3 ms·

I think this article is from 2010.

• jacquesm 8y ago
  That's not relevant there are plenty of single precision float applications today (and many fixed point applications as well). It all depends on your workload.
• duckerude 8y ago
  I wanted to put over a billion floats in a numpy array just a few months ago. Making them 16-bit saved a lot of memory. It doesn't matter how much resource limits increase, people are going to keep hitting them. And when they hit them, using a smaller data type will always help.