3 ms·

Floating point calculations used to be a lot slower than integer calculations so it was very common to use fixed point numbers. Also for good performance, you w

Floating point calculations used to be a lot slower than integer calculations so it was very common to use fixed point numbers. Also for good performance, you would usually not do what this code does, calculate the coordinates for each pixel explicitly. Instead you would calculate the coordinates of the starting corner and the delta between adjacent pixels and then just add the delta each time you move to the next pixel. That is also generally easier to do with fixed point numbers as adding 0.1 with floating point numbers a 1000 times will not yield 100 because 0.1 is not exactly representable with base 2 floating point numbers. For this visualization this probably does not matter too much, but if you care that you are not slightly off and you want to calculate stuff incrementally, then doing it in fixed point might make things easier. I have no clue about the first point on current hardware, if floating point calculations are still notably less performant, if there is a relevant difference in the number of execution units and so on.

adrian_b 1y ago
In very old CPUs and in many microcontrollers, floating-point operations are slower than integer operations. However, in many old but not very old CPUs, e.g. in many from the last decade of the 20th century and from the first decade of this century, floating-point multiplication and division were much faster than integer multiplication and division. So for those CPUs, which include models like Pentium 4, or even the first Intel Core models (those older than Nehalem, which got a dedicated integer multiplier), there were many cases when converting an integer computation into a floating-point computation could increase the speed many times.