  Evolution can be broadly described in terms of mutations of the genotype and
the subsequent selection of the phenotype. The full enumeration of a given
genotype-phenotype (GP) map is therefore a powerful technique in examining
evolutionary landscapes. However, because the number of genotypes typically
grows exponentially with genome length, such calculations rapidly become
intractable. Here I apply graphics processing unit(GPU) techniques to the
hydrophobic-polar (HP)model for protein folding. This GP map is a simple and
well-studied model for the complex process of protein folding. Prior studies on
relatively small 2D and 3D lattices have been exclusively carried out using
conventional central processing unit (CPU) approaches. By using GPU techniques,
I was able to reproduce the pioneering calculations of Li et al.[1] with a
speed up of 580-700 fold over a CPU. I was also able to perform the largest
enumeration to date of the 6x6 lattice. These novel calculations provide
evidence that a popular "plum-pudding" metaphor that suggests that phenotypes
are disconnected in genotype space does not describe the data. Instead a
"spaghetti" metaphor of connected genotype networks may be more suitable.
Furthermore, the data allows the relationships between designability and
complexity within GP space to be explored. GPU approaches appear extremely well
suited toGP mapping and the success of this work provides a promising
introduction for its wider application in this field.
