June 2026 monthly summary for ROCm/TheRock focusing on stabilizing CI and reducing flaky nightly builds. The primary change delivered in this period disables problematic rocprofiler-systems examples to prevent ASAN nightly build failures, enabling a stable baseline and paving the way for re-enablement with better safeguards.

Month: 2026-03 — ROCm/rocm-systems delivered notable CI reliability improvements, enhanced data serialization, and a migration path for rocprof-sys. Key changes focused on business value: reduce CI flakiness, improve observability, and ensure correctness of cached trace data, while guiding users toward modern markers. Key features delivered: - CI/CD Reliability and Observability Improvements: Introduced a safe CDash submission path (safe_submit) and GitHub Actions-aware logging helpers to improve CI output readability and resilience to CDash outages. Replaced raw ctest_submit calls with safe_submit, and modernized logging. Cleanup included the removal of legacy run-ci.sh in favor of run-ci.py and a SPDX header update. (Commit: f88e4ee44d1ce72e3a5c9a773dfef7b3bcf0c5ec) - Trace Cache Serialization of Optional Fields: Extended trace_cache to serialize std::optional<T>, enabling nullable fields like system_tid in pmc_event_with_sample. This improves data correctness when thread IDs are resolved asynchronously. (Commit: 3e3a94a4ef09446fc2caf42d3417ac89bd856fea) - API Deprecation Notice and Migration Guidance for rocprof-sys: Added user API deprecation notices with guidance to migrate to ROCTx Markers from the rocprofiler-sdk, including updated documentation and runtime warnings. (Commit: e7d568f6f691a79eb74f6782db256b288d640962) Overall impact and accomplishments: - Increased CI reliability, reducing false negatives due to CDash submission failures and improving developer feedback with clearer GH Actions logs. - Improved data correctness and future-proofing of trace data by supporting nullable fields in cached samples. - Proactive user guidance for API migrations, reducing risk for downstream users and aligning with the ROCm roadmap. Technologies/skills demonstrated: - CMake and ctest customization (safe_submit, error handling, GH Actions integration) - GitHub Actions logging and workflow readability enhancements - C++ type traits and serialization patterns for std::optional<T> - Optional field propagation in serialization/deserialization paths - API deprecation strategy, documentation updates, and runtime warnings

February 2026 monthly summary for ROCm/rocm-systems. The month focused on stability, developer productivity, and richer profiling context. Key outcomes include a critical robustness fix for rocpd statement executors to prevent use-after-free crashes, a build-system optimization to accelerate incremental builds by making external-dependency installs output-based, and an MPI profiling enhancement that attaches rank/size and profiler configuration to rocpd_process metadata. Together, these improvements reduce crash risk, shorten the edit-compile-test cycle, and improve MPI performance analysis, delivering measurable business value through increased reliability, faster cycles, and better diagnostics. Technologies demonstrated include CMake optimization patterns, improved external-project handling, JSON metadata serialization, and MPI integration hooks.

January 2026 ROCm/rocm-systems monthly performance summary highlighting key features, major fixes, and impact. Key features delivered: - Observability Enhancements: Upgraded to a structured logging stack using spdlog, introduced a dedicated rocprofiler-systems-logger, and added runtime log level control via command-line arguments and environment variables. This replaced legacy logging macros with modern equivalents and improved performance and maintainability. Relevant commits include: 318d13870f374cc806f64b77d3b9336b1baf8076 (spdlog integration and logging upgrade) and 940488ed5809b12740d80fa223b7fbba335a000c (fixing process_page category naming). - Profiling metrics clarification: Renamed the process_page category to reflect physical memory usage, increasing profiling clarity for users. - PyTorch Environment Auto-Discovery: Added automatic PyTorch library discovery for Python applications, enabling automatic identification of Python interpreters and corresponding PyTorch library paths to ensure correct runtime linkage. Commit: b533f56197ba1089653de799f737ab9d0c38626c. Major bugs fixed: - Corrected the naming and description of the process_page profiling category to align with physical memory usage, reducing user confusion and improving profiling accuracy (commit 940488ed). Overall impact and accomplishments: - Significantly improved observability, performance, and maintainability of ROCm/rocm-systems across users and deployments. - Reduced runtime linkage issues by automating PyTorch library discovery, resulting in smoother environment setup and fewer support incidents. - Strengthened profiling accuracy, providing clearer, more actionable metrics for performance tuning. Technologies/skills demonstrated: - CMake build integration, submodule management, and migration to spdlog for structured logging. - Modern C++ practices (exception-based error handling, improved runtime log control). - Python runtime discovery and interpreter/path mapping for dynamic library linkage. - Cross-repo collaboration and clear commit hygiene across multiple features.

Concise monthly summary for 2025-12 focusing on delivering ROC Profiler enhancements and trace_cache testing for ROCm/rocm-systems. Highlights include performance gains, data fidelity improvements, and expanded test coverage driving reliability for profiling workflows and customer-facing performance analysis.

Concise monthly summary for 2025-11 focusing on business value and technical achievements for ROCm/rocm-systems.

Month: 2025-10 | Repos: ROCm/rocm-systems. Summary: In Oct 2025, delivered stability and tunable profiling data collection across the RoCM stack. Key features delivered include Perfetto flush period configurability via ROCPROFSYS_PERFETTO_FLUSH_PERIOD_MS, and RoCPD cache management improvements with category region caching, caching refactor, and related metrics enhancements. A critical bug fix addressed rocprof-sys-python runtime errors by ensuring Python libs are located and loaded via LD_LIBRARY_PATH. The RoCPD work also fixed VAAPI traces and improved JSON parsing and UUID handling for more reliable data stores. Impact: Improved profiling reliability, lower overhead, and faster debugging cycles; CI and builds more robust. Technologies demonstrated: Python runtime hygiene, environment configuration (LD_LIBRARY_PATH), Perfetto, caching architectures, cmake/build hygiene, nlohmann JSON, VAAPI tracing, and container/CI readiness.

August 2025 monthly summary focusing on delivering robust CI/CD automation and enhanced observability for ROCm subsystems. Key outcomes include streamlined cross-OS CI for rocprofiler-systems, trace-based data logging enhancements in amd_smi and cpu_freq, and a bug fix ensuring correct stream ID association in rocpd tracing. These efforts improved reliability, observability, and data-driven performance debugging, enabling faster iterations and better developer productivity.