cuda-kernel-autodev

Community

Autotune CUDA kernels end-to-end safely

AuthorRomaosir
Version1.0.0
Installs0

System Documentation

What problem does it solve?

It helps you turn a correctness-verified CUDA kernel into a faster one by running an iterative hypothesis → implement → measure → keep-or-revert optimization loop with disciplined logging.

Core Features & Use Cases

  • End-to-end CUDA kernel dev loop: Establishes a correct baseline, then iterates with keep/revert discipline while tracking speedups and correctness across workloads.
  • Roofline- and technique-driven optimization planning: Uses sibling skills to choose what to try next and to apply proven technique patterns for the identified bottleneck.
  • Profiling and experiment governance: Integrates Nsight Compute collection (NCU) and enforces strict experiment hygiene (one focused change per iteration, commit-before-run, monotonic progress expectations).
  • Submission-ready workflow: Wraps up with a final correctness check and produces a reviewable performance report.

Quick Start

Ask an AI to optimize your CUDA kernel to beat a reference baseline on your target GPU using a correctness-gated, keep-or-revert autotuning loop with NCU profiling.

Dependency Matrix

Required Modules

nvidia-sminvcctorchncu-cuda-profilinggitweb-search

Components

references

💻 Claude Code Installation

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Please help me install this Skill:
Name: cuda-kernel-autodev
Download link: https://github.com/Romaosir/IF_Romao_kernel_optimize/archive/main.zip#cuda-kernel-autodev

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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