
Shuheng Deng developed a feature for the alibaba/MNN repository that default-enables KLEIDIAI kernels through a configurable build option, streamlining integration and deployment for users. By introducing a macro-based kernel-enable flag and updating backend support, Shuheng centralized kernel activation at compile time, reducing manual configuration and improving maintainability. The work involved customizing the build system using CMake and C++, with careful attention to version control and validation to ensure stability. Although no bugs were fixed during this period, the feature accelerated time-to-value for kernel-enabled workloads and demonstrated depth in build configuration and backend integration within a production codebase.
September 2025 – alibaba/MNN: Delivered a key feature by upgrading Kleidiai to 1.14.0, aligning build artifacts with the new naming convention, and validating packaging integrity. No major bugs fixed this month. Overall impact: improved dependency compatibility, packaging reliability, and smoother downstream integration. Skills demonstrated: dependency management, build automation, artifact verification, and repo maintenance.
September 2025 – alibaba/MNN: Delivered a key feature by upgrading Kleidiai to 1.14.0, aligning build artifacts with the new naming convention, and validating packaging integrity. No major bugs fixed this month. Overall impact: improved dependency compatibility, packaging reliability, and smoother downstream integration. Skills demonstrated: dependency management, build automation, artifact verification, and repo maintenance.
July 2025 focused on delivering hardware-accelerated AI capabilities in MNN by integrating KleidiAI-powered convolution acceleration and SME2 Q4 asymmetric kernels. The effort included refactoring the existing convolution path for AI accelerators, adding KleidiAIConvolution support, and expanding kernel coverage with SME2 Q4 asym kernels. Build and backend integration were updated (CMake and backend changes) to enable seamless integration and future production deployment.
July 2025 focused on delivering hardware-accelerated AI capabilities in MNN by integrating KleidiAI-powered convolution acceleration and SME2 Q4 asymmetric kernels. The effort included refactoring the existing convolution path for AI accelerators, adding KleidiAIConvolution support, and expanding kernel coverage with SME2 Q4 asym kernels. Build and backend integration were updated (CMake and backend changes) to enable seamless integration and future production deployment.
In May 2025, focused on stabilizing the KleidiAi integration with the MNN ARM backend for alibaba/MNN. Delivered a targeted set of bug fixes and refactors to improve correctness, memory management, and compatibility with kernel formats. These changes reduce runtime risk and prepare for broader ARM backend support.
In May 2025, focused on stabilizing the KleidiAi integration with the MNN ARM backend for alibaba/MNN. Delivered a targeted set of bug fixes and refactors to improve correctness, memory management, and compatibility with kernel formats. These changes reduce runtime risk and prepare for broader ARM backend support.

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