triton-ascend-example-layernorm
CommunityTriton Ascend LayerNorm kernel demo.
Authorxchang1121
Version1.0.0
Installs0
System Documentation
What problem does it solve?
LayerNorm reductions and normalization are common building blocks in neural networks; this Skill demonstrates a complete Triton Ascend implementation to perform two-stage reduction (mean/variance) and normalization.
Core Features & Use Cases
- Two-stage reduction: compute statistics then normalize.
- Triton Ascend kernel structure with example code and patterns for block scheduling.
- Use case: building LayerNorm-like kernels on Ascend hardware and extending to other reduce/normalize operators.
Quick Start
Run the Triton Ascend LayerNorm example to validate the kernel on your device.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
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Please help me install this Skill: Name: triton-ascend-example-layernorm Download link: https://github.com/xchang1121/AutoResearch-CC-hook/archive/main.zip#triton-ascend-example-layernorm Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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