[Rickertsen2]

Originally Posted by Mark McLeod

Most of the problems with the processor keeping up that I've run across with various teams have been due to inefficient and bloated code. They more often run out of programming space than processor time. The most common exception has been bloated interrupt handlers causing multiple interrupts to be missed. The code problems are to be expected with people learning to program for the first time and attempting to implement complex equations from their math textbook.
The cautions are more directed at the neophytes than experienced programmers.

I did some measurements last Fall on the Robovation (formerly EDU) controller and came up with:
v45% more program space than the equivalent operation using integer math is what’s roughly required for simple floating-point operations (e.g., a=10.5*2.3 vs i=105*23)
v22% more time is required for equivalent float vs. integer operations

I no longer remember the details as to what percentage of program space was due to a one time floating point library and what each additional statement demands. It just takes a minute or two to run the test though.

Where did you come up with these figures? The time difference btw float and fixed/decimal depends on the operation. For some operations its not that great. For others it is very large. Same with the instruction cycles.