Many applications in Comparative Genomics lend
themselves to implementations that take advantage of
common high-performance features in modern microprocessors.
However, the common suggestion that a dataparallel,
multithreaded, or high-throughput implementation
is possible often ignores the complexity of actually
creating such software. In this paper, we present a dataparallel
algorithm for a classic comparative genomics
algorithm, the dot plot, along with a multiprocessor extension.
For large genomic comparisons, these new algorithms
achieve speedups of up to 14.4x over the sequential
version. This speedup introduces the opportunity of performing
full pairwise comparisons on entire genomes on a
much larger scale than previously possible. We also present
the experimental, model-driven approach used to develop
the algorithm that allowed us to carefully study and
evaluate implementation options and fully understand the
parameters effecting its performance.