Subnormal numbers have a different, basically fixed-point, representation. They exist in order to bridge the large (relatively speaking; indeed "infinite" in a sense) gap between the least positive normal number, zero, and the greatest negative normal number, caused by the usual significand-exponent representation.
Most "mundane" uses of floating point have no need for subnormal numbers, and results that underflow could just be flushed to zero. But they’re sometimes important in scientific computing to ensure sufficient smoothness around zero, avoiding precision issues.
Most "mundane" uses of floating point have no need for subnormal numbers, and results that underflow could just be flushed to zero. But they’re sometimes important in scientific computing to ensure sufficient smoothness around zero, avoiding precision issues.