maderix/ANE

原文摘要

Training neural networks on Apple Neural Engine via reverse-engineered private APIs ANE Training — Backpropagation on Apple Neural Engine Training neural networks directly on Apple's Neural Engine (ANE) via reverse-engineered private APIs. No CoreML training APIs, no Metal, no GPU — pure ANE compute. Project Scope & Intent I'm genuinely grateful for all the attention this project has received — I never expected a weekend research hack to blow up like this. Thank you to everyone who starred, forked, ran benchmarks on their own hardware, and shared the work. It means a lot. That said, I want to set clear expectations about what this project is and isn't. This is a research project , not a production framework. The goal was to demonstrate that training on the Apple Neural Engine — and potentially other NPUs — is possible , and that the barrier has always been software support, not hardware capability. The ANE is a remarkably capable piece of silicon that Apple restricts to inference-only use through CoreML. This project bypasses that restriction using reverse-engineered private APIs to show what's possible when you give the hardware a chance. What This Project Is A proof of concept fo…