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Publications of SPCL

M. Copik, T. Grosser, T. Hoefler, P. Bientinesi, B. Berkels:

 Work-Stealing Prefix Scan: Addressing Load Imbalance in Large-Scale Image Registration

(IEEE Transactions on Parallel and Distributed Systems. Vol 33, Nr. 3, pages 523-535, IEEE, Mar. 2022)

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Abstract

Parallelism patterns (e.g., map or reduce) have proven to be effective tools for parallelizing high-performance applications. In this paper, we study the recursive registration of a series of electron microscopy images - a time consuming and imbalanced computation necessary for nano-scale microscopy analysis. We show that by translating the image registration into a specific instance of the prefix scan, we can convert this seemingly sequential problem into a parallel computation that scales to over thousand of cores. We analyze a variety of scan algorithms that behave similarly for common low-compute operators and propose a novel work-stealing procedure for a hierarchical prefix scan. Our evaluation shows that by identifying a suitable and well-optimized prefix scan algorithm, we reduce time-to-solution on a series of 4,096 images spanning ten seconds of microscopy acquisition from over 10 hours to less than 3 minutes (using 1024 Intel Haswell cores), enabling derivation of material properties at nanoscale for long microscopy image series.

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BibTeX

@article{,
  author={Marcin Copik and Tobias Grosser and Torsten Hoefler and Paolo Bientinesi and Benjamin Berkels},
  title={{Work-Stealing Prefix Scan: Addressing Load Imbalance in Large-Scale Image Registration}},
  journal={IEEE Transactions on Parallel and Distributed Systems},
  year={2022},
  month={03},
  pages={523-535},
  volume={33},
  number={3},
  publisher={IEEE},
  doi={10.1109/TPDS.2021.3095230},
}