On Wed, Mar 11, 2026 at 10:58 AM matti picus via NumPy-Discussion < [email protected]> wrote:
> On Tue, Mar 10, 2026 at 1:28 PM Sebastian Berg > <[email protected]> wrote: > > > > Hi all, > > > > In the NumPy 2.4 cycle, there were some native float16 implementations > > merged with rather low precision leading to the following issue: > > https://github.com/numpy/numpy/issues/30821 > > > > That is, previously, it used float loops so ~0.5 ULP error, now is is > > 2+ULP for many algorithms, on _some_ hardware: > > https://github.com/numpy/numpy/pull/23351 > > > > There is always an argument around that users of float16 probably don't > > care about many ULP, but I guess they also have very few bits of > > precision to begin with? > > I don't have a huge opinion on it, but we are more and more in the > > position where it is unclear if sacrificing a bit of precision is the > > right thing or not... > > > > Similar questions actually arise for float32 math, is it OK to trade- > > off precision for performance (or to what degree, everything trades a > > bit)? > > We have had discussions around this before but it is still a difficult > > trade-off to make and there is no choice that makes everyone happy. [1] > > > > - Sebastian > > > > [1] We can work towards something like `np.opts(precision="low")` or > > so, but that doesn't change the question of defaults much... > > I do like the idea of having a precise/fast toggle. Until we can > develop one, I think we should prefer precise. So we should revert and > document somewhere that float16 (and the soon-to-be-incoming bfloat16) > are, in NumPy, container types, and that all the math for them is done > as float16. > You meant `float32` here. And yes, I agree. Having a few code paths use platform/CPU-dependent instructions like AVX512-xxx ones, and as a result having a small subset of the NumPy API have different accuracy/speed trade-offs seems not all that useful to almost all users. And makes it harder to build up a mental model of what NumPy is actually doing. Cheers, Ralf
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