  Genome sequences contain hundreds of millions of DNA base pairs. Finding the
degree of similarity between two genomes requires executing a compute-intensive
dynamic programming algorithm, such as Smith-Waterman. Traditional von Neumann
architectures have limited parallelism and cannot provide an efficient solution
for large-scale genomic data. Approximate heuristic methods (e.g. BLAST) are
commonly used. However, they are suboptimal and still compute-intensive. In
this work, we present BioSEAL, a Biological SEquence ALignment accelerator.
BioSEAL is a massively parallel non-von Neumann processing-in-memory
architecture for large-scale DNA and protein sequence alignment. BioSEAL is
based on resistive content addressable memory, capable of energy-efficient and
high-performance associative processing. We present an associative processing
algorithm for entire database sequence alignment on BioSEAL and compare its
performance and power consumption with state-of-art solutions. We show that
BioSEAL can achieve up to 57x speedup and 156x better energy efficiency,
compared with existing solutions for genome sequence alignment and protein
sequence database search.
