Very glad to see that Halide keeps being developed, despite remaining a bit of a niche language (for now). Anything that makes squeezing out more performance f

Very glad to see that Halide keeps being developed, despite remaining a bit of a niche language (for now). Anything that makes squeezing out more performance from our computers while writing more elegant code at the same time deserves more attention. I wonder if any of the techniques used in Halide can be (somewhat) generalized to domains outside of image processing? EDIT: Ah, I see that the paper basically answers my questions, as it sees applications in ML contexts. Also, theat new demosaicking algorithm looks great, wonder if will make it's way to DarkTable any time soon? The page of the paper[0] also has presentation slides[1] which (to me at least) feel a bit more accessible. Hope the accompanying presentation will be on YouTube soon. [0] http://gradient.halide.ai/ http://gradient.halide.ai/ [1] https://people.csail.mit.edu/tzumao/gradient_halide/gradient_halide_slides.pdf https://people.csail.mit.edu/tzumao/gradient_halide/gradient...