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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Agentic Kernel Optimization for All — automated GPU kernel optimization for any kernel, any hardware, any language
| Date | Stars |
|---|---|
| 2026-07-31 | 335 |
| 2026-08-05 | 340 |
| 2026-08-06 | 340 |
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<h1 align="center">AKO4ALL</h1> <p align="center"><b>Agentic Kernel Optimization for All</b></p> <p align="center"> <a href="https://tongminglaic.github.io/AKO"><img src="https://img.shields.io/badge/Project-Page-blue" alt="Project Page"></a> <a href="https://github.com/TongmingLAIC/AKO4X"><img src="https://img.shields.io/badge/GitHub-AKO4X-blue?logo=github" alt="AKO4X"></a> <a href="https://tongminglaic.github.io/AKO/assets/ako-tech-report.pdf"><img src="https://img.shields.io/badge/Tech%20Report-PDF-blue" alt="Tech Report"></a> </p> <p align="center"><b>If you find our work useful, please consider giving us a star 🌟</b></p> <p align="center"> <img src="assets/speedup_vs_expert.png" alt="Bar chart: AKO4ALL geomean speedup over the FlashInfer expert on four inference operators — GQA decode 1.36x, MLA decode 1.21x, MLA prefill 1.50x, RMSNorm 1.12x — on NVIDIA B200; all four bars clear the 1.0x expert line." width="640" /> <br/> <i>Geomean speedup over the FlashInfer <b>expert</b> baseline (the strongest kernel FlashInfer ships) on NVIDIA B200 — every op clears the expert. Full table in <a href="#results">Results</a>.</i> </p> ## News - 📄 **[2026.05.31]** The **[AKO tech report](https://tongminglaic.github.io/AKO/assets/ako-tech-report.pdf)** is now available. - 🚀 **[2026.05.31]** [**AKO4X**](https://github.com/TongmingLAIC/AKO4X) is now open-source — the closed-loop, campaign-based system behind our [MLSys 2026 competition](https://mlsys26.flashinfer.ai/) entry. - ✨ **[2026.05.31]** **AKO4ALL** is now a single drop-in [Claude Code](https://docs.anthropic.com/en/docs/claude-code) skill — invoke it in any working directory. - 🚀 **[2026.03.24]** AKO4ALL is released. **Table of Contents** - [What is AKO4ALL?](#what-is-ako4all) - [What You Provide](#what-you-provide) - [Install](#install) - [How to Use](#how-to-use) - [Requirements](#requirements) - [How It Works](#how-it-works) - [Results](#results) - [Agent Behavior](#agent-behavior) - [Permissions](#permissions) - [Repo Layout](#repo-layout) - [Example: SOL-ExecBench](#example-sol-execbench) - [Anti-Cheat](#anti-cheat) - [FAQ](#faq) - [Tech Report](#tech-report) - [Acknowledgments](#acknowledgments) ## What is AKO4ALL? **AKO4ALL is automated GPU kernel optimization, packaged as a single [Claude Code](https://docs.anthropic.com/en/docs/claude-code) skill.** Drop a kernel into your working directory, invoke the skill, and the agent bootstraps a workspace in place and iteratively rewrites the kernel for maximum performance — profile, edit, benchmark, repeat, until the kernel stops getting faster. The skill is a single `SKILL.md` protocol document; other coding agents can drive the same loop by following it directly. <p align="center"> <img src="assets/hero.png" alt="A cartoon robot agent at a single workshop bench iterates on a glowing GPU kernel cube — with iteration logbook, profiler, timer, and commit stamp at hand, and a speedup chart on the chalkboard — illustrating AKO4ALL's single-session, drop-in kernel optimization loop." width="780" /> </p> **AKO4ALL vs [AKO4X](https://github.com/TongmingLAIC/AKO4X)** — two sibling projects with different framings. - **Form:** AKO4ALL is a single Claude Code skill that runs in place in your working directory. AKO4X is a template repository that builds a fresh isolated child environment for each run. - **Unit of work:** AKO4ALL is *one continuous optimization run on one kernel* — resumable across chat sessions, but with no memory carried into the next run on the same kernel. AKO4X is a *multi-round campaign on one operator* — a persistent master agent spawns rounds back-to-back, and a per-operator archive accumulates each round's results so the Nth round is informed by all earlier rounds. - **Harness evolution:** AKO4ALL's protocol is static — you can supply behavior directives, but the skill itself does not change. AKO4X has an opt-in *harness co-evolution* mode in which the agent, after each round, can propos
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matched fp:31e7867db701177c, llm:Repository description: 'Agentic Kernel Optimization for All — automated GPU kernel optimization for any kernel, any hardware, any language' (Python)
matched fp:31e7867db701177c, llm:Repository description: 'Agentic Kernel Optimization for All — automated GPU kernel optimization for any kernel, any hardware, any language' (Python)