Genomics is transforming medicine and our understanding of life in fundamental ways. Genomics data, however, is far outpacing Moore»s Law. Third-generation sequencing technologies produce 100X longer reads than second generation technologies and reveal a much broader mutation spectrum of disease and evolution. However, these technologies incur prohibitively high computational costs. Over 1,300 CPU hours are required for reference-guided assembly of the human genome, and over 15,600 CPU hours are required for de novo assembly. This paper describes "Darwin" --- a co-processor for genomic sequence alignment that, without sacrificing sensitivity, provides up to $15,000X speedup over the state-of-the-art software for reference-guided assembly of third-generation reads. Darwin achieves this speedup through hardware/algorithm co-design, trading more easily accelerated alignment for less memory-intensive filtering, and by optimizing the memory system for filtering. Darwin combines a hardware-accelerated version of D-SOFT, a novel filtering algorithm, alignment at high speed, and with a hardware-accelerated version of GACT, a novel alignment algorithm. GACT generates near-optimal alignments of arbitrarily long genomic sequences using constant memory for the compute-intensive step. Darwin is adaptable, with tunable speed and sensitivity to match emerging sequencing technologies and to meet the requirements of genomic applications beyond read assembly.

@inproceedings{paperbot4231,
  title = {Darwin},
  author = {Yatish Turakhia and Gill Bejerano and William J. Dally},
  booktitle = {ASPLOS},
  year = {2018},
  doi = {10.1145/3173162.3173193}
}