 2025
June 2025
1 Commits • 1 Features
Jun 1, 2025June 2025 monthly summary focused on delivering Cray OpenACC integration and ensuring build-system compatibility for the amrvac/AGILE-experimental repository. The work established a Cray-specific architecture file with appropriate Fortran compiler flags for OpenMP/OpenACC and debugging/optimization levels, aligning with the new build system architecture definitions and reducing platform integration risk.
June 2025
1 Commits • 1 Features
Jun 1, 2025June 2025 monthly summary focused on delivering Cray OpenACC integration and ensuring build-system compatibility for the amrvac/AGILE-experimental repository. The work established a Cray-specific architecture file with appropriate Fortran compiler flags for OpenMP/OpenACC and debugging/optimization levels, aligning with the new build system architecture definitions and reducing platform integration risk.
May 2025
1 Commits
May 1, 2025May 2025: AGILE testing baseline updated to reflect the current configuration by switching the baseline test to the van Leer limiter and refreshing the expected output accordingly. These changes align the test baseline with runtime behavior, improve test reliability, and strengthen CI validation for AGILE configurations.
1 Commits
May 1, 2025May 2025: AGILE testing baseline updated to reflect the current configuration by switching the baseline test to the van Leer limiter and refreshing the expected output accordingly. These changes align the test baseline with runtime behavior, improve test reliability, and strengthen CI validation for AGILE configurations.
May 2025
April 2025
32 Commits • 4 Features
Apr 1, 2025April 2025 monthly summary for amrvac/AGILE-experimental. Focus was on enabling Cray/LUMI GPU execution, stabilizing Cray-specific compiler interactions, and modernizing the CI/toolchain to current standards. Delivered concrete GPU/architecture enhancements, targeted bug fixes for Cray constraints, and dependency/CI maintenance to improve reliability, performance, and scalability on Cray hardware while keeping the development pipeline aligned with enterprise standards.
April 2025
32 Commits • 4 Features
Apr 1, 2025April 2025 monthly summary for amrvac/AGILE-experimental. Focus was on enabling Cray/LUMI GPU execution, stabilizing Cray-specific compiler interactions, and modernizing the CI/toolchain to current standards. Delivered concrete GPU/architecture enhancements, targeted bug fixes for Cray constraints, and dependency/CI maintenance to improve reliability, performance, and scalability on Cray hardware while keeping the development pipeline aligned with enterprise standards.
February 2025
1 Commits • 1 Features
Feb 1, 2025February 2025 Monthly Summary for amrvac/AGILE-experimental: Delivered GPU-accelerated ghost cell update loop with a refactor to improve simulation throughput and scalability. The update path was migrated to the GPU using OpenACC directives, with the loop parallelized and computations offloaded to the device. A helper function was inlined and ghost cell values are assigned directly on the device, reducing CPU-GPU transfers and synchronization overhead. Commit reference: 67c6a57137f1ac345dfd673689722723f5a7a51b (WIP: Move ghostcell update loop to GPU). No major bugs were documented this month; the focus was on performance optimization and enabling scalable GPU execution.
1 Commits • 1 Features
Feb 1, 2025February 2025 Monthly Summary for amrvac/AGILE-experimental: Delivered GPU-accelerated ghost cell update loop with a refactor to improve simulation throughput and scalability. The update path was migrated to the GPU using OpenACC directives, with the loop parallelized and computations offloaded to the device. A helper function was inlined and ghost cell values are assigned directly on the device, reducing CPU-GPU transfers and synchronization overhead. Commit reference: 67c6a57137f1ac345dfd673689722723f5a7a51b (WIP: Move ghostcell update loop to GPU). No major bugs were documented this month; the focus was on performance optimization and enabling scalable GPU execution.
February 2025
January 2025
1 Commits
Jan 1, 2025January 2025 focused on stabilizing the NVIDIA_acc build configuration in amrvac/AGILE-experimental. Delivered a targeted bug fix that restores optimization flags for the NVIDIA accelerator path and cleanly separates the debug build configuration into a dedicated file (nvidia_accdebug.defs). This improves build reliability, debugging efficiency, and maintainability across CI and developer workflows. The change reduces misconfiguration risk while preserving strong performance tuning capabilities and sets groundwork for easier future enhancements.
January 2025
1 Commits
Jan 1, 2025January 2025 focused on stabilizing the NVIDIA_acc build configuration in amrvac/AGILE-experimental. Delivered a targeted bug fix that restores optimization flags for the NVIDIA accelerator path and cleanly separates the debug build configuration into a dedicated file (nvidia_accdebug.defs). This improves build reliability, debugging efficiency, and maintainability across CI and developer workflows. The change reduces misconfiguration risk while preserving strong performance tuning capabilities and sets groundwork for easier future enhancements.
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Quality Metrics
Correctness87.6%
Maintainability88.6%
Architecture85.4%
Performance82.0%
AI Usage20.2%
Skills & Technologies
Programming Languages
FortranMakeMakefilePythonShellYAMLbashmakefile
Technical Skills
Bug FixBuild AutomationBuild System ConfigurationBuild SystemsCI/CDCUDACode CompilationCode FormattingCode RefactoringCompiler Bug FixCompiler Bug WorkaroundCompiler ConfigurationCompiler DirectivesConditional CompilationConfiguration Management
Repositories Contributed To
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