Yatish Turakhia and Gill Bejerano, Stanford University; William J. Dally, Stanford University and NVIDIA Research
Best Paper at ASPLOS '18: Link to Paper (external site)
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.
title = {Darwin: A Genomics Co-processor Provides up to 15,000X Acceleration on Long Read Assembly},
booktitle = {2019 USENIX Annual Technical Conference (USENIX ATC 19)},
year = {2019},
address = {Renton, WA},
url = {https://www.usenix.org/conference/atc19/presentation/turakhia},
publisher = {USENIX Association},
month = jul
}