
Ben Wibking developed advanced simulation capabilities for the quokka-astro/quokka repository, focusing on high-fidelity astrophysical and magnetohydrodynamics workflows. He engineered adaptive mesh refinement (AMR) features, GPU-accelerated routines, and robust CI/CD pipelines using C++, CUDA, and Python. His work included implementing divergence-preserving MHD solvers, performance profiling, and runtime configuration systems to improve simulation accuracy and scalability. Ben modernized the build environment for C++20 and CUDA 12.0, enhanced developer onboarding with comprehensive documentation, and maintained reproducibility through regression testing and containerization. The depth of his contributions addressed both scientific correctness and developer productivity, resulting in a maintainable, scalable codebase.

October 2025: Implemented major MHD capabilities and tooling enhancements for quokka-astro/quokka, delivering higher fidelity simulations, robust test coverage, and improved maintainability. Key features include divergence-preserving AMR support for MHD with EdgeFluxRegister and CI/docs/tests, and a sentinel-based I/O system that triggers per-step plotfiles and checkpoints. A critical regression-test bug was fixed by enabling plotfile outputs for MHDBlast. The codebase was modernized with C++20 and CUDA 12.0 readiness, along with documentation cleanup and maintenance of submodules. Overall impact: more accurate simulations, reliable automation, streamlined dependency management, and improved developer productivity. Technologies/skills demonstrated: C++20, CUDA 12.0, AMReX, advanced AMR techniques, regression testing, CI pipelines, and submodule maintenance.
October 2025: Implemented major MHD capabilities and tooling enhancements for quokka-astro/quokka, delivering higher fidelity simulations, robust test coverage, and improved maintainability. Key features include divergence-preserving AMR support for MHD with EdgeFluxRegister and CI/docs/tests, and a sentinel-based I/O system that triggers per-step plotfiles and checkpoints. A critical regression-test bug was fixed by enabling plotfile outputs for MHDBlast. The codebase was modernized with C++20 and CUDA 12.0 readiness, along with documentation cleanup and maintenance of submodules. Overall impact: more accurate simulations, reliable automation, streamlined dependency management, and improved developer productivity. Technologies/skills demonstrated: C++20, CUDA 12.0, AMReX, advanced AMR techniques, regression testing, CI pipelines, and submodule maintenance.
September 2025 monthly summary: Delivered major stability and modernization across quokka and parthenon repos, focusing on core simulation reliability, dev-environment modernization, and improved developer onboarding and governance. Reharsing key commitments: Core Simulation Improvements and Stability refactored hydro retry logic and deterministic AMR flux registers, with removal of obsolete cooling modules in favor of ResampledCooling; Dependency and Environment Modernization upgraded AMReX and ROCm 7.x readiness, plus CI/devcontainer/CI upgrades; Documentation and Onboarding Enhancements expanded developer docs, onboarding materials, and governance tooling; a GPU-related risk was mitigated by reverting the Balsara ComputeEMF method to a stable baseline while investigations continue; Parthenon repository gained documentation restructuring and governance enhancements with automated checks and changelog updates.
September 2025 monthly summary: Delivered major stability and modernization across quokka and parthenon repos, focusing on core simulation reliability, dev-environment modernization, and improved developer onboarding and governance. Reharsing key commitments: Core Simulation Improvements and Stability refactored hydro retry logic and deterministic AMR flux registers, with removal of obsolete cooling modules in favor of ResampledCooling; Dependency and Environment Modernization upgraded AMReX and ROCm 7.x readiness, plus CI/devcontainer/CI upgrades; Documentation and Onboarding Enhancements expanded developer docs, onboarding materials, and governance tooling; a GPU-related risk was mitigated by reverting the Balsara ComputeEMF method to a stable baseline while investigations continue; Parthenon repository gained documentation restructuring and governance enhancements with automated checks and changelog updates.
2025-08 monthly work summary for quokka-astro/quokka focused on delivering GPU-stable, resource-efficient simulation features, stabilizing runtime behavior, and tightening CI/CD and dependencies. Highlights include GPU stability improvements, improved simulation termination timing, and CI/CD workflow/dependency alignment, with clear business value in reliability, efficiency, and faster feedback loops.
2025-08 monthly work summary for quokka-astro/quokka focused on delivering GPU-stable, resource-efficient simulation features, stabilizing runtime behavior, and tightening CI/CD and dependencies. Highlights include GPU stability improvements, improved simulation termination timing, and CI/CD workflow/dependency alignment, with clear business value in reliability, efficiency, and faster feedback loops.
Expanded Quokka's physics and reliability in July 2025, delivering key features and robustness improvements to enable higher-fidelity simulations and easier adoption. Highlights include ghost wavespeeds/face velocities with extended AMR ghost cells and validation scripts; extrema-preserving xPPM reconstruction with updated tests; Magnetohydrodynamics (MHD) capabilities (EMF computation and MHD solvers); runtime-configurable stellar velocity limit; and always-compile particle functionality. Concurrent robustness fixes across I/O, MPI, and memory, plus tooling/docs improvements to support onboarding and CI. These changes deliver tangible business value: more accurate magnetized simulations, safer runtime configuration, reproducible results, and reduced build friction.
Expanded Quokka's physics and reliability in July 2025, delivering key features and robustness improvements to enable higher-fidelity simulations and easier adoption. Highlights include ghost wavespeeds/face velocities with extended AMR ghost cells and validation scripts; extrema-preserving xPPM reconstruction with updated tests; Magnetohydrodynamics (MHD) capabilities (EMF computation and MHD solvers); runtime-configurable stellar velocity limit; and always-compile particle functionality. Concurrent robustness fixes across I/O, MPI, and memory, plus tooling/docs improvements to support onboarding and CI. These changes deliver tangible business value: more accurate magnetized simulations, safer runtime configuration, reproducible results, and reduced build friction.
June 2025 delivered core capabilities and performance improvements across quokka and parthenon, driving scientific usability, reproducibility, and scale. Highlights include: 1) Academic Citation Badge to boost project visibility and attribution; 2) Performance profiling instrumentation (BL_PROFILE) added across particle creation, deposition, destruction, and related tasks for targeted bottleneck analysis; 3) Universal refinement restart support enabling multi-level restarts with interpolated data; 4) Isolated disk galaxy simulation mode expanding physics with validation data and initial conditions; 5) CI/DevOps modernization, including ARM64 CI migration to GitHub Actions and Canary-based workflows, improving reliability and reducing maintenance burden. Notable reliability improvement: Lustre I/O workaround updates in the AMReX submodule. These results collectively enhance reproducibility, scalability, and development velocity, delivering tangible business value across simulations and scientific workflows.
June 2025 delivered core capabilities and performance improvements across quokka and parthenon, driving scientific usability, reproducibility, and scale. Highlights include: 1) Academic Citation Badge to boost project visibility and attribution; 2) Performance profiling instrumentation (BL_PROFILE) added across particle creation, deposition, destruction, and related tasks for targeted bottleneck analysis; 3) Universal refinement restart support enabling multi-level restarts with interpolated data; 4) Isolated disk galaxy simulation mode expanding physics with validation data and initial conditions; 5) CI/DevOps modernization, including ARM64 CI migration to GitHub Actions and Canary-based workflows, improving reliability and reducing maintenance burden. Notable reliability improvement: Lustre I/O workaround updates in the AMReX submodule. These results collectively enhance reproducibility, scalability, and development velocity, delivering tangible business value across simulations and scientific workflows.
May 2025 performance summary for quokka-astro/quokka: Focused on stabilizing runtime, accelerating workloads on Frontier, and improving contributor onboarding. Delivered container and environment updates to enable ROCm 6.4 compatibility; fixed a restart cadence bug to ensure accurate plotting and checkpoint timing; introduced Poisson supercycling to boost performance on static meshes; enhanced HPC reliability with a SLURM-based auto-cancel mechanism and MPI barriers to prevent hangs; and expanded rendering capabilities by integrating Viskores and improving Ascent rendering for CI workflows. These changes boost reliability, throughput, and developer efficiency, while reducing maintenance and support overhead across the project.
May 2025 performance summary for quokka-astro/quokka: Focused on stabilizing runtime, accelerating workloads on Frontier, and improving contributor onboarding. Delivered container and environment updates to enable ROCm 6.4 compatibility; fixed a restart cadence bug to ensure accurate plotting and checkpoint timing; introduced Poisson supercycling to boost performance on static meshes; enhanced HPC reliability with a SLURM-based auto-cancel mechanism and MPI barriers to prevent hangs; and expanded rendering capabilities by integrating Viskores and improving Ascent rendering for CI workflows. These changes boost reliability, throughput, and developer efficiency, while reducing maintenance and support overhead across the project.
April 2025 performance highlights for quokka: delivered accuracy improvements for particle acceleration across AMR levels, updated compilation and build quality tooling, and prepared the codebase for GPU-accelerated execution on Frontier. Key changes include an AMR interpolation upgrade, targeted bug fixes, GPU-enabled environment updates, and documentation hygiene enhancements that together improve scientific fidelity, performance readiness, and maintainability.
April 2025 performance highlights for quokka: delivered accuracy improvements for particle acceleration across AMR levels, updated compilation and build quality tooling, and prepared the codebase for GPU-accelerated execution on Frontier. Key changes include an AMR interpolation upgrade, targeted bug fixes, GPU-enabled environment updates, and documentation hygiene enhancements that together improve scientific fidelity, performance readiness, and maintainability.
March 2025 (quokka-astro/quokka) focused on stabilizing the development pipeline, validating OpenPMD outputs, and enabling HPC hardware testing. The work delivered reduces build/test fragility, accelerates hardware experimentation, and enhances CI coverage, directly supporting faster, more reliable releases for HydroBlast3D.
March 2025 (quokka-astro/quokka) focused on stabilizing the development pipeline, validating OpenPMD outputs, and enabling HPC hardware testing. The work delivered reduces build/test fragility, accelerates hardware experimentation, and enhances CI coverage, directly supporting faster, more reliable releases for HydroBlast3D.
February 2025 focused on stability, reproducibility, and developer experience for the quokka project. Deliverables targeted devcontainer reliability, output provenance, regression-test resource usage, and development guidance to accelerate onboarding and ensure consistent coding practices.
February 2025 focused on stability, reproducibility, and developer experience for the quokka project. Deliverables targeted devcontainer reliability, output provenance, regression-test resource usage, and development guidance to accelerate onboarding and ensure consistent coding practices.
January 2025 monthly development summary for quokka-astro/quokka. Delivered four major items: AMD ROCm version enforcement for Quokka on AMD GPUs with updated docs; CI/build compatibility workaround for GCC 14 with HIP; expanded simulation configuration by making max_timesteps unlimited; added a runtime option to disable the energy conservation check in the Sedov test. These workstreams improved hardware compatibility, CI reliability, and simulation capabilities, aligning with product goals and reducing blockers for contributors.
January 2025 monthly development summary for quokka-astro/quokka. Delivered four major items: AMD ROCm version enforcement for Quokka on AMD GPUs with updated docs; CI/build compatibility workaround for GCC 14 with HIP; expanded simulation configuration by making max_timesteps unlimited; added a runtime option to disable the energy conservation check in the Sedov test. These workstreams improved hardware compatibility, CI reliability, and simulation capabilities, aligning with product goals and reducing blockers for contributors.
December 2024 focused on delivering robust data output, HPC readiness, and CI/tooling improvements for quokka. Key work spanned OpenPMD output stabilization, Frontier/HPC readiness, CI/test automation, and a new runtime option for timing instrumentation. The team prioritized business value by reducing data-quality risk, enabling scalable HPC runs, and accelerating feedback loops for developers and researchers.
December 2024 focused on delivering robust data output, HPC readiness, and CI/tooling improvements for quokka. Key work spanned OpenPMD output stabilization, Frontier/HPC readiness, CI/test automation, and a new runtime option for timing instrumentation. The team prioritized business value by reducing data-quality risk, enabling scalable HPC runs, and accelerating feedback loops for developers and researchers.
2024-11 Monthly Summary for quokka-astro/quokka focused on delivering visualization capabilities, simplifying maintenance, and improving build performance. Key features delivered include a new video generation workflow, 2D projection plotfile I/O, and targeted infrastructure and build optimizations that reduce maintenance burden and accelerate development cycles. NVHPC compiler compatibility improvements were made to ensure portable, reliable builds. Notable process improvements updated the PR template to streamline automated review. Impact: Enhanced ability for analysts to visualize simulation results, faster developer feedback through shorter compile times and cleaner repo state, and improved cross-compiler support for NVHPC. Note: All work aligns with business goals of reliable visualization, scalable build processes, and maintainable infrastructure.
2024-11 Monthly Summary for quokka-astro/quokka focused on delivering visualization capabilities, simplifying maintenance, and improving build performance. Key features delivered include a new video generation workflow, 2D projection plotfile I/O, and targeted infrastructure and build optimizations that reduce maintenance burden and accelerate development cycles. NVHPC compiler compatibility improvements were made to ensure portable, reliable builds. Notable process improvements updated the PR template to streamline automated review. Impact: Enhanced ability for analysts to visualize simulation results, faster developer feedback through shorter compile times and cleaner repo state, and improved cross-compiler support for NVHPC. Note: All work aligns with business goals of reliable visualization, scalable build processes, and maintainable infrastructure.
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