OpenXiangShan/GEM5
Apr 2026 – Jun 2026
3 Months active
Languages Used
Python
Technical Skills
CPU architectureConfiguration managementPerformance optimizationperformance evaluationsystem configurationPython
XXtaoo
PROFILE
Xxtaoo
Over a three-month period, contributed to the OpenXiangShan/GEM5 repository by developing and optimizing CPU and memory subsystem configurations using C++ and Python. Focused on performance tuning for the kmhv3 CPU, including disabling pipeline stages and adjusting fetch-to-decode delays to enable controlled benchmarking. Enhanced memory modeling fidelity by introducing LSQ-local fake DCache MainPipe and refining cache refill logic to better represent timing and resource contention. Centralized prefetcher configuration and improved observability through new statistics, supporting more accurate performance analysis. All changes emphasized reproducibility, traceability, and system stability, enabling faster experimentation and more reliable hardware-software trade-off evaluations.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
8Total
Bugs
0
Commits
8
Features
4
Lines of code
1,435
Activity Months3
Your Network
34 peopleWork History
June 2026
3 Commits • 2 Features
Jun 1, 2026June 2026 monthly summary: Delivered policy-driven enhancements to prefetcher configuration and improved management of XSComposite/L2Composite in GEM5/OpenXiangShan, along with a significant upgrade to memory-subsystem modeling. The changes increase configurability, data-path fidelity, and experimentation speed for performance optimization. Implemented LSQ-local fake DCache MainPipe to model L1D refills and store-buffer interactions, enabling more accurate timing and resource blocking analysis. Refined cache refill behavior by tracking eviction dirty data and gating bank usage, resulting in more realistic memory-system timing. Added extensive blocking/admission statistics and timing refinements to improve observability and debugability. Overall, these work items lay the groundwork for more trustworthy performance projections and faster hardware/software trade-off decisions.
3 Commits • 2 Features
Jun 1, 2026June 2026 monthly summary: Delivered policy-driven enhancements to prefetcher configuration and improved management of XSComposite/L2Composite in GEM5/OpenXiangShan, along with a significant upgrade to memory-subsystem modeling. The changes increase configurability, data-path fidelity, and experimentation speed for performance optimization. Implemented LSQ-local fake DCache MainPipe to model L1D refills and store-buffer interactions, enabling more accurate timing and resource blocking analysis. Refined cache refill behavior by tracking eviction dirty data and gating bank usage, resulting in more realistic memory-system timing. Added extensive blocking/admission statistics and timing refinements to improve observability and debugability. Overall, these work items lay the groundwork for more trustworthy performance projections and faster hardware/software trade-off decisions.
June 2026
May 2026
3 Commits • 1 Features
May 1, 2026May 2026 performance-focused delivery for OpenXiangShan/GEM5. RTL-aligned KmhV3 timing with prefetch buffer optimization completed, with a stability rollback process to ensure safe deployment. Final configuration aligns KmhV3 timing and memory parameters with RTL, enabling 3-cycle L2 forward/response latencies, 1-cycle hint wakeup offset, and hardware prefetch buffers by default, balancing throughput with system stability. All changes tracked via commit history (with Change-Id signatures) to support traceability and future audits.
May 2026
3 Commits • 1 Features
May 1, 2026May 2026 performance-focused delivery for OpenXiangShan/GEM5. RTL-aligned KmhV3 timing with prefetch buffer optimization completed, with a stability rollback process to ensure safe deployment. Final configuration aligns KmhV3 timing and memory parameters with RTL, enabling 3-cycle L2 forward/response latencies, 1-cycle hint wakeup offset, and hardware prefetch buffers by default, balancing throughput with system stability. All changes tracked via commit history (with Change-Id signatures) to support traceability and future audits.
April 2026
2 Commits • 1 Features
Apr 1, 2026OpenXiangShan/GEM5: Implemented targeted performance tuning for the ideal kmhv3 CPU to assess throughput with a modified pipeline. Key changes include disabling the dispatch stage and setting fetchToDecodeDelay to 5, enabling controlled experiments and baseline data. Prepared changes for PR and documented rationale (Change-Id references). No major bug fixes recorded this month for this repo. Overall, delivered a reproducible configuration for performance evaluation, paving the way for data-driven optimizations and faster performance benchmarking.
2 Commits • 1 Features
Apr 1, 2026OpenXiangShan/GEM5: Implemented targeted performance tuning for the ideal kmhv3 CPU to assess throughput with a modified pipeline. Key changes include disabling the dispatch stage and setting fetchToDecodeDelay to 5, enabling controlled experiments and baseline data. Prepared changes for PR and documented rationale (Change-Id references). No major bug fixes recorded this month for this repo. Overall, delivered a reproducible configuration for performance evaluation, paving the way for data-driven optimizations and faster performance benchmarking.
April 2026
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Quality Metrics
Correctness95.0%
Maintainability92.6%
Architecture95.0%
Performance95.0%
AI Usage32.6%
Skills & Technologies
Programming Languages
Python
Technical Skills
C++CPU architectureCache SimulationComputer ArchitectureConfiguration managementPerformance AnalysisPerformance optimizationPythonPython scriptingSimulation Modelingperformance evaluationperformance optimizationperformance tuningsystem architecturesystem configuration
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