Never considered fast-math. I get the sense its useful but can create awkward and/or unexpected surprises. If I was to use it I'd have to have a verification test harness as part of some pipeline to comfirm no weirdness. Literally a bunch of example canary calculations to determine if fast-math will kill or harm some real use case.
Is this a sensible approach? What are others experiences around this? I've never bothered with this kind of optimisation and I now vaguely feel like I'm missing out.
I tend to use calculations for deterministic purposes rather than pure accuracy. 1+1=2.1 where the answer is stable and approximate is still better and more useful than 1+1=2.0 but where the answer is unstable. Eg because one of those is 0.9999999 and the precision triggers some edge case.
Is this a sensible approach? What are others experiences around this? I've never bothered with this kind of optimisation and I now vaguely feel like I'm missing out.
I tend to use calculations for deterministic purposes rather than pure accuracy. 1+1=2.1 where the answer is stable and approximate is still better and more useful than 1+1=2.0 but where the answer is unstable. Eg because one of those is 0.9999999 and the precision triggers some edge case.