add-jit-kernel
CommunityAdd custom CUDA kernels to SGLang
Authorrayleizhu
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill provides a structured, step-by-step guide to integrate new, lightweight CUDA kernels into the SGLang framework, streamlining the development of custom high-performance operations.
Core Features & Use Cases
- JIT Kernel Integration: Learn how to implement and register custom CUDA kernels using Just-In-Time (JIT) compilation within SGLang.
- Abstractions: Utilizes SGLang's provided C++ and CUDA abstractions for safer and more consistent kernel development.
- Use Case: Developers can add specialized tensor operations, like custom activation functions or element-wise transformations, directly into SGLang for use in their machine learning models.
Quick Start
Follow the tutorial to implement a new JIT kernel by creating the necessary C++ and CUDA files and adding a Python wrapper.
Dependency Matrix
Required Modules
None requiredComponents
scriptsreferencesassets
💻 Claude Code Installation
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Please help me install this Skill: Name: add-jit-kernel Download link: https://github.com/rayleizhu/sglang/archive/main.zip#add-jit-kernel Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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