ThunderKittens：a simple yet faster flashattention alternative

[sorasoras]

ThunderKittens is an embedded domain-specific language (DSL) within CUDA designed to simplify the development of high-performance AI kernels on GPUs. It provides abstractions for working with small tiles (e.g., 16x16) of data, which aligns well with the capabilities of modern GPU architectures and tensor cores.

Performance: Despite its simplicity, kernels written in ThunderKittens can match or outperform hand-written CUDA kernels. For example, on the H100 GPU, a ThunderKittens implementation of the forward flash attention kernel outperforms FlashAttention-2 by around 30%.

On 4090s and A100s, TK matches FA2 performance in just a few lines of code.

On H100s, TK is faster forward and backward than FA2 by quite a bit -- so there is no tradeoff of clean versus speed (in this case!)

Tiles Seem Pretty General Coming soon -- ThunderKittens on AMD hardware!

https://hazyresearch.stanford.edu/blog/2024-05-12-tk

https://github.com/HazyResearch/ThunderKittens

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This could be alternative to FA2 AMD would have support latter as well.

[shimmyshimmer]

Yes thanks for being on the lookout! We will mostly likely be implementing this pretty soon!