Single Precision: Friend or Foe

The recent developments of so called disruptive technologies always lead to some kind of everlasting discussion.
Today I want to say something about the hassle whether GPUs are feasible in any way for scientific computing as their double precision Performance is nowadays not too far away from standard CPUs. And single precision is not worth the discussion, as nobody wants to board a plane or a ship which was simulated just in single precision.

Detour
So for non-simulators first some explanation: single precision means a floating point representation of a given number using up to 4 bytes. Double precision uses up to 8 bytes and can therefore provide much more accuracy.

GPUs are originally designed for graphics applications that do not actually need single precision. There is a bunch of very fast FLOP commands just working on 24 bits instead of 32 bits (again 32 bits = 4 byte = single precision).
E.g. current NVIDIA cards just have 1 dp FLOP unit per 8 sp FLOP unit.

Till now its obvious why everyone complains about the worse dp performance in contrast to sp performance. However, nobody (well I do) complains about the low dp performance I actually get off a current x86 processor. There are some kinds of system configuration were you will just get about 10% or even less the performance.

This comes as data is brought much slower to the computing units than it is computed on there.
This is true for most scientific codes, e.g. stencil codes. Therefore you will see the usual breakdown to 50% of performance when switching from sp to dp on GPUs as you see on CPUs, because you simply transfer twice the data over the same system bus.
So, the dp units are most often not the limit of compute performance.