What important bits are those? I can't imagine what you have in mind here; my current job and my previous job have both revolved around MLIR-based compilers, and it has never seemed to me that there is anything missing. I wonder if you might be expecting MLIR to do a job it's not really meant for.

> There’s very little common usable infrastructure that is upstreamed

Hmm I wonder what all that stuff is then that's under mlir/lib?

Like what are you even talking about? First of all there are literally three upstream frontends (flang, ClangIR, and torch-mlir). Most people use PyTorch as a frontend (some people use Jax or Triton). Secondly, downstream users having their own dialects... is basically the whole point of MLIR. Core dialects like linalg, tensor, memref, arith are absolutely generically useful. In addition many (not all) MLIR-based production quality compilers are fully open source (IREE, Triton) even if wholly developed at a for-profit.

I'd be interested to learn about such closed-source important bits and invite them to MLIR workshop / open developer meeting. Having worked on the project essentially since its inception, I am quite positive that the bits the original MLIR team considered important are completely open source.

Certainly, there are closed-source downstream dialects, that was one of the actual design goals of the project, but they are rarely as useful as one might think. I'd expect every big company with a hardware to have an ISA/intrinsic-level dialect, at least as a prototype, that they won't open source for the same reason they won't open source the ISA.

What I find sad is the lack is that end-to-end flows from, e.g., PyTorch to binaries are usually living outside of the LLVM project, and often in each company's downstream. There is some slow motion to fix that.