November 2025 for OpenXiangShan-Nanhu/LinkNan: Executed routine dependency maintenance by updating the nanhu subproject to commit a80a1f8. This update, recorded in commit 7d7503bce17ea05e5a7677e63d0e43ce5538287e, keeps dependencies current, reduces drift, and improves build stability and future upgrade readiness. No major bugs were fixed this month; instead, the focus was on stability and maintainability. Key business value: preserved compatibility with upstream changes, smoother onboarding of future features, and improved release predictability. Technologies/skills demonstrated: Git version control, dependency management, submodule coordination, and maintainability practices.

October 2025 performance month focused on correctness, robustness, and observability across the Nanhu family. Delivered significant memory subsystem fixes in Nanhu-V5, improved data consistency in queue merging, hardened exception/prefetch handling to reduce deadlocks, and reestablished detailed performance visibility. Also aligned integration with upstream changes by bumping the nanhu subproject in LinkNan.

OpenXiangShan-Nanhu/Nanhu-V5 — September 2025: focused on strengthening memory subsystem correctness, exception handling, and test infrastructure. Delivered a targeted set of fixes across DCache timing, TLB/miss/page fault handling, and SFENCE interactions to improve reliability of memory operations, reduced risk of misreporting AF/PF, and prevented stale refills. Also improved Load/Prefetch RAR handling and significantly hardened the testing/difftest workflow to boost regression confidence and release readiness. These changes stabilize core memory pipelines, reduce failure modes in production, and establish a solid foundation for upcoming performance work.

August 2025 monthly performance summary for OpenXiangShan-Nanhu: Focused on stabilizing the memory hierarchy, improving correctness in the data path, and aligning dependencies to TB baselines. Delivered a comprehensive set of bug fixes and minor feature improvements across Nanhu-V5 and LinkNan that reduce risk, improve reliability, and increase system throughput under real workloads. Key areas include MissQueue/LoadPipe/LoadQueue corrections to prevent incorrect signaling and deadlocks, robust UnCache behavior with deviceType support, DCache/DTLB/L2 hint stabilization, and safe prefetch handling with permission checks. Also aligned subproject dependencies to maintain compatibility with latest Nanhu changes (TB-1327).

July 2025: Focused on correctness, maintainability, and configurability of the Nanhu-V5 memory subsystem. Delivered critical fixes across LoadUnit, LSU, MainPipe, SBuffer, MissQueue, and MMIO paths; removed dead code and tightened parameterization; updated environment references to support downstream testing. The work reduces edge-case regressions, stabilizes core paths, and lays groundwork for targeted performance improvements.

June 2025 monthly summary for OpenXiangShan-Nanhu/Nanhu-V5: Strengthened PMP/PMACheck robustness with MemBlock PMPWrapper integration, improved atomic operation correctness with earlier trigger evaluation and enhanced violation/exception handling, and completed a comprehensive memory subsystem maintenance/refactor to improve maintainability and RAW-check compatibility. Also hardened initialization defaults for tdata and s3_mmio to prevent undefined behavior. These efforts reduce defect leakage, raise reliability of the core memory path, and establish a cleaner, more scalable foundation for future optimizations.

May 2025 monthly summary for OpenXiangShan-Nanhu/Nanhu-V5: Delivered core memory subsystem reliability fixes, performance/timing enhancements, and codebase cleanup. Achievements span bug fixes, architectural refinements, and maintainability improvements with strong business value in reliability and memory performance.

April 2025 (OpenXiangShan-Nanhu/Nanhu-V5): Delivered memory subsystem robustness improvements, enhanced NC memory support, and ensured reliable operation across MMIO, cache, and memory pipelines. The work focused on correctness, reliability, and performance, directly reducing memory-related instability and stalls while enabling advanced memory access control features.

March 2025 (Month: 2025-03) – Nanhu-V5 delivered architecture refinements, governance updates, and a targeted bug fix that collectively improve reliability, maintainability, and memory efficiency. Key changes include an LSU overhaul that removes VLSU from MemBlock and shifts misalignment handling to software exceptions, a repository/configuration governance update to OpenXiangShan-Nanhu and gating changes (TP disabled in NKBL), and a SRAM queue sizing correction to ensure grantDataQueue uses a power-of-two-plus-one for correct sizing. These changes enable safer builds, clearer error handling, and better memory utilization across deployments.

February 2025 monthly summary for OpenXiangShan-Nanhu/Nanhu-V5 focused on stabilizing the MDP core. Key work consolidated around validation, state management, and code cleanup to improve reliability and maintainability of the MDP decision pipeline.

January 2025 monthly summary for OpenXiangShan-Nanhu/Nanhu-V5: Focused on a critical correctness fix in the memory-prediction redirect path. Implemented changes to source the PC redirect pointer and offset from s0_redirect_bits_reg.stFtqIdx and s0_redirect_bits_reg.stFtqOffset, ensuring the FTQ index/offset are correct when a redirect is valid and preventing mispredictions. This work is captured in commit 38e1716473b68d0210a6e9159e2f374c61fce5f9 with message '[redirectGen] fix memPredPcRead, it should use stFtqIdx'. Key achievements: 1) Correct memPredPcRead source for mem-predicted redirects using stFtqIdx; 2) Verified redirect generation path aligns FTQ indexing; 3) Reduced misprediction risk in the fetch/redirect pipeline; 4) Clear traceability to commit and repository where the change was made. Impact: Improved correctness and stability of memory-prediction redirects in Nanhu-V5, lowering misprediction-induced stalls and debugging overhead; demonstrable progress toward more reliable instruction fetch. Technologies/skills demonstrated: memory prediction, redirect generation, FTQ indexing, HDL/Verilog logic wiring (s0_redirect_bits_reg), change traceability via commit metadata.

December 2024 (Nanhu-V5) monthly summary: Focused on memory subsystem optimization, timing correctness, and developer tooling. Delivered notable features and fixes that reduce memory footprint, improve coherence timing, and streamline verification workflows. The work emphasizes business value through performance potential, area efficiency, and faster validation cycles.

Month: 2024-11 — Nanhu-V5: Delivered a focused set of microarchitectural and memory-subsystem improvements across the TLB, memory ordering, caches, and processor configuration, with targeted bug fixes to stabilize parameters and signaling. The work enhances throughput, reduces latency for memory-intensive workloads, and improves predictability under load, positioning the project for greater scalability and reliability as workloads grow. Highlights include TLB/memory translation optimizations, MDP integration for better load/store prediction, processor parameter/config refinements, LoadUnit responsiveness tuning, and DCache rework with simplified config.