vllm-project/vllm-ascend
Dec 2025 – Dec 2025
1 Month active
Languages Used
Python
Technical Skills
Kernel DevelopmentMachine LearningPerformance OptimizationPyTorchTritonbackend development
Ascendyh
PROFILE
Ascendyh
During December 2025, Osiris contributed kernel optimizations to the vllm-project/vllm-ascend repository, focusing on performance improvements for Ascend NPUs. Osiris developed two Triton-based kernels in Python: a fused GDN gating kernel to accelerate Gated Delta Net workflows and an L2 normalization kernel to optimize tensor operations. The implementation maintained backward compatibility, requiring no user-facing API changes, and included updates to backend wrappers. Osiris validated the new kernels against vLLM v0.12.0 and v0.13.0 branches, ensuring robust integration. The work demonstrated depth in kernel development, machine learning, and performance optimization, with collaborative code review and sign-off processes.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
2Total
Bugs
0
Commits
2
Features
1
Lines of code
245
Activity Months1
Your Network
218 peopleWork History
December 2025
2 Commits • 1 Features
Dec 1, 2025Month: 2025-12 — vLLM Ascend kernel optimizations milestone. Delivered two Triton-based kernels for Ascend NPUs, including a fused GDN gating kernel and an L2 normalization kernel, with no user-facing API changes. These changes target performance improvements for Gated Delta Net workflows and tensor operations. Validated against vLLM v0.12.0 and v0LLM main v0.13.0, with backend wrappers updated to support the new kernels. Commit highlights: b2c121637fd8b8045e66e24ea0f63cb17ffb3b69 (PR #4304) and a90482803dc12ede67028d4b83e029fde48f1adf (PR #4595). Co-authored-by: Mengqing Cao; Signed-off-by: Ascendyh.
2 Commits • 1 Features
Dec 1, 2025Month: 2025-12 — vLLM Ascend kernel optimizations milestone. Delivered two Triton-based kernels for Ascend NPUs, including a fused GDN gating kernel and an L2 normalization kernel, with no user-facing API changes. These changes target performance improvements for Gated Delta Net workflows and tensor operations. Validated against vLLM v0.12.0 and v0LLM main v0.13.0, with backend wrappers updated to support the new kernels. Commit highlights: b2c121637fd8b8045e66e24ea0f63cb17ffb3b69 (PR #4304) and a90482803dc12ede67028d4b83e029fde48f1adf (PR #4595). Co-authored-by: Mengqing Cao; Signed-off-by: Ascendyh.
December 2025
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Quality Metrics
Correctness100.0%
Maintainability80.0%
Architecture100.0%
Performance90.0%
AI Usage60.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
Kernel DevelopmentMachine LearningPerformance OptimizationPyTorchTritonbackend developmentmachine learning
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