It is normal to get values close to zero in a correctly implemented floating point algorithm - what matters is that, at that point, you don't rely on their dyna

It is normal to get values close to zero in a correctly implemented floating point algorithm - what matters is that, at that point, you don't rely on their dynamic range or precision. Trap-on-underflow would produce many false positives for algorithms which would be perfectly happy having those numbers be treated as zero. This is not uncommon - it is completely expected with, say, anything implementing an exponential decay! A slow exponential decay could run into subnormals for large spans of time, yet be fine having those treated as zero.