March 2026 performance summary focusing on stability, reliability, and cross-repo improvements. Key fixes addressed CUDA GTest runtime linking issues, test environment stability, and memory-space correctness for Kokkos on APUs. Introduced CI/workflow templates to streamline testing and project documentation in E3SM, with cross-repo quality gains for NCAR/micm and E3SM.

November 2025 monthly summary for NCAR/micm: Delivered flexible CUDA kernels enabling user-defined vector lengths for NormalizedError and AlphaMinusJacobian, enhancing adaptability to varying problem sizes and potential performance benefits. Implemented changes include memory allocation adjustments, device memory checks, and expanded testing to validate correctness across vector lengths. This work improves runtime configurability and reliability for kernel computations, supporting future optimizations and varied workloads.

September 2025 monthly summary focusing on feature delivery and bug fixes across two repositories: NCAR/micm and E3SM. Delivered CUDA-based solver enhancements with user-defined vector lengths and refreshed unit tests; cleaned HIP build initialization code to fix build failures. Highlights include targeted kernel and test updates, improved performance flexibility, and increased build reliability across CUDA and HIP environments.

NCAR/micm — August 2025 monthly summary Overview: - Focused on expanding CUDA-based numerical tests and kernel flexibility to improve reliability and performance across GPUs and build environments. Key features delivered: - CUDA matrix tests: vector-length flexibility and robustness - Description: Enables user-defined vector lengths for dense and sparse matrices; refactored tests for clarity and robustness; improved compatibility across build environments. - Commits included: 899df2a716948dad343ced6268348e3c8d8f1401; 324afed6bc1b93e878ad3afb340f85711f399d3a - CUDA LU decomposition with user-defined vector lengths - Description: Allows user-defined vector lengths in CudaDenseMatrix and CudaSparseMatrix; adjusts LU kernel and memory handling to optimize performance across hardware configurations. - Commit included: f9106c807ca4218928e2f22629c0feec8f1b88fc Major bugs fixed: - No critical bugs fixed this month; primary effort focused on feature enhancements and test robustness across architectures and environments. Overall impact and accomplishments: - Broadened test coverage and kernel flexibility for CUDA-backed operations, improving reliability of numerical routines across diverse GPU configurations. - Potential performance benefits from kernel/memory optimizations and vector-length tuning. - Strengthened CI and development workflow through improved cross-build compatibility. Technologies/skills demonstrated: - CUDA programming, C/C++, kernel optimization, memory layout optimization, test harness refactoring, cross-platform build/configuration.

Month 2025-06 (NCAR/micm): Delivered a new SparseMatrix.PrintNonZeroElements API and fixed GPU memory pressure for large grids. The new PrintNonZeroElements iterates matrix blocks to print non-zero entries with their row and column indices and includes unit tests across multiple ordering policies. To address GPU out-of-memory issues, introduced an indexing_only flag that prevents unnecessary allocations when only indexing is performed, enhancing stability and scalability for large simulations. These changes improve observability of sparse matrices, reduce memory footprint on GPUs, and enable larger, more reliable runs.

April 2025 monthly performance summary focusing on business value and technical achievements across two/repos: NCAR/micm and E3SM-Project/E3SM. The quarter delivered two high-impact features, targeted bug fixes, and code hygiene improvements that reduce risk and accelerate future production runs.

March 2025 monthly summary for NCAR/micm focusing on performance optimization in CUDA paths and memory-access improvements to support faster reaction/product Jacobian calculations. Implemented a restrict qualifier for local raw pointers in ProcessSet CUDA to indicate non-overlapping memory access, enabling potential compiler optimizations and better GPU utilization. This work strengthens the perf profile of the micm module and establishes groundwork for higher throughput on large-scale simulations.

February 2025: Delivered an automated stale issue/PR cleanup workflow for NCAR/micm using GitHub Actions and actions/stale, with a daily cadence to mark inactive items and auto-close after inactivity. The feature reduces manual triage time, improves backlog hygiene, and keeps the repository focused on active work. No major bugs fixed this month. Technologies demonstrated include CI/CD automation, YAML workflows, and integration of third-party actions, enhancing maintainability and developer productivity.

January 2025 NCAR/micm: Implemented performance optimizations and correctness improvements for the MICM Solver, including iterator-based CPU enhancements, Rosenbrock substepping fix with inline LU, and expanded integration tests across LU methods and matrix formats.

November 2024 monthly summary for NCAR/micm. Focused on strengthening the linear solver path by refactoring the LU decomposition to be Doolittle-specific across CUDA, JIT, and standard solvers. This included renaming classes and files to reflect the specialization, aligning implementations with the Doolittle algorithm to improve clarity, correctness, and maintainability. The work reduces risk of solver regressions and simplifies future optimizations. Key outcomes: cross-component naming consistency, easier code review, and a foundation for targeted performance improvements in the linear solver stack.