shouldn't the title be "CUDA Tile IR Open Sourced"?
NVIDIA tensor core units, where the second column in kernel optimization is producing a test suite.
Fun game: see how many clicks it takes you to learn what MLIR stands for.
I lost count at five or six. Define your acronyms on first use, people.
Will be interesting to see if Nvidia and other have any interest & energy getting this used by others, if there actually is an ecosystem forming around it.
Google leading XLA & IREE, with awesome intermediate representations, used by lots of hardware platforms, and backing really excellent Jax & Pytorch implementations, having tools for layout & optinization folks can share: they really build an amazing community.
There's still so much room for planning/scheduling, so much hardware we have yet to target. RISC-V has really interesting vector instructions, for example, and it seems like there's so much exploration / work to do to better leverage that.
Nvidia has partners everywhere now. Nvlink is used by Intel, AWS Tritanium, others. Yesterday the Groq exclusive license that Nvidia paid to give to Groq?! Seeing how and when CUDA Tiles emerges: will be interesting. Moving from fabric partnerships, up up up the stack.
>The CUDA Tile IR project is under the Apache License v2.0 with LLVM Exceptions