Generates GPU kernels for CUDA, HIP, Metal, and CPU via Python.
npx skills add https://github.com/jstzwj/ai-infra-plugins --skill tilelang
Please help me install this Agent Skill. Skill: tilelang Source: https://github.com/jstzwj/ai-infra-plugins/tree/main/plugins/tilelang/skills/tilelang Command: npx skills add https://github.com/jstzwj/ai-infra-plugins --skill tilelang
TileLang simplifies the development of high-performance GPU kernels by providing a framework that automatically dispatches to hardware-optimized instructions, reducing complexity for engineers.
Write a TileLang kernel to perform matrix multiplication, compile, and execute it directly within your Python environment.
High-intent search queries and answers about installing and using this skill.
Automate GPU kernel generation by writing a Python interface that dispatches hardware-optimized instructions to CUDA, HIP, Metal, or CPU backends, minimizing manual tuning for deep learning and scientific computation scenarios.
Develop high-performance GEMM kernels by leveraging deep API primitives for memory management and tensor core operations, generating efficient code that maximizes hardware utilization for AI model training and inference.
You do not need TensorFlow; compilation and execution require a Python environment along with dependencies including TVM, Torch, and NumPy to facilitate the kernel creation workflow.
You can access low-level primitives for memory management, data movement, and tensor core operations, enabling fine-grained control over hardware-optimized instructions for HIP architectures.
Manual GPU kernel tuning requires extensive low-level hardware knowledge, whereas automated code dispatching abstracts these complexities, automatically generating optimized instructions for CUDA, HIP, Metal, and CPU architectures.
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