
Over nine months, Ceba contributed to the OpenXiangShan ecosystem by engineering robust CPU simulation, emulation, and build infrastructure across repositories such as XiangShan and NEMU. Leveraging C, C++, and SystemVerilog, Ceba unified TLB hit detection, improved MMU trap handling, and refactored privilege instruction logic to enhance virtualization accuracy and system reliability. Their work included enabling Clang toolchain support, optimizing CI/CD pipelines, and consolidating documentation for better onboarding. By addressing low-level memory management, cache coherency, and register mapping, Ceba delivered solutions that reduced translation errors, improved debugging, and accelerated development cycles, demonstrating depth in low-level systems programming and hardware-software integration.

September 2025 highlights: stability improvements, governance enhancements, and documentation-driven quality across the OpenXiangShan ecosystem. Key focus areas included MMU reliability, repository governance, and flexible register access features.
September 2025 highlights: stability improvements, governance enhancements, and documentation-driven quality across the OpenXiangShan ecosystem. Key focus areas included MMU reliability, repository governance, and flexible register access features.
Summary for 2025-08: Delivered critical correctness improvements to the MMU trap handling and NMIE/MPRV semantics in OpenXiangShan/NEMU, with a focus on reliability and business value. The work enhances guest address translation accuracy and trap semantics, resulting in more robust emulation, fewer edge-case failures during hardware error handling, and improved software compatibility for RISC-V workloads. Impact: Reduced risk for teams relying on NEMU for OS validation and driver testing, improved emulator fidelity, and faster debugging cycles due to clearer MMU/NMIE/MPRV behavior. The changes support more stable QA and integration testing across RISC-V software stacks.
Summary for 2025-08: Delivered critical correctness improvements to the MMU trap handling and NMIE/MPRV semantics in OpenXiangShan/NEMU, with a focus on reliability and business value. The work enhances guest address translation accuracy and trap semantics, resulting in more robust emulation, fewer edge-case failures during hardware error handling, and improved software compatibility for RISC-V workloads. Impact: Reduced risk for teams relying on NEMU for OS validation and driver testing, improved emulator fidelity, and faster debugging cycles due to clearer MMU/NMIE/MPRV behavior. The changes support more stable QA and integration testing across RISC-V software stacks.
July 2025: Documentation-focused month across OpenXiangShan/XiangShan and OpenXiangShan/XiangShan-doc. Delivered consolidated documentation enhancements, clarified licensing terms, and published event materials to improve onboarding, external collaboration, and design reviews. No major bugs fixed this month; focus was on documentation quality and knowledge sharing, enabling faster onboarding and clearer external contributions.
July 2025: Documentation-focused month across OpenXiangShan/XiangShan and OpenXiangShan/XiangShan-doc. Delivered consolidated documentation enhancements, clarified licensing terms, and published event materials to improve onboarding, external collaboration, and design reviews. No major bugs fixed this month; focus was on documentation quality and knowledge sharing, enabling faster onboarding and clearer external contributions.
June 2025 performance summary: Delivered targeted improvements across three repositories to strengthen address translation reliability, build tooling, and hypervisor stability. Key deliverables include unifying TLB hit detection and robust gpaddr calculation in XiangShan, enabling Clang as the primary RISC-V toolchain in NEMU with a Clang defconfig, and stabilizing hypervisor exception handling tables in riscv-cheri. Together, these efforts reduce translation errors, accelerate development cycles, and improve runtime correctness for virtualization features. The work demonstrates proficiency in CPU microarchitecture, compiler/toolchain integration, and cross-repo collaboration, translating technical improvements into tangible business value such as fewer mis-translations, faster CI feedback, and more robust platform behavior.
June 2025 performance summary: Delivered targeted improvements across three repositories to strengthen address translation reliability, build tooling, and hypervisor stability. Key deliverables include unifying TLB hit detection and robust gpaddr calculation in XiangShan, enabling Clang as the primary RISC-V toolchain in NEMU with a Clang defconfig, and stabilizing hypervisor exception handling tables in riscv-cheri. Together, these efforts reduce translation errors, accelerate development cycles, and improve runtime correctness for virtualization features. The work demonstrates proficiency in CPU microarchitecture, compiler/toolchain integration, and cross-repo collaboration, translating technical improvements into tangible business value such as fewer mis-translations, faster CI feedback, and more robust platform behavior.
April 2025 performance summary: Reliability, cleanliness, and maintainability improvements across OpenXiangShan projects, with targeted fixes for submodule handling, repository hygiene, and a comprehensive refactor in NEMU. These changes reduce operational friction, improve onboarding, and strengthen the foundation for faster, safer releases.
April 2025 performance summary: Reliability, cleanliness, and maintainability improvements across OpenXiangShan projects, with targeted fixes for submodule handling, repository hygiene, and a comprehensive refactor in NEMU. These changes reduce operational friction, improve onboarding, and strengthen the foundation for faster, safer releases.
March 2025: Focused on CI/CD reliability, MMU correctness, and simulation stability. Delivered streamlined artifact generation in XiangShan, fixed regression and MMU translation issues for robust virtualization, and improved NEMU stability by making REPORT_ILLEGAL_INSTR opt-in. Result: fewer flaky builds, more accurate emulation, and faster validation cycles.
March 2025: Focused on CI/CD reliability, MMU correctness, and simulation stability. Delivered streamlined artifact generation in XiangShan, fixed regression and MMU translation issues for robust virtualization, and improved NEMU stability by making REPORT_ILLEGAL_INSTR opt-in. Result: fewer flaky builds, more accurate emulation, and faster validation cycles.
Concise monthly summary for Jan 2025 covering OpenXiangShan repos (NEMU, difftest, XiangShan). Emphasizes business value delivered through improved debugging, CI readiness, and documentation governance, as well as environment reliability and code quality improvements.
Concise monthly summary for Jan 2025 covering OpenXiangShan repos (NEMU, difftest, XiangShan). Emphasizes business value delivered through improved debugging, CI readiness, and documentation governance, as well as environment reliability and code quality improvements.
December 2024 performance summary across OpenXiangShan projects focused on stability, determinism, observability, and performance measurement. Delivered targeted fixes to timing-sensitive PTW/GPF paths, enhanced virtualization timekeeping, upgraded profiling instrumentation, and improved debugging/configurability. These changes reduce runtime risk in production, improve reproducibility for performance analysis, and accelerate readiness for NEMU-related deployments.
December 2024 performance summary across OpenXiangShan projects focused on stability, determinism, observability, and performance measurement. Delivered targeted fixes to timing-sensitive PTW/GPF paths, enhanced virtualization timekeeping, upgraded profiling instrumentation, and improved debugging/configurability. These changes reduce runtime risk in production, improve reproducibility for performance analysis, and accelerate readiness for NEMU-related deployments.
November 2024: Focused on correctness, reliability, and CI efficiency across OpenXiangShan projects. Key outcomes include corrected instruction fetch exception handling in XiangShan, CI optimization via gitignore hygiene, accurate Sv48x4 GVPNi address calculation in NEMU, strengthened instruction tracing under PERF_OPT, and aligned difftest interrupt handling with spike/difftest changes.
November 2024: Focused on correctness, reliability, and CI efficiency across OpenXiangShan projects. Key outcomes include corrected instruction fetch exception handling in XiangShan, CI optimization via gitignore hygiene, accurate Sv48x4 GVPNi address calculation in NEMU, strengthened instruction tracing under PERF_OPT, and aligned difftest interrupt handling with spike/difftest changes.
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