February 2026 summary: Implemented crucial physics enhancements for star formation and particle mass management, hardened restart and particle lifecycle for long, stable runs, upgraded build/dependency tooling and CI, and expanded diagnostics/visualization with AMR-preserving projections and cumulative SN histories. Fixed MPI projection bug and improved community/docs integration, delivering clear business value through more realistic simulations, increased reliability, and better observability.

January 2026 monthly summary focusing on delivering configurable runtime controls, robust output management, GPU build reliability, physics diagnostics, and CI usability. The work significantly improves reproducibility, reliability, and observability for large-scale GPU-accelerated simulations in quokka, with clear business value for INCITE-type workloads and iterative development. Key achievements: - Unified runtime configurability and output formatting: consolidated runtime controls across simulations, including advanced timestep management, a PLM limiter runtime parameter, a density floor expressed as a runtime-parm expression, 7-digit checkpoint/plotfile numbering, and safe default AMR iteration settings for regridding. This reduces manual tuning, minimizes run-time surprises, and stabilizes long runs. - Runtime configurability enhancements: added init_shrink, initial_dt, and constant_dt options to control timestepping behavior at runtime, aligning with proven Castro-style controls for stability and reproducibility. - PLM limiter selection at runtime: introduced a runtime parameter to choose among minmod, sweby, or mc limiters, enabling rapid experimentation with convergence and accuracy tradeoffs. - Divergence-free physics restart and diagnostics: added divergence-free interpolation for restart on refined grids and introduced SFR history/diagnostics to support extended stellar evolution analyses, improving physical fidelity and long-run observability. - CI and build usability: CI workflow now prints the full container image URL after successful builds, enabling quick retrieval and deployment of built images for testing and production. Major bugs fixed: - GPU build stability and grid generation fixes: fixed the LinearAlfvenWave-GPU regression test, addressed a suite of miscellaneous GPU fixes (ComputeDensityFloorDebug for GPU builds, AGENTS.md pointer-capture guidance, and enabling NDEBUG for fmt on AMD GPUs), and updated the AMReX submodule to fix grid-generation issues impacting INCITE runs. - Derived variables and AMR grid consistency: fixed 2D slices of derived variables and updated AMR grid behavior to ensure reliable visualization and analysis on multi-level grids. Overall impact and accomplishments: - Increased reliability and reproducibility for long-running, GPU-accelerated simulations with safer defaults and richer runtime configurability. - Improved observability through enhanced diagnostics (SFR histories and restart diagnostics) and CI usability (container URL exposure). - Reduced operational risk for INCITE-scale jobs by addressing critical grid-generation and GPU regression issues, enabling more stable production runs. Technologies/skills demonstrated: - Amrex/AMR grid management, ParmParse runtime parameters, and runtime-controlled timestepping (init_shrink, initial_dt, constant_dt). - PLM limiter selection and 7-digit plotfile/checkpoint numbering for stable high-timestep workflows. - Divergence-free interpolation, SFR diagnostics, and long-term stellar evolution analysis tooling. - GPU build stability practices, regression testing, and CI pipeline improvements (container image URL exposure).

December 2025 monthly summary focusing on business value and technical achievements for the quokka project. The team delivered key physics enhancements, improved numerical robustness, and strengthened deployment and tooling to support reproducible research and production runs across varied HPC environments.

November 2025 — Quokka: Focused on improving CI/CD reliability for GPU/CUDA builds and strengthening solver validation. Key outcomes include substantially faster and more reliable GPU CI, plus formal numerical verification for HydroWave RK2+PPM, enhancing confidence in performance and correctness for GPU-accelerated workflows.

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.

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.

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.

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.

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.

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.