OpenXiangShan-Nanhu/Nanhu-V5
Nov 2024 – Nov 2024
1 Month active
Languages Used
Scala
Technical Skills
Computer ArchitectureDigital Logic DesignHardware DesignVerilog/Chisel
denghaiwen
PROFILE
Denghaiwen
During November 2024, this developer enhanced the OpenXiangShan-Nanhu/Nanhu-V5 repository by tuning the CPU fetch and predictor stack for improved performance and reliability. They enlarged the instruction fetch buffer and optimized the TAGE predictor by reducing the number of banks, using Verilog and Chisel for hardware design. Additionally, they addressed a bug in the TAGE table initialization by refining the reset logic to exclude the valid bit from reset hit checks, ensuring correct predictor startup. Their work demonstrated strong skills in computer architecture and digital logic design, resulting in higher instruction throughput and reduced misprediction rates at startup.
Overall Statistics
Feature vs Bugs
50%Features
Repository Contributions
2Total
Bugs
1
Commits
2
Features
1
Lines of code
60
Activity Months1
Your Network
20 people
Work History
November 2024
2 Commits • 1 Features
Nov 1, 20242024-11 monthly summary for OpenXiangShan-Nanhu/Nanhu-V5 focusing on performance improvements and reliability enhancements in the CPU fetch/predictor stack. Delivered a feature and a bug fix that together improve instruction fetch throughput, reduce mispredictions on startup, and strengthen predictor initialization. Demonstrated strong microarchitectural tuning, regression discipline, and clear Git traceability. Business value is higher IPC, better workload performance, and lower energy per instruction, with reduced maintenance risk.
2 Commits • 1 Features
Nov 1, 20242024-11 monthly summary for OpenXiangShan-Nanhu/Nanhu-V5 focusing on performance improvements and reliability enhancements in the CPU fetch/predictor stack. Delivered a feature and a bug fix that together improve instruction fetch throughput, reduce mispredictions on startup, and strengthen predictor initialization. Demonstrated strong microarchitectural tuning, regression discipline, and clear Git traceability. Business value is higher IPC, better workload performance, and lower energy per instruction, with reduced maintenance risk.
November 2024
Activity
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Scala
Technical Skills
Computer ArchitectureDigital Logic DesignHardware DesignVerilog/Chisel
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