Yeah… I’m not too keen on (pure) mathematical abstractions, since I think of what’s happening at the electro-mechanical level. Like for example, Haskell did some important things in my opinion - but it wasn’t type systems (macros are better): the Just-Nothing pattern is one of the best ways to handle errors in my opinion.
So something like Guy Belloch and the CM-5 makes more sense to me, since it tries to model parallel vector primitives: scan, reduce, permute, etc. - there’s still an implicit for all. Actually, it’s very close in terms of the vector abstraction with APL, but APL and friends are like brainfuck to me. It’s too terse. That’s why I gravitate more towards something that is explicit, models the hardware, and maybe a bit more verbose. Readability is important to me and I don’t like terse code.
Though, that’s not to say I want everything as array notation, because it only gets you so far. The relational model for multi-sets is immensely useful, too. But, I try to wedge it around parallel vector primitives - because that’s where the performance is.
That said, this probably doesn’t work to do anything for the performance in lil at all, but it’s the mental model I find most useful to think about vector computations, since it maps really well to the hardware (not necessarily lil’s virtual machine, though). Like Iverson and APL, I don’t necessarily care for the modern math model either (I find right-to-left and inside-out unnatural), but I don’t like APL’s either.