Scalability Issues in FFT Computation

Alan Ayala; Stanimire Tomov; Miroslav Stoyanov; Jack Dongarra

doi:10.1007/978-3-030-86359-3_21

Scalability Issues in FFT Computation

Alan Ayala, Stanimire Tomov, Miroslav Stoyanov, Jack Dongarra

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

12 Scopus citations

Abstract

The fast Fourier transform (FFT), is one the most important tools in mathematics, and it is widely required by several applications of science and engineering. State-of-the-art parallel implementations of the FFT algorithm, based on Cooley-Tukey developments, are known to be communication-bound, which causes critical issues when scaling the computational and architectural capabilities. In this paper, we study the main performance bottleneck of FFT computations on hybrid CPU and GPU systems at large-scale. We provide numerical simulations and potential acceleration techniques that can be easily integrated into FFT distributed libraries. We present different experiments on performance scalability and runtime analysis on the world’s most powerful supercomputers today: Summit, using up to 6,144 NVIDIA V100 GPUs, and Fugaku, using more than one million Fujitsu A64FX cores.

Original language	English
Title of host publication	Parallel Computing Technologies - 16th International Conference, PaCT 2021, Proceedings
Editors	Victor Malyshkin
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	279-287
Number of pages	9
ISBN (Print)	9783030863586
DOIs	https://doi.org/10.1007/978-3-030-86359-3_21
State	Published - 2021
Event	16th International Conference on Parallel Computing Technologies, PaCT 2021 - Kaliningrad, Russian Federation Duration: Sep 13 2021 → Sep 18 2021

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	12942 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	16th International Conference on Parallel Computing Technologies, PaCT 2021
Country/Territory	Russian Federation
City	Kaliningrad
Period	09/13/21 → 09/18/21

Funding

This research was supported by the Exascale Computing Project (ECP), Project Number: 17-SC-20-SC, a collaborative effort of two DOE organizations (the Office of Science and the National Nuclear Security Administration) responsible for the planning and preparation of a capable exascale ecosystem.

Keywords

Hybrid systems
Parallel FFT
Scalability

Access to Document

10.1007/978-3-030-86359-3_21

Cite this

Ayala, A., Tomov, S., Stoyanov, M., & Dongarra, J. (2021). Scalability Issues in FFT Computation. In V. Malyshkin (Ed.), Parallel Computing Technologies - 16th International Conference, PaCT 2021, Proceedings (pp. 279-287). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12942 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-86359-3_21

Ayala, Alan ; Tomov, Stanimire ; Stoyanov, Miroslav et al. / Scalability Issues in FFT Computation. Parallel Computing Technologies - 16th International Conference, PaCT 2021, Proceedings. editor / Victor Malyshkin. Springer Science and Business Media Deutschland GmbH, 2021. pp. 279-287 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "The fast Fourier transform (FFT), is one the most important tools in mathematics, and it is widely required by several applications of science and engineering. State-of-the-art parallel implementations of the FFT algorithm, based on Cooley-Tukey developments, are known to be communication-bound, which causes critical issues when scaling the computational and architectural capabilities. In this paper, we study the main performance bottleneck of FFT computations on hybrid CPU and GPU systems at large-scale. We provide numerical simulations and potential acceleration techniques that can be easily integrated into FFT distributed libraries. We present different experiments on performance scalability and runtime analysis on the world{\textquoteright}s most powerful supercomputers today: Summit, using up to 6,144 NVIDIA V100 GPUs, and Fugaku, using more than one million Fujitsu A64FX cores.",

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Ayala, A, Tomov, S, Stoyanov, M & Dongarra, J 2021, Scalability Issues in FFT Computation. in V Malyshkin (ed.), Parallel Computing Technologies - 16th International Conference, PaCT 2021, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12942 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 279-287, 16th International Conference on Parallel Computing Technologies, PaCT 2021, Kaliningrad, Russian Federation, 09/13/21. https://doi.org/10.1007/978-3-030-86359-3_21

Scalability Issues in FFT Computation. / Ayala, Alan; Tomov, Stanimire; Stoyanov, Miroslav et al.
Parallel Computing Technologies - 16th International Conference, PaCT 2021, Proceedings. ed. / Victor Malyshkin. Springer Science and Business Media Deutschland GmbH, 2021. p. 279-287 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12942 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - Scalability Issues in FFT Computation

AU - Ayala, Alan

AU - Tomov, Stanimire

AU - Stoyanov, Miroslav

AU - Dongarra, Jack

PY - 2021

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N2 - The fast Fourier transform (FFT), is one the most important tools in mathematics, and it is widely required by several applications of science and engineering. State-of-the-art parallel implementations of the FFT algorithm, based on Cooley-Tukey developments, are known to be communication-bound, which causes critical issues when scaling the computational and architectural capabilities. In this paper, we study the main performance bottleneck of FFT computations on hybrid CPU and GPU systems at large-scale. We provide numerical simulations and potential acceleration techniques that can be easily integrated into FFT distributed libraries. We present different experiments on performance scalability and runtime analysis on the world’s most powerful supercomputers today: Summit, using up to 6,144 NVIDIA V100 GPUs, and Fugaku, using more than one million Fujitsu A64FX cores.

AB - The fast Fourier transform (FFT), is one the most important tools in mathematics, and it is widely required by several applications of science and engineering. State-of-the-art parallel implementations of the FFT algorithm, based on Cooley-Tukey developments, are known to be communication-bound, which causes critical issues when scaling the computational and architectural capabilities. In this paper, we study the main performance bottleneck of FFT computations on hybrid CPU and GPU systems at large-scale. We provide numerical simulations and potential acceleration techniques that can be easily integrated into FFT distributed libraries. We present different experiments on performance scalability and runtime analysis on the world’s most powerful supercomputers today: Summit, using up to 6,144 NVIDIA V100 GPUs, and Fugaku, using more than one million Fujitsu A64FX cores.

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Ayala A, Tomov S, Stoyanov M, Dongarra J. Scalability Issues in FFT Computation. In Malyshkin V, editor, Parallel Computing Technologies - 16th International Conference, PaCT 2021, Proceedings. Springer Science and Business Media Deutschland GmbH. 2021. p. 279-287. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-86359-3_21

Scalability Issues in FFT Computation

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