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This project is from CMU. Hazy Research at Stanford talked about the megakernel too: https://hazyresearch.stanford.edu/blog/2025-05-27-no-bubbles

Good to see the competition in this area.

(Edited): Related paper covering the larger "mirage" project, but this doesn't cover the "megakernel" approach: https://arxiv.org/abs/2405.05751

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This is the writer of the blog post. You are right that Stanford's work is a parallel effort. The main difference is that our focus is on compilation: making it easier to generate megakernels automatically.

And their focus is..?

Ooops, missed one sentence in my previous response. Stanford's MegaKernel project tackles a similar challenge but focuses on manual CUDA implementation. While MPK takes a compiler-driven approach—users express their LLMs at the PyTorch level, and MPK automatically compiles them into optimized megakernels. Our goal is to make programming megakernels much more accessible.

Hazy Research also has ThunderKittens, pretty cool library. There's a lot of effort to really formalize, pipeline, divide and conquer in the current NVIDIA GPU model for maximize GPU efficiency, and to write compilers/DSL's for things, it seems.

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