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UID:submissions.supercomputing.org_SC20_sess147_pap597@linklings.com
SUMMARY:SegAlign: A Scalable GPU-Based Whole Genome Aligner
DESCRIPTION:Paper\n\nSegAlign: A Scalable GPU-Based Whole Genome Aligner\n
 \nGoenka, Turakhia, Paten, Horowitz\n\nPairwise Whole Genome Alignment (WG
 A) is a crucial first step to understanding evolution at the DNA-sequence 
 level. Pairwise WGA of thousands of currently available species genomes co
 uld help make biological discoveries; computing them, however, for even a 
 fraction of the millions of possible pairs is prohibitive; WGA of a single
  pair of vertebrate genomes (human-mouse) takes 11 hours on a 96-core Amaz
 on Web Services (AWS) instance (c5.24xlarge).\n\nThis paper presents SegAl
 ign; a scalable, GPU-accelerated system for computing pairwise WGA. SegAli
 gn is based on the standard seed-filter-extend heuristic, in which the fil
 tering stage dominates the runtime (e.g., 98% for human-mouse WGA), and is
  accelerated using GPU(s). Using three vertebrate genome pairs, we show th
 at SegAlign provides a speedup of up to 14x on an 8-GPU, 64-core AWS insta
 nce (p3.16xlarge) for WGA and a nearly 2.3x reduction in dollar cost. SegA
 lign also allows parallelization over multiple GPU nodes and scales effici
 ently.\n\nTag: Accelerators, FPGA, and GPUs, Algorithms, Applications, Sca
 lable Computing\n\nRegistration Category: Tech Program Reg Pass
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