Replacing floats with fixed point isn’t usually a meaningful optimization on modern CPUs. The FPU runs in parallel to the integer units, so you can easily end up idling the FPU while the integer units are too busy doing both the math and the necessary state management (counters, pointer arithmetic etc.)
This could make sense for SIMD however, but then the problem is getting the array data in the right format before the computation — if you’re converting from float to int and back within the loop, it destroys any performance gain.
Fixed point uses a lot less power though, and many use cases are effectively power limited rather than functional-unit limited, since if you really do fill all functional units on every cycle you'll soon need to throttle back your clock speed...
Perhaps a good example of that is video encoding, which is mostly fixed point, despite it looking like a pretty close fit for floating point maths.
A very good point. My worldview of performance is highly biased towards “full steam ahead” desktop graphics.
Video encoding is a bit of a special case though because the common algorithms are carefully designed for hardware acceleration. For most rendering, it doesn’t make sense to go out of your way to avoid the FPU.
This could make sense for SIMD however, but then the problem is getting the array data in the right format before the computation — if you’re converting from float to int and back within the loop, it destroys any performance gain.