[DarkUranium]

I very commonly see fixed-point libs be slower than floating-point (assuming floating-point hardware is available --- soft-float is slow as hell compared to fixed-point, of course).

Commonly enough that I think it's some fundamental reason (given available/current hardware as opposed to hypothetical).

Two reasons I can think of, though granted, they only apply in certain niches:

1) Floating-point SIMD extensions are far more common than integer ones. This means you can compute N (often N=4 or 8) float operations in one instruction, vs 1 integer operation.

2) For any GPGPU processing: GPUs far prefer floats, to the point where you didn't even use to have integers available (somewhat ironically, the platforms that prefer float much more strongly to int are mobile/embedded ones nowadays --- which is the exact opposite of the CPU situation). To this day, you have a `mul24` intrinsic for integer multiplication in some languages ... which converts two integers to floats, multiplies them as floats, and then converts back to integers. Yes, that was faster than direct multiplication. I'm sure many GPUs do it directly nowadays though.

It's also worth considering that a typical fixed-point multiply (as opposed to integer) is an integer multiply followed by a shift; often to a 2×-bit intermediate, if you want to preserve precision. That's a cost.