This shouldn't need to be said, but don't use -ffast-math if you want reproducibility. Unfortunately, the times when you most want reproducibility tend to be the same sorts of number-crunching where -ffast-math would be most useful.
> Unfortunately, the times when you most want reproducibility tend to be the same sorts of number-crunching where -ffast-math would be most useful.
Thanks for the clarification. The obvious caveats of -ffast-math are well documented and most applications shouldn't use that flag.
There are exceptions to this however, I tend to work on such problems. For example, game physics, 3d graphics and some scientific algorithms that have built-in numerical inaccuracy (so -ffast-math doesn't help but doesn't hurt either) but high perf requirements. I also tend to have extensive testing for the most crucial parts of my programs that should catch any problems with this (but many people don't do this with game physics, etc code).
Thankfully, -ffast-math is easy to disable if you start suspecting problems that are caused by that flag.
I'd diagree, Game physics and scientific algorithms are often precisely where you want reproducible results.
Game physics because of lockstep networking and replays, scientific algorithms because... well, you want your results to be reproducible. Scientific method and all that.
Often times you don't mind if it isn't accurate, but that isn't the same thing as precision. You want it to be precise, i.e. reproducible.
