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Xiaoyu Zhang

PROFILE

Xiaoyu Zhang

Worked on model optimization, deployment, and documentation across the yhyang201/sglang and zhaochenyang20/Awesome-ML-SYS-Tutorial repositories, focusing on deep learning and performance engineering. Delivered end-to-end improvements for models like Wan2.2, Mistral Large, Hunyuan3D, and Kimi-K2.5 by integrating CUDA-based optimizations, refining kernel efficiency, and enhancing CI/CD reliability. Enhanced documentation with detailed code walk-throughs and deployment guidance for multi-node inference, including ZeroMQ IPC references and standardized formatting. Used Python, CUDA, and PyTorch to implement configurable optimization frameworks, enable piecewise CUDA graphs, and streamline inference pipelines, resulting in improved model performance, reduced latency, and more robust deployment workflows.

Overall Statistics

Feature vs Bugs

100%Features

Repository Contributions

15Total
Bugs
0
Commits
15
Features
10
Lines of code
2,001
Activity Months2

Work History

May 2026

13 Commits • 9 Features

May 1, 2026

May 2026 focused on boosting performance, reliability, and deployment readiness across Wan2.2, Mistral Large, Hunyuan3D, and Kimi-K2.5. Delivered end-to-end model optimization for Wan2.2 with diffusion integration, CI stabilization, and backend defaults; introduced a configurable optimization framework for Mistral Large; enhanced Hunyuan3D export quality; enabled piecewise CUDA graphs and improved token handling for Kimi-K2.5; and pushed multiple inference and kernel efficiency improvements (CFG gating, FP32 LayerNorm caching, RMSNorm/LTX2 kernel optimizations, VSA attention refactor, and JIT routing). These changes collectively increase model performance, reduce latency, stabilize benchmarking, and enable scalable deployment, delivering clear business value.

December 2024

2 Commits • 1 Features

Dec 1, 2024

December 2024 monthly summary for zhaochenyang20/Awesome-ML-SYS-Tutorial focused on documentation improvements and minor bug fixes in SGLang. Delivered key feature updates: improved code walk-through and inline guidance for Scheduler management of the Radix Cache and the deployment sequences for TokenizerManager and DetokenizerManager in multi-node inference scenarios; added a ZeroMQ IPC reference in the docs; corrected a minor typo ('charactor' to 'character') with consistent code-reference formatting.

Activity

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Quality Metrics

Correctness92.0%
Maintainability86.6%
Architecture88.0%
Performance90.6%
AI Usage44.0%

Skills & Technologies

Programming Languages

CUDAMarkdownPython

Technical Skills

3D ModelingCI/CDCUDAConfiguration ManagementData ProcessingDeep LearningDocumentationGPU ProgrammingGPU programmingMachine LearningModel OptimizationPerformance OptimizationPerformance optimizationPipeline ConfigurationPyTorch

Repositories Contributed To

2 repos

Overview of all repositories you've contributed to across your timeline

yhyang201/sglang

May 2026 May 2026
1 Month active

Languages Used

CUDAMarkdownPython

Technical Skills

3D ModelingCI/CDCUDAConfiguration ManagementData ProcessingDeep Learning

zhaochenyang20/Awesome-ML-SYS-Tutorial

Dec 2024 Dec 2024
1 Month active

Languages Used

Markdown

Technical Skills

Documentation