Tencent/ncnn
Oct 2024 – Mar 2026
18 Months active
Languages Used
C++CMakePythonYAMLMarkdownShellGLSLC
Technical Skills
ARM NEON optimizationARM assemblyARM developmentC++C++ developmentC++ programming
nihui
PROFILE
Nihui
Nihuini developed core neural network infrastructure and performance optimizations for the Tencent/ncnn repository, focusing on cross-platform inference acceleration and robust model conversion. Over 18 months, Nihuini engineered features such as Vulkan-based GPU compute paths, AVX512 and ARM NEON optimizations, and advanced ONNX-to-PNNX model conversion, using C++ and Python. The work included memory-mapped model loading, dynamic shape handling, and quantization improvements, addressing both runtime efficiency and deployment flexibility. By integrating CI/CD automation and enhancing API stability, Nihuini ensured reliable builds and broad hardware compatibility. The depth of engineering enabled scalable, high-performance inference across diverse devices and operating systems.
Overall Statistics
Feature vs Bugs
69%Features
Repository Contributions
318Total
Bugs
57
Commits
318
Features
129
Lines of code
443,956
Activity Months18
Your Network
217 peopleSame Organization
@tencent.com177
abushwangMember
LB7666Member
afeizhangMember
AIG-BotMember
aiyiwang2025Member
Hua TianMember
alcheminMember
Jinliang ZhengMember
amintongMember
Shared Repositories
40
Work History
March 2026
20 Commits • 4 Features
Mar 1, 2026In March 2026, Tencent/ncnn delivered major Vulkan-based acceleration and extensive x86 optimizations, plus CI and refactor improvements that collectively boosted inference performance, stability, and maintainability across platforms.
20 Commits • 4 Features
Mar 1, 2026In March 2026, Tencent/ncnn delivered major Vulkan-based acceleration and extensive x86 optimizations, plus CI and refactor improvements that collectively boosted inference performance, stability, and maintainability across platforms.
March 2026
February 2026
11 Commits • 5 Features
Feb 1, 2026February 2026 monthly summary for Tencent/ncnn. This month focused on delivering performance, memory efficiency, and stability improvements across the Vulkan SDPA path, along with broader GPU/driver compatibility enhancements. The work enabled faster model initialization, lower peak RAM usage, and more robust operation across drivers and hardware configurations, supporting larger models and higher throughput.
February 2026
11 Commits • 5 Features
Feb 1, 2026February 2026 monthly summary for Tencent/ncnn. This month focused on delivering performance, memory efficiency, and stability improvements across the Vulkan SDPA path, along with broader GPU/driver compatibility enhancements. The work enabled faster model initialization, lower peak RAM usage, and more robust operation across drivers and hardware configurations, supporting larger models and higher throughput.
January 2026
26 Commits • 12 Features
Jan 1, 2026Tencent/ncnn – January 2026: Focused on delivering business value through shader/tooling improvements, Vulkan runtime optimizations, API exposure enhancements, and cross‑platform packaging/CI improvements. The work emphasized reliability, performance, and developer experience across desktop and mobile platforms.
26 Commits • 12 Features
Jan 1, 2026Tencent/ncnn – January 2026: Focused on delivering business value through shader/tooling improvements, Vulkan runtime optimizations, API exposure enhancements, and cross‑platform packaging/CI improvements. The work emphasized reliability, performance, and developer experience across desktop and mobile platforms.
January 2026
December 2025
11 Commits • 5 Features
Dec 1, 2025December 2025 — Tencent/ncnn: CI reliability and API/graph optimizations with performance gains and broader model support. Key outcomes include unified Windows XP CI workflow with binary-size comparison and improved artifact logging, a new NCNN Versioning API with backward-compatible version retrieval, AVX512-based GEMM n-tile x16 unrolling for better memory access and compute, PNNX graph optimization enhancements (fusion of adjacent permutes and removal of no-op permutes with rotary embedding interleaving in scope), and a Torch stack negative-axis crash fix enhancing stability. These changes reduce build friction, improve compatibility, and boost inference performance across targets.
December 2025
11 Commits • 5 Features
Dec 1, 2025December 2025 — Tencent/ncnn: CI reliability and API/graph optimizations with performance gains and broader model support. Key outcomes include unified Windows XP CI workflow with binary-size comparison and improved artifact logging, a new NCNN Versioning API with backward-compatible version retrieval, AVX512-based GEMM n-tile x16 unrolling for better memory access and compute, PNNX graph optimization enhancements (fusion of adjacent permutes and removal of no-op permutes with rotary embedding interleaving in scope), and a Torch stack negative-axis crash fix enhancing stability. These changes reduce build friction, improve compatibility, and boost inference performance across targets.
November 2025
24 Commits • 9 Features
Nov 1, 2025November 2025 highlights for Tencent/ncnn focused on performance, stability, and deployment tooling across Vulkan, x86, and cross-tooling workflows. Key features were delivered to improve inference speed, portability, and model exportability, while targeted bug fixes enhanced reliability on MSVC/x86, CI stability, and cross-arch builds. The team also expanded coverage for advanced model constructs such as rotary embeddings and RMSNorm and improved build/CI pipelines for broader platform support.
24 Commits • 9 Features
Nov 1, 2025November 2025 highlights for Tencent/ncnn focused on performance, stability, and deployment tooling across Vulkan, x86, and cross-tooling workflows. Key features were delivered to improve inference speed, portability, and model exportability, while targeted bug fixes enhanced reliability on MSVC/x86, CI stability, and cross-arch builds. The team also expanded coverage for advanced model constructs such as rotary embeddings and RMSNorm and improved build/CI pipelines for broader platform support.
November 2025
October 2025
13 Commits • 5 Features
Oct 1, 2025October 2025 monthly summary for Tencent/ncnn focused on expanding ONNX compatibility, boosting autoregressive inference performance, and strengthening CI/Windows support, while delivering practical examples and expanded transformer tooling. Key outcomes include expanded ONNX support in PNNX (grid sampling, dynamic resizing, improved constant input handling and padding value conversions) along with a legacy opset compatibility fix, enabling broader model coverage and smoother migration from older models. Performance optimizations were delivered via a key-value cache for MultiHeadAttention to accelerate autoregressive inference. A practical Whisper ASR integration example with end-to-end flow (loading audio, language detection, transcription) and 30-second input truncation demonstrated real-world usability. CI and Windows workflow improvements were implemented to improve build efficiency and compatibility (Windows SDK setup for Protobuf/SwiftShader; updated tests for Torch 2.9.0 and ONNX external data). Additionally, advanced transformer support and tensor reshaping enhancements were shipped (new attention variants, reduced unnecessary contiguous calls, unified view/reshape, expanded tests). These efforts collectively improve deployment flexibility, reduce runtime overhead, and strengthen cross-platform development and testing pipelines.
October 2025
13 Commits • 5 Features
Oct 1, 2025October 2025 monthly summary for Tencent/ncnn focused on expanding ONNX compatibility, boosting autoregressive inference performance, and strengthening CI/Windows support, while delivering practical examples and expanded transformer tooling. Key outcomes include expanded ONNX support in PNNX (grid sampling, dynamic resizing, improved constant input handling and padding value conversions) along with a legacy opset compatibility fix, enabling broader model coverage and smoother migration from older models. Performance optimizations were delivered via a key-value cache for MultiHeadAttention to accelerate autoregressive inference. A practical Whisper ASR integration example with end-to-end flow (loading audio, language detection, transcription) and 30-second input truncation demonstrated real-world usability. CI and Windows workflow improvements were implemented to improve build efficiency and compatibility (Windows SDK setup for Protobuf/SwiftShader; updated tests for Torch 2.9.0 and ONNX external data). Additionally, advanced transformer support and tensor reshaping enhancements were shipped (new attention variants, reduced unnecessary contiguous calls, unified view/reshape, expanded tests). These efforts collectively improve deployment flexibility, reduce runtime overhead, and strengthen cross-platform development and testing pipelines.
September 2025
16 Commits • 3 Features
Sep 1, 2025September 2025 performance summary for Tencent/ncnn focusing on Vulkan/GEMM GPU compute optimization, ONNX-to-PNNX model conversion enhancements, and API/CI stability improvements. The work delivered tangible improvements in performance, interoperability, and build reliability, directly supporting faster inference, broader model support, and more robust development workflows across platforms.
16 Commits • 3 Features
Sep 1, 2025September 2025 performance summary for Tencent/ncnn focusing on Vulkan/GEMM GPU compute optimization, ONNX-to-PNNX model conversion enhancements, and API/CI stability improvements. The work delivered tangible improvements in performance, interoperability, and build reliability, directly supporting faster inference, broader model support, and more robust development workflows across platforms.
September 2025
August 2025
16 Commits • 5 Features
Aug 1, 2025August 2025 performance review: Delivered substantial enhancements across tensor/model manipulation, Vulkan data transfer, and robust model conversion, with cross-platform CI improvements and a Piper TTS example to showcase portability. The work directly enhances model portability, runtime efficiency on Vulkan backends, and CI reliability, enabling faster iteration and safer deployments across Windows, RISCV, and QEMU environments.
August 2025
16 Commits • 5 Features
Aug 1, 2025August 2025 performance review: Delivered substantial enhancements across tensor/model manipulation, Vulkan data transfer, and robust model conversion, with cross-platform CI improvements and a Piper TTS example to showcase portability. The work directly enhances model portability, runtime efficiency on Vulkan backends, and CI reliability, enabling faster iteration and safer deployments across Windows, RISCV, and QEMU environments.
July 2025
12 Commits • 4 Features
Jul 1, 2025July 2025 Tencent/ncnn monthly summary focusing on business value and technical achievements. Key Vulkan backend enhancements, license compliance improvements, and CI/tooling upgrades contributed to broader compatibility, reliability, and performance across platforms with improved tensor support and validation workflows.
12 Commits • 4 Features
Jul 1, 2025July 2025 Tencent/ncnn monthly summary focusing on business value and technical achievements. Key Vulkan backend enhancements, license compliance improvements, and CI/tooling upgrades contributed to broader compatibility, reliability, and performance across platforms with improved tensor support and validation workflows.
July 2025
June 2025
24 Commits • 16 Features
Jun 1, 2025June 2025 Tencent/ncnn monthly performance summary. This period focused on delivering high-impact features, improving inference performance and portability, and stabilizing CI across environments. Key outcomes include targeted norm improvements, expanded dequantization support, Vulkan shader/memory feature work, and CI modernization, coupled with a critical Vulkan validation bug fix that enhances cross-GPU compatibility and reliability. The work demonstrates strong cross-discipline execution across performance optimization, graphics/Vulkan integration, and CI automation, driving faster release cycles and broader hardware support.
June 2025
24 Commits • 16 Features
Jun 1, 2025June 2025 Tencent/ncnn monthly performance summary. This period focused on delivering high-impact features, improving inference performance and portability, and stabilizing CI across environments. Key outcomes include targeted norm improvements, expanded dequantization support, Vulkan shader/memory feature work, and CI modernization, coupled with a critical Vulkan validation bug fix that enhances cross-GPU compatibility and reliability. The work demonstrates strong cross-discipline execution across performance optimization, graphics/Vulkan integration, and CI automation, driving faster release cycles and broader hardware support.
May 2025
27 Commits • 12 Features
May 1, 2025May 2025 performance highlights for Tencent/ncnn: focused on expanding deployment capabilities, improving stability, enriching model demonstrations, and strengthening CI/CD for production readiness. Key user/customer value delivered includes server-side, headless inference support on NVIDIA GPUs, more reliable Vulkan paths, practical model evaluation via new YOLOv11 and Yoloworld examples, and a more stable, scalable CI/CD workflow across Ubuntu 25 and ONNX/PNNX pipelines.
27 Commits • 12 Features
May 1, 2025May 2025 performance highlights for Tencent/ncnn: focused on expanding deployment capabilities, improving stability, enriching model demonstrations, and strengthening CI/CD for production readiness. Key user/customer value delivered includes server-side, headless inference support on NVIDIA GPUs, more reliable Vulkan paths, practical model evaluation via new YOLOv11 and Yoloworld examples, and a more stable, scalable CI/CD workflow across Ubuntu 25 and ONNX/PNNX pipelines.
May 2025
April 2025
50 Commits • 19 Features
Apr 1, 2025April 2025 performance snapshot for Tencent/ncnn focusing on delivering high-value features, stabilizing builds, and expanding cross-platform support. The team emphasized business value through robust ONNX/PNNX integration, faster builds, and more reliable CI across architectures while continuing to improve code quality and inference validation.
April 2025
50 Commits • 19 Features
Apr 1, 2025April 2025 performance snapshot for Tencent/ncnn focusing on delivering high-value features, stabilizing builds, and expanding cross-platform support. The team emphasized business value through robust ONNX/PNNX integration, faster builds, and more reliable CI across architectures while continuing to improve code quality and inference validation.
March 2025
13 Commits • 4 Features
Mar 1, 2025March 2025: Tencent/ncnn delivered major GPU acceleration, dynamic shape handling, and cross-architecture inference improvements, with stronger ONNX compatibility and stability. This period focused on expanding Vulkan-based performance, enabling dynamic shape-driven execution, and broadening model support across architectures, while improving CI quality and environment reliability.
13 Commits • 4 Features
Mar 1, 2025March 2025: Tencent/ncnn delivered major GPU acceleration, dynamic shape handling, and cross-architecture inference improvements, with stronger ONNX compatibility and stability. This period focused on expanding Vulkan-based performance, enabling dynamic shape-driven execution, and broadening model support across architectures, while improving CI quality and environment reliability.
March 2025
February 2025
11 Commits • 5 Features
Feb 1, 2025February 2025 performance and tooling highlights for Tencent/ncnn. Focused on quantization robustness, CPU inference optimizations, and developer tooling to accelerate model deployment. This work delivered quantization improvements, int8 on x86 optimizations, enhanced quantization/model conversion tooling, Vulkan/SPIR-V toolchain updates, and PNNX toolkit enhancements, collectively improving deployment efficiency, memory usage, and device coverage.
February 2025
11 Commits • 5 Features
Feb 1, 2025February 2025 performance and tooling highlights for Tencent/ncnn. Focused on quantization robustness, CPU inference optimizations, and developer tooling to accelerate model deployment. This work delivered quantization improvements, int8 on x86 optimizations, enhanced quantization/model conversion tooling, Vulkan/SPIR-V toolchain updates, and PNNX toolkit enhancements, collectively improving deployment efficiency, memory usage, and device coverage.
January 2025
7 Commits • 3 Features
Jan 1, 2025January 2025 performance summary for Tencent/ncnn. Focused on delivering high-impact features, improving model loading reliability, optimizing core math paths, and strengthening testing infrastructure to boost build speed and code quality. The work enhanced real-world usability of the framework for computer vision workloads while reducing maintenance friction and enabling faster iterations.
7 Commits • 3 Features
Jan 1, 2025January 2025 performance summary for Tencent/ncnn. Focused on delivering high-impact features, improving model loading reliability, optimizing core math paths, and strengthening testing infrastructure to boost build speed and code quality. The work enhanced real-world usability of the framework for computer vision workloads while reducing maintenance friction and enabling faster iterations.
January 2025
December 2024
21 Commits • 9 Features
Dec 1, 2024Month: 2024-12 — Tencent/ncnn Overview: This month focused on delivering portable vectorization, accelerating inference performance, strengthening the ONNX import pipeline, and boosting cross-platform build stability. The team advanced SIMD-based optimizations, expanded CI coverage, and hardened the PNNX/ONNX workflow to support broader hardware targets and more reliable model deployment. Key features delivered: - Port RVV intrinsic 1.0+ integration to enable vectorized operations on RISC-V targets (#5642). - GEMM int8 SIMD optimization for x86 across SSE2/XOP/AVX/AVX512/VNNI/VNNIint8, improving int8 inference throughput (#5763). - PNNX ONNX conversion and input handling enhancements: convert select to crop and squeeze; auto inputshape from traced inputs; match ONNX zeros/ones (#5826-#5828, #5832). - PNNX ONNX clip conversion fix and tests to ensure correct clipping behavior and test coverage (#5834). - PNNX build, CI improvements, and cross-platform reliability: macOS/Windows build fixes, quick test CI, and CI args adjustments for WebAssembly/Node.js; Android/Clang fixes; stability changes for CI (#5838, #5843, #5845, #5842, #5846). - CI coverage expansion for RISCV: added C908 and spacemit X60 CI (#5850, #5852). Major bugs fixed: - PNNX ONNX clip conversion fix and tests with clamps and consistent outputs (#5834). - CI WebAssembly and Node.js args adjustments to align with node>20 changes (#5843). - Android build fixes (NDK r16b CI) and Clang AVX-512 BF16 build fixes (#5845, #5842). - CI stability improvements including disabling WOA SVML optimization to stabilize tests (#5846). - Android linking: define empty assertion termination function to fix linking with older NDK; later revert to maintain compatibility (#5847, #5854). Overall impact and accomplishments: - Significantly improved cross-architecture performance and portability, enabling more efficient deployment of NCNN models on diverse devices (x86, ARM, RISCV). - Strengthened the ONNX import path (Pnnx) for broader model compatibility and easier model evolution, reducing manual tuning. - Expanded CI coverage and stability across platforms (macOS/Windows/Android/WebAssembly/RISCV), speeding up integration cycles and reducing flaky builds. Technologies/skills demonstrated: - SIMD/vectorization (RVV, x86 AVX/AVX512, VNNI) and performance optimization for int8 operations. - PNNX/ONNX import pipeline enhancements, including auto input shapes and operator mappings. - Cross-platform build engineering (macOS/Windows/Android/WebAssembly), NDK compatibility, and CI/CD automation. - Test-driven validation for model conversion and clipping behavior; release engineering (URL updates).
December 2024
21 Commits • 9 Features
Dec 1, 2024Month: 2024-12 — Tencent/ncnn Overview: This month focused on delivering portable vectorization, accelerating inference performance, strengthening the ONNX import pipeline, and boosting cross-platform build stability. The team advanced SIMD-based optimizations, expanded CI coverage, and hardened the PNNX/ONNX workflow to support broader hardware targets and more reliable model deployment. Key features delivered: - Port RVV intrinsic 1.0+ integration to enable vectorized operations on RISC-V targets (#5642). - GEMM int8 SIMD optimization for x86 across SSE2/XOP/AVX/AVX512/VNNI/VNNIint8, improving int8 inference throughput (#5763). - PNNX ONNX conversion and input handling enhancements: convert select to crop and squeeze; auto inputshape from traced inputs; match ONNX zeros/ones (#5826-#5828, #5832). - PNNX ONNX clip conversion fix and tests to ensure correct clipping behavior and test coverage (#5834). - PNNX build, CI improvements, and cross-platform reliability: macOS/Windows build fixes, quick test CI, and CI args adjustments for WebAssembly/Node.js; Android/Clang fixes; stability changes for CI (#5838, #5843, #5845, #5842, #5846). - CI coverage expansion for RISCV: added C908 and spacemit X60 CI (#5850, #5852). Major bugs fixed: - PNNX ONNX clip conversion fix and tests with clamps and consistent outputs (#5834). - CI WebAssembly and Node.js args adjustments to align with node>20 changes (#5843). - Android build fixes (NDK r16b CI) and Clang AVX-512 BF16 build fixes (#5845, #5842). - CI stability improvements including disabling WOA SVML optimization to stabilize tests (#5846). - Android linking: define empty assertion termination function to fix linking with older NDK; later revert to maintain compatibility (#5847, #5854). Overall impact and accomplishments: - Significantly improved cross-architecture performance and portability, enabling more efficient deployment of NCNN models on diverse devices (x86, ARM, RISCV). - Strengthened the ONNX import path (Pnnx) for broader model compatibility and easier model evolution, reducing manual tuning. - Expanded CI coverage and stability across platforms (macOS/Windows/Android/WebAssembly/RISCV), speeding up integration cycles and reducing flaky builds. Technologies/skills demonstrated: - SIMD/vectorization (RVV, x86 AVX/AVX512, VNNI) and performance optimization for int8 operations. - PNNX/ONNX import pipeline enhancements, including auto input shapes and operator mappings. - Cross-platform build engineering (macOS/Windows/Android/WebAssembly), NDK compatibility, and CI/CD automation. - Test-driven validation for model conversion and clipping behavior; release engineering (URL updates).
November 2024
5 Commits • 2 Features
Nov 1, 2024November 2024 monthly summary for Tencent/ncnn. Focused on delivering high-impact features, fixing critical issues, and improving cross-platform reliability. Resulted in tangible business value through faster inference, expanded audio preprocessing capabilities, and more robust build/deployment pipelines.
5 Commits • 2 Features
Nov 1, 2024November 2024 monthly summary for Tencent/ncnn. Focused on delivering high-impact features, fixing critical issues, and improving cross-platform reliability. Resulted in tangible business value through faster inference, expanded audio preprocessing capabilities, and more robust build/deployment pipelines.
November 2024
October 2024
11 Commits • 7 Features
Oct 1, 2024October 2024 performance and stability enhancement for Tencent/ncnn focused on accelerating inference, improving model loading, and broadening hardware compatibility. Major work delivered across quantization, model loading, and cross-architecture optimizations, with strong emphasis on maintaining numerical integrity and business-ready performance. The month culminated in tangible speedups and broader deployment scenarios across ARM, x86, and HarmonyOS environments.
October 2024
11 Commits • 7 Features
Oct 1, 2024October 2024 performance and stability enhancement for Tencent/ncnn focused on accelerating inference, improving model loading, and broadening hardware compatibility. Major work delivered across quantization, model loading, and cross-architecture optimizations, with strong emphasis on maintaining numerical integrity and business-ready performance. The month culminated in tangible speedups and broader deployment scenarios across ARM, x86, and HarmonyOS environments.
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Quality Metrics
Correctness90.6%
Maintainability83.4%
Architecture86.6%
Performance86.8%
AI Usage61.8%
Skills & Technologies
Programming Languages
CC++CMakeGLSLMarkdownPowerShellPythonShellYAML
Technical Skills
API designAPI developmentARM NEON intrinsicsARM NEON optimizationARM architectureARM assemblyARM developmentAVXAVX programmingAVX2AVX512AVX512 optimizationAlgorithm OptimizationAlgorithm optimizationAndroid Development
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline