January 2026 performance summary for LLNL/axom: Delivered a cross-cutting build-system and CI/CD refresh that enables faster, more reliable HPC software delivery. Key deliverables include upgrading core build toolchains (camp/raja/umpire) with Spack 1.1.0 and updated spack_packages, plus vcpkg version updates, ensuring compatibility with modern compilers and toolchains. Implemented ROCm + OpenMP flag improvements by reorganizing Fortran and ROCm flags and enabling experimental OpenMP SIMD features for improved performance and portability on AMD hardware. Addressed Windows OpenMP reliability with a RAJA patch and stabilized Windows CI through MSVC-focused improvements. Updated and tested critical dependencies (RAJA v2025.12.1, Caliper 2.14.0, bumped CMake externals) and conducted extensive RAJA version testing to harden compatibility. Modernized CI/CD and host-configs (Docker host-configs, Python external for Docker, indentation adjustments in Docker spack.yaml, updated host-configs for CZ/RZ, updated GHA tpl hash and image tags) to improve reproducibility and reduce feedback cycles across platforms.

Month 2025-12 was focused on expanding Axom’s HPC readiness, improving GPU and CUDA workflows, and strengthening build/test reliability. Delivered several high-impact features, fixed key compatibility gaps, and modernized packaging and CI to support scalable, high-performance workloads across ROCm/MPI and CUDA environments.

November 2025: Strengthened build reliability, GPU readiness, and developer productivity across GEOS and Axom. Delivered cross-repo build environment improvements, GPU acceleration enablement, Python binding enhancements, and CI/test infrastructure upgrades that shorten feedback loops and reduce maintenance burden. These changes extend compiler/CUDA support, stabilize GPU workflows, simplify Python integration, and optimize test execution, delivering measurable business value through faster builds, improved GPU performance, and higher software quality.

October 2025 (2025-10): Key outcomes include Docker image modernization for LLNL/axom to support GCC/Clang with MPICH and locale support, along with CI infrastructure upgrades to test against latest toolchains and Ubuntu 24.04. The changes improved portability, reproducibility, and build reliability across developer and CI environments, enabling faster feedback and more robust scientific workflows.

September 2025 focused on stabilizing and modernizing the build and CI pipelines, expanding cross-repo dependency management, and advancing readiness for a robust 1.0 release across LLNL/axom, GEOS-DEV/GEOS, and GEOS-DEV/thirdPartyLibs. The work improves build reliability, cross-platform consistency, and developer workflows, enabling faster iteration, easier onboarding, and more predictable downstream deployments.

In 2025-08, LLNL/axom delivered notable gains in build reliability, testing coverage, and tooling integration across cross-platform environments. The month focused on strengthening CI stability, improving RAJA-related test coverage, and aligning downstream tooling with robust build hygiene. These efforts reduce regression risk, accelerate release cycles, and improve reproducibility for Windows, CUDA, and MPI workflows, enabling smoother downstream adoption and more predictable engineering outcomes.

July 2025 monthly summary for LLNL/axom and spack-packages focused on delivering key features, fixing major bugs, and advancing portability and CI reliability. Highlights include refactoring zeroMessage into a function with allocation path and fixing linkage; comprehensive build/tooling updates to support modern toolchains; addition of a Python sidre_createdatastore example; extensive CUDA and portability fixes; and stability improvements across tests and code formatting.

June 2025 monthly summary for LLNL/axom: Delivered significant data interoperability, testing, and cross-platform readiness. Key outcomes include Numpy integration for Sidre views enabling numpy-based analytics; expanded Sidre Python test coverage; added Sidre C++ unit test for sidre_group converted to sidre view; RTD documentation updates; and build/devtools stability across platforms with CUDA/BlueOS fixes. GPU workflow improvements include MPI handling workarounds and sanitizer guardrails. Business value: streamlined analytics, increased CI confidence, and broader platform support with safer, maintainable code.

May 2025 monthly summary for LLNL/axom focused on enabling Python access to Sidre through nanobind, stabilizing the Python extension build, and improving overall code quality. Key outcomes include deliverables for Sidre Python bindings and test coverage, a streamlined nanobind integration workflow, and documentation/typing improvements that enhance maintainability and developer onboarding.

Concise monthly summary for 2025-04 focusing on delivery of modernized build system across AXOM, 2D geometry enhancements, Python interop, and RAJA/LvArray updates, plus a rollback that stabilized MPI in Toss. Highlights include cross-repo CI/build improvements, broader hardware support (HIP/CCE, Clang/GCC toolchains, Spack environments), and improved documentation for maintainability and onboarding.

March 2025 recap: Delivered cross-repo ROCm/HIP compatibility work, build-system resilience, and Mathpresso integration across LLNL/axom, GEOS-DEV/thirdPartyLibs, and GEOS. The efforts enhanced hardware coverage, packaging reliability, and CI stability, enabling broader deployment, easier downstream integration, and faster feature delivery.

February 2025 monthly summary focused on delivering 2D mesh workflow capabilities, stabilizing CI/build automation, and improving maintainability across LLNL/axom, GEOS-DEV/thirdPartyLibs, and GEOS. Key business value delivered includes enabling 2D in-memory quest and IntersectionShaper workflows, tightening CI for ROCm, and streamlining containerized builds via Spack/Docker to reduce build times and improve reproducibility.

January 2025 (2025-01) focused on increasing correctness, stability, and testing coverage for LLNL/axom’s geometry and analysis tooling, while establishing CI sanitizers to catch undefined-behavior early. Key features include UBSAN integration and suppression macro, initial GitLab CI sanitizer job, and environment/test infrastructure improvements. Major bug fixes address suppression file management, path naming, and geometry clipping robustness. The combined work delivers stronger correctness guarantees, faster issue detection in CI, and broader test coverage, enabling safer releases and improved developer productivity.

December 2024 monthly summary for LLNL/axom focused on stability, memory safety, and observability improvements that enhance reliability in production workloads and support ongoing performance optimization.

November 2024: Delivered two feature updates in LLNL/axom that stabilize builds and ROCm deployments. Key business outcomes include more reliable CI across environments (macOS 13 target updates to address Azure Pipelines deprecation) and corrected ROCm/Spack path handling (ROCM_PATH resolved via llvm-amdgpu; fixed installation prefixes for ROCm versions 6.1.2 and 6.2.1). These changes reduce flaky builds, simplify onboarding, and future-proof ROCm-enabled workflows. Technologies demonstrated include CI/CD tuning, cross-environment compatibility, ROCm path resolution, and Spack integration.

October 2024: Delivered Dev Tools and Host Configuration Update for Build Environments in LLNL/axom. Updated host-configs for rzadams and tioga builds to use the latest devtools and updated library/tool paths, ensuring builds leverage current development toolchains and reducing environment-related failures. This work improves build reliability, reduces CI noise, and accelerates developer feedback.

December 2023 monthly focus: deliver targeted improvements to GPU debugging and reliability in LLNL/axom. Implemented HIP device kernel assertion support to enable and simplify the use of asserts in HIP kernels, improving error checking and debugging for GPU code. This change reduces debugging time and increases runtime safety for HIP paths while aligning with existing device-side assertion practices.