mozilla/onnxruntime
Nov 2024 – Mar 2025
4 Months active
Languages Used
C++Python
Technical Skills
C++C++ developmentCompiler compatibilityMachine LearningPerformance OptimizationSoftware maintenance
liqun Fu
PROFILE
Liqun Fu
Worked on the mozilla/onnxruntime repository, delivering four features and one bug fix over four months focused on deep learning model optimization and performance engineering. Enhanced kernel performance by optimizing SkipLayerNorm and implementing AVX2 acceleration for rotary embedding operations, using C++ and AVX2 programming to target modern hardware. Upgraded ONNX Runtime to v1.17.0, aligning dependencies and adapting code for new operators to ensure compatibility with evolving ONNX specifications. Integrated rotary positional embeddings with FP16 kernels, streamlining the codebase by removing legacy FP32 paths. Emphasized benchmarking, unit testing, and compiler compatibility to improve throughput, maintainability, and future extensibility.
Overall Statistics
Feature vs Bugs
80%Features
Repository Contributions
5Total
Bugs
1
Commits
5
Features
4
Lines of code
2,783
Activity Months4
Your Network
4931 peopleSame Organization
@microsoft.com4926
GitOpsMember
Ananta GuptaMember
Abi GicicMember
Abigail HartmanMember
Abram SandersonMember
Adam EttenbergerMember
Adam KrantzMember
Alexandre GattikerMember
Ami HollanderMember
Work History
March 2025
1 Commits • 1 Features
Mar 1, 2025March 2025 monthly summary for mozilla/onnxruntime: Delivered Rotary Positional Embeddings (RoPE) integration with FP16 kernels, improving generation performance and efficiency. Removed legacy FP32 kernel to streamline the codebase and reduce maintenance. This lays groundwork for broader FP16 deployment in generation workloads (e.g., GQA).
1 Commits • 1 Features
Mar 1, 2025March 2025 monthly summary for mozilla/onnxruntime: Delivered Rotary Positional Embeddings (RoPE) integration with FP16 kernels, improving generation performance and efficiency. Removed legacy FP32 kernel to streamline the codebase and reduce maintenance. This lays groundwork for broader FP16 deployment in generation workloads (e.g., GQA).
March 2025
February 2025
1 Commits • 1 Features
Feb 1, 2025February 2025 — mozilla/onnxruntime: Rotary Embedding AVX2 Optimization delivered. Focused performance engineering on rotary embedding kernels to enable AVX2 acceleration on supported hardware, with new AVX2 implementations and updates to existing code paths. Benchmarks indicate significant performance improvements for rotary embedding operations, contributing to higher throughput in production workloads.
February 2025
1 Commits • 1 Features
Feb 1, 2025February 2025 — mozilla/onnxruntime: Rotary Embedding AVX2 Optimization delivered. Focused performance engineering on rotary embedding kernels to enable AVX2 acceleration on supported hardware, with new AVX2 implementations and updates to existing code paths. Benchmarks indicate significant performance improvements for rotary embedding operations, contributing to higher throughput in production workloads.
December 2024
1 Commits • 1 Features
Dec 1, 2024December 2024 summary for mozilla/onnxruntime: Primary focus on upgrading ONNX Runtime to v1.17.0, aligning dependencies, and adapting code for new operators and ONNX spec changes. This work enhances interoperability, potential performance improvements, and future compatibility with downstream models and tooling. No critical bugs fixed this month; main value comes from upgrade, stabilization, and preparation for downstream adoption.
1 Commits • 1 Features
Dec 1, 2024December 2024 summary for mozilla/onnxruntime: Primary focus on upgrading ONNX Runtime to v1.17.0, aligning dependencies, and adapting code for new operators and ONNX spec changes. This work enhances interoperability, potential performance improvements, and future compatibility with downstream models and tooling. No critical bugs fixed this month; main value comes from upgrade, stabilization, and preparation for downstream adoption.
December 2024
November 2024
2 Commits • 1 Features
Nov 1, 2024Month 2024-11 mozilla/onnxruntime: Focused on performance and portability. Delivered targeted improvements to SkipLayerNorm and fixed GCC 10+ compatibility, delivering tangible business value through faster kernels and broader compiler support.
November 2024
2 Commits • 1 Features
Nov 1, 2024Month 2024-11 mozilla/onnxruntime: Focused on performance and portability. Delivered targeted improvements to SkipLayerNorm and fixed GCC 10+ compatibility, delivering tangible business value through faster kernels and broader compiler support.
Activity
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Quality Metrics
Correctness92.0%
Maintainability84.0%
Architecture92.0%
Performance92.0%
AI Usage36.0%
Skills & Technologies
Programming Languages
C++Python
Technical Skills
AVX2AVX2 programmingC++C++ developmentCompiler compatibilityDeep LearningFP16Machine LearningModel OptimizationPerformance OptimizationPython developmentSoftware maintenanceTensor Operationsbenchmarkingmachine learning
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