Hi.
I also know FMA rounding errors about GPU & CPU.
when cuda capability < 2.0, I implemented scratch CNN on python(with numpy) and  perfectly equal with pytorch output.
when cuda capability >=  2.0, I tried to met the output using fma library in gcc, using ieee-754-2008 library, but I can’t.
precision between  output of convolution in pytorch and (c-modeling, numpy) are different.
for example, max distance is 0.0000167 (pytorch vs c-model and numpy)
So, I want to disable FMA features, because it is critical issue to me.
I have an question,
When calculate convolution in pytorch -> cuda,
can you tell me correct data type?

fma((double)X *(double)Y + (double)B)
fma((float)X *(float)Y + (float)B)

Thanks.