Abstract: Described herein, Smith-Waterman using Associative Massive Parallelism (SWAMP) extends the single, highest scoring subsequence alignment the traditional Smith-Waterman algorithm and variations return to discover the top k highest scoring non-overlapping, non-intersecting subalignments in parallel. Embodiments provided herein provide synergistic work, accelerating the high quality of alignments, in addition to providing multiple subsequence discovery that is handled in an automated fashion within the algorithm. SWAMP and SWAMP+ (and related algorithms such as are described herein) are parallel algorithms that are designed to run in an accelerated manner, inter alia, on single-instruction, multiple-data (SIMD) machines. Not only is the alignment/matching process accelerated for the single, highest matching alignment, in embodiments the algorithm can analyze deeper into the sequences for additional high-quality alignments.