KernelWiki
OfficialOptimize NVIDIA GPU kernels with expert knowledge
Authormit-han-lab
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill provides expert knowledge for optimizing NVIDIA Blackwell (SM100, B200) and Hopper (SM90, H100) GPU kernels, enabling users to improve performance and efficiency.
Core Features & Use Cases
- Kernel Optimization: Offers insights into performance patterns, techniques, and specific kernel case studies for both architectures.
- Performance Patterns: Helps identify issues like low SM utilization, memory-bound, register pressure, and compute-bound scenarios.
- DSLs & Languages: Provides guidance on using CuTe DSL, CUDA C++ with PTX inline, Triton on Blackwell, and other relevant languages/DSLs.
- Migration Guides: Offers guidance for migrating Hopper features to Blackwell.
- PR References: Allows users to query specific PRs for implementation details.
Quick Start
Use the KernelWiki skill to search for information on optimizing a specific kernel, such as python3 scripts/query.py "optimization for FlashAttention-4".
Dependency Matrix
Required Modules
PyYAML
Components
scriptsreferencesassets
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: KernelWiki Download link: https://github.com/mit-han-lab/KernelWiki/archive/main.zip#kernelwiki Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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