I hadn't heard of Furthark before, very cool project. I've actually had "Learn How to write a compiler by writing an APL that supports GPU-optimized numerical o

I hadn't heard of Furthark before, very cool project. I've actually had "Learn How to write a compiler by writing an APL that supports GPU-optimized numerical ops." Part of the reason that I was interested in working on such a project (besides the fact that I find APL, GPU compute, and compilers really interesting) Is that I feel like the rise of new compute platforms (GPUs, BLAST accelerators, Neural Net accelerators, Crypto ASICs, etc.) and open hardware (RISC-V) could motivate a new wave of research in compilers (I guess that is what MLIR is). It's really easy to picture how having a family of programming language for every class of accelerators can go very wrong, but it's kinda cool to picture what it would be like if biology, chemistry, meteorology, astrophysics, and other quantitative fields had open-source hardware accelerators and software stacks that became foundational components which "normal" programmers rarely ever touched. Then when we finally get practical quantum computing down to the size of something that could go in a PCI-E slot, there will already be a compilation toolchain waiting to target it.