Floating point type represents a number by storing its significant digits and its exponent separately on separate binary words so it fits in 16, 32, 64 or 128 bits.
Fixe
One issue not covered is the answers is a power consumption. Though it highly depends on specific hardware architecture, usually FPU consumes much more energy than ALU in CPU thus if you target mobile applications where power consumption is important it's worth consider fixed point impelementation of the algorithm.