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DTSTART:19700308T020000
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DTSTAMP:20210402T160052Z
LOCATION:Track 2
DTSTART;TZID=America/New_York:20201117T153000
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UID:submissions.supercomputing.org_SC20_sess147_pap310@linklings.com
SUMMARY:Multi-Node Multi-GPU Diffeomorphic Image Registration for Large-Sc
 ale Imaging Problems
DESCRIPTION:Paper\n\nMulti-Node Multi-GPU Diffeomorphic Image Registration
  for Large-Scale Imaging Problems\n\nBrunn, Himthani, Biros, Mehl, Mang\n\
 nWe present a  Gauss-Newton-Krylov solver for large deformation diffeomorp
 hic image registration. We extend the publicly available CLAIRE library to
  multi-node multi-graphics processing unit (GPU) systems and introduce nov
 el algorithmic modifications that significantly improve  performance.  Our
  contributions comprise; (i) a new preconditioner for the reduced-space Ga
 uss-Newton Hessian system,  (ii) a highly-optimized multi-node multi-GPU i
 mplementation exploiting device direct communication for the main computat
 ional kernels (interpolation, high-order finite difference operators and F
 ast-Fourier-Transform), and (iii) a comparison with state-of-the-art CPU a
 nd GPU implementations. We solve a  256^3-resolution image registration pr
 oblem in five seconds on a single NVIDIA Tesla V100, with a performance sp
 eedup of 70% compared to the state-of-the-art. In our largest run, we regi
 ster 2048^3 resolution images (25b unknowns; approximately 152x larger tha
 n the largest problem solved in state-of-the-art GPU implementations) on 6
 4 nodes with 256 GPUs on TACC's Longhorn system.\n\nTag: Accelerators, FPG
 A, and GPUs, Algorithms, Applications, Scalable Computing\n\nRegistration 
 Category: Tech Program Reg Pass
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