So why use denormalized numbers at all? It costs time to normalize the denormalized result of an operation; if you know the loss of precision is not significant to your computation, you may not want to pay the price, especially in an inner loop of a vector or matrix operation. Also, you can get a few extra bits of exponent (read: dynamic range of the value) in trade for the loss of mantissa precision.
The primary reason for denormalized numbers is to provide gradual underflow. Denormalized numbers allow for some additional values between zero and the smallest normalized number greater than zero.
Rick Zaccone