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FFT, FMM, and multigrid on the road to exascale: Performance challenges and opportunities

Journal Article · · Journal of Parallel and Distributed Computing
 [1];  [2];  [2]
  1. Univ. of Illinois at Urbana-Champaign, IL (United States); OSTI
  2. Univ. of Illinois at Urbana-Champaign, IL (United States)
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FFT, FMM, and multigrid methods are widely used fast and highly scalable solvers for elliptic PDEs. However, emerging large-scale computing systems are introducing challenges in comparison to current petascale computers. Recent efforts (Dongarra et al. 2011) have identified several constraints in the design of exascale software that include massive concurrency, resilience management, exploiting the high performance of heterogeneous systems, energy efficiency, and utilizing the deeper and more complex memory hierarchy expected at exascale. In this paper, we perform a model-based comparison of the FFT, FMM, and multigrid methods in the context of these projected constraints. Finally, we use performance models to offer predictions about the expected performance on upcoming exascale system configurations based on current technology trends.
Research Organization:
Univ. of Illinois at Urbana-Champaign, IL (United States)
Sponsoring Organization:
USDOE Advanced Research Projects Agency - Energy (ARPA-E); USDOE National Nuclear Security Administration (NNSA)
Grant/Contract Number:
NA0002374
OSTI ID:
1801076
Alternate ID(s):
OSTI ID: 1573268
Journal Information:
Journal of Parallel and Distributed Computing, Journal Name: Journal of Parallel and Distributed Computing Journal Issue: C Vol. 136; ISSN 0743-7315
Publisher:
ElsevierCopyright Statement
Country of Publication:
United States
Language:
English

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Related Subjects

97 MATHEMATICS AND COMPUTING
Fast Fourier transform
computer science
exascale
fast multipole method
multigrid
performance modeling