
Worked on OpenXiangShan projects, delivering hardware and emulator enhancements across RISC-V CPU and vector paths. Focused on floating-point and vector instruction support, this developer improved parameterization in the YunSuan repository, enabling robust FP conversions and hardware scaling. They expanded F16 instruction set compatibility, refined decoding logic, and enhanced debugging through CI/CD and emulator updates. Using Scala, C, and Python, they addressed correctness in floating-point arithmetic, vector dependencies, and submodule integration. Their work included bug fixes and new features in XiangShan and ready-to-run, resulting in more accurate simulation, broader hardware compatibility, and improved stability for complex system workloads.
Month: 2025-11 — Focused on improving DecodeUnit correctness for RVV paths, with emphasis on emulation fractional calculation and vector instruction dependency handling. Implemented two related changes that enhance decoding reliability and vector operation handling; these improvements reduce misdecode risk and improve execution stability for vector workloads. Highlights include the following commits: b5911ed5d7ecd02dd4802631b32cf745ea634cbd (fix(rvv): Fixed whether emul is a fractional) and 6d380e5fbfa434c9059517f14f9cdb74fc6a9dce (feat(rvv): Add oldvd dependency clearing for some instructions).
Month: 2025-11 — Focused on improving DecodeUnit correctness for RVV paths, with emphasis on emulation fractional calculation and vector instruction dependency handling. Implemented two related changes that enhance decoding reliability and vector operation handling; these improvements reduce misdecode risk and improve execution stability for vector workloads. Highlights include the following commits: b5911ed5d7ecd02dd4802631b32cf745ea634cbd (fix(rvv): Fixed whether emul is a fractional) and 6d380e5fbfa434c9059517f14f9cdb74fc6a9dce (feat(rvv): Add oldvd dependency clearing for some instructions).
January 2025: Delivered targeted FP correctness fixes and NEMU readiness improvements across OpenXiangShan/XiangShan and ready-to-run, focusing on FP EEW handling, SEW/vsew8 support, and NEMU stability. Key outcomes include enabling vsew8 in zvfh, updating NEMU references across submodules, and broad stability/refactor improvements to the simulator and build/config infrastructure. These changes improve FP accuracy for double-precision paths, expand SEW support, and reduce integration risk for future workloads.
January 2025: Delivered targeted FP correctness fixes and NEMU readiness improvements across OpenXiangShan/XiangShan and ready-to-run, focusing on FP EEW handling, SEW/vsew8 support, and NEMU stability. Key outcomes include enabling vsew8 in zvfh, updating NEMU references across submodules, and broad stability/refactor improvements to the simulator and build/config infrastructure. These changes improve FP accuracy for double-precision paths, expand SEW support, and reduce integration risk for future workloads.
November 2024 monthly summary outlining key delivered features, major bugs fixed, and overall impact across the OpenXiangShan projects. Focused on expanding F16 support, aligning references and CI coverage, and tightening correctness in FP and vector paths. Business value centers on broader hardware compatibility testing, improved debugging capabilities, and more accurate numerical behavior across simulators and emulators.
November 2024 monthly summary outlining key delivered features, major bugs fixed, and overall impact across the OpenXiangShan projects. Focused on expanding F16 support, aligning references and CI coverage, and tightening correctness in FP and vector paths. Business value centers on broader hardware compatibility testing, improved debugging capabilities, and more accurate numerical behavior across simulators and emulators.
Concise monthly summary for OpenXiangShan/YunSuan (2024-10). Focused on delivering robust FP conversion reliability through parameterization improvements in the postnorm stage.
Concise monthly summary for OpenXiangShan/YunSuan (2024-10). Focused on delivering robust FP conversion reliability through parameterization improvements in the postnorm stage.

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