add-jit-kernel

Community

Add 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 required

Components

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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