  A physically-motivated genetic algorithm (GA) and full enumeration for a
tile-based model of self-assembly (JaTAM) is implemented using a graphics
processing unit (GPU). We observe performance gains with respect to
state-of-the-art implementations on CPU of factor 7.7 for the GA and 2.9 for
JaTAM. The correctness of our GA implementation is demonstrated using a
test-bed fitness function, and our JaTAM implementation is verified by
classifying a well-known search space $S_{2,8}$ based on two tile types. The
performance gains achieved allow for the classification of a larger search
space $S^{32}_{3,8}$ based on three tile types. The prevalence of structures
based on two tile types demonstrates that simple organisms emerge preferrably
even in complex ecosystems. The modularity of the largest structures found
motivates the assumption that to first order, $S_{2,8}$ forms the building
blocks of $S_{3,8}$. We conclude that GPUs may play an important role in future
studies of evolutionary dynamics.
