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PinTing oscillatory problems with a massively parallel rational approximation Schreiber, Martin
Description
The stagnated increase in CPU frequency and the resulting trend in HPC towards massively parallel systems poses new challenges for HPC applications. The ongoing trend towards massive parallelism (accelerator cards and many-core systems) requires redesigning existing algorithms to cope with these architectures. In this presentation we will focus on oscillatory problems. Solving them with a regular time stepping method leads to a timestep-by-step sequentialization in the time dimension. In combination with the CFL limitation, an increasing resolutions also results in an increase in the number of these sequential time steps. For problems which are already limited in their scalability this directly leads to an increase in wall clock time which can make the results less valuable or even useless. Based on underlying properties of oscillatory problems we make use of a recently developed method of a "rational approximation of exponential integrator" (REXI). This method uses features of linear oscillatory problems which allows a massively parallel formulation. This yields several beneficial advantages: e.g. an increase in resolution does not lead to an increase in the number of time steps as it is the case with conventional time stepping methods. In contrast, it leads to an increase in the degree of parallelization. Our results show speedups of over 2 orders of magnitude compared to a standard time stepping method and a scalability model indicates robust scalability beyond 100k cores in case of large time step sizes. Finally, an extension to a semi-Lagrangian time stepping scheme to cope with non-linearities will be discussed.
Item Metadata
Title |
PinTing oscillatory problems with a massively parallel rational approximation
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Creator | |
Publisher |
Banff International Research Station for Mathematical Innovation and Discovery
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Date Issued |
2016-11-29T09:11
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Description |
The stagnated increase in CPU frequency and the resulting trend in HPC
towards massively parallel systems poses new challenges for HPC
applications. The ongoing trend towards massive parallelism
(accelerator cards and many-core systems) requires redesigning
existing algorithms to cope with these architectures. In this
presentation we will focus on oscillatory problems. Solving them with
a regular time stepping method leads to a timestep-by-step
sequentialization in the time dimension. In combination with the CFL
limitation, an increasing resolutions also results in an increase in
the number of these sequential time steps. For problems which are
already limited in their scalability this directly leads to an
increase in wall clock time which can make the results less valuable
or even useless. Based on underlying properties of oscillatory
problems we make use of a recently developed method of a "rational
approximation of exponential integrator" (REXI). This method uses
features of linear oscillatory problems which allows a massively
parallel formulation. This yields several beneficial advantages:
e.g. an increase in resolution does not lead to an increase in the
number of time steps as it is the case with conventional time stepping
methods. In contrast, it leads to an increase in the degree of
parallelization. Our results show speedups of over 2 orders of
magnitude compared to a standard time stepping method and a
scalability model indicates robust scalability beyond 100k cores in
case of large time step sizes. Finally, an extension to a
semi-Lagrangian time stepping scheme to cope with non-linearities will
be discussed.
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Extent |
28 minutes
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Subject | |
Type | |
File Format |
video/mp4
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Language |
eng
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Notes |
Author affiliation: University of Exeter
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Series | |
Date Available |
2017-05-15
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Provider |
Vancouver : University of British Columbia Library
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Rights |
Attribution-NonCommercial-NoDerivatives 4.0 International
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DOI |
10.14288/1.0347481
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URI | |
Affiliation | |
Peer Review Status |
Unreviewed
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Scholarly Level |
Postdoctoral
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Rights URI | |
Aggregated Source Repository |
DSpace
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Item Citations and Data
Rights
Attribution-NonCommercial-NoDerivatives 4.0 International