The shuffle instructions are commonly used when encoding or decoding integer serialization formats or processing integer arrays. It can also be a fast intermediate operation for some bit-twiddling algorithms, which would require multiple sequential operations to achieve an equivalent distribution of bits for processing.
If you are not working on high-performance bit-twiddling algorithms then you will probably have limited use for shuffle intrinsics. For those applications, it can save a few clock cycles for each call relative to more naive methods.
Shuffles are what makes SIMD go. It's trivial to make simple repeated math ops done in parallel instead of 4 (SIMD vector width) times sequentially, but shuffling vectors cleverly is where you can get big performance wins.
Basic example, doing addition of 4 values in 2 ALU operations:
vec4 sum(vec4 v) // return v.x+v.y+v.z+v.w repeated 4 times
{
vec4 temp = v + v.yxzw;
return temp + temp.zwxy; // did I get this right?
}
If you think of processors as plumbing, shuffle operations are like pipes: they put the data in the right place for other operations. General shuffle operations let you do things like convert RGB data to RGBA data without trouble. Shuffling is a more flexible version of the more common pack, unpack, and bytewise shift operations.
