I have a quick question for constant folding.
When I treated a code twice by changing the data type from 'floating point' to 'integer,'
What I found was:
optimization is done better for the code having int's.
E.g., for this simple code:
It's not about constant folding. The optimizing part of this is "Canonicalize Induction Variables", which as with all of LLVM's loop optimizations, work on integers only.
The reason is that float point math is very difficult to model. You can not, for example, transform this:
double sum = 0;
for (unsigned i = 0; i < j; ++i)
my_double += 0.00001;
my_double = 0.00001 * j;
because the addition in floating point math may not actually change the value. Consider 1000000 + 0.0000001. A float doesn't have enough precision, so the result will equal 1000000, making the result of the loop entirely different than if you were to rewrite it with multiplication.
If you're interested in tackling this, the core loop analysis that needs to learn how floats work is "Scalar Evolution Analysis" in lib/Analysis/ScalarEvolution.cpp.
Seung Jae Lee wrote: