Abstract
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. In addition we use performance models to offer predictions about the expected performance on upcoming exascale system configurations based on current technology trends.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 63-74 |
| Number of pages | 12 |
| Journal | Journal of Parallel and Distributed Computing |
| Volume | 136 |
| DOIs | |
| State | Published - Feb 2020 |
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Keywords
- Exascale
- Fast Fourier transform
- Fast multipole method
- Multigrid
- Performance modeling
ASJC Scopus subject areas
- Software
- Theoretical Computer Science
- Hardware and Architecture
- Computer Networks and Communications
- Artificial Intelligence
Cite this
FFT, FMM, and multigrid on the road to exascale : Performance challenges and opportunities. / Ibeid, Huda; Olson, Luke; Gropp, William.
In: Journal of Parallel and Distributed Computing, Vol. 136, 02.2020, p. 63-74.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - FFT, FMM, and multigrid on the road to exascale
T2 - Performance challenges and opportunities
AU - Ibeid, Huda
AU - Olson, Luke
AU - Gropp, William
PY - 2020/2
Y1 - 2020/2
N2 - 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. In addition we use performance models to offer predictions about the expected performance on upcoming exascale system configurations based on current technology trends.
AB - 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. In addition we use performance models to offer predictions about the expected performance on upcoming exascale system configurations based on current technology trends.
KW - Exascale
KW - Fast Fourier transform
KW - Fast multipole method
KW - Multigrid
KW - Performance modeling
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UR - http://www.scopus.com/inward/citedby.url?scp=85074439422&partnerID=8YFLogxK
U2 - 10.1016/j.jpdc.2019.09.014
DO - 10.1016/j.jpdc.2019.09.014
M3 - Article
AN - SCOPUS:85074439422
VL - 136
SP - 63
EP - 74
JO - Journal of Parallel and Distributed Computing
JF - Journal of Parallel and Distributed Computing
SN - 0743-7315
ER -