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| Titel |
Towards Performance Portability with GungHo |
| VerfasserIn |
Rupert Ford, Matthew Glover, David Ham, Mike Hobson, Chris Maynard, Lawrence Mitchell, Steve Mullerworth, Stephen Pickles, Mike Rezny, Graham Riley, Nigel Wood, Mike Ashworth |
| Konferenz |
EGU General Assembly 2014
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 16 (2014) |
| Datensatznummer |
250097640
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| Publikation (Nr.) |
 EGU/EGU2014-13243.pdf |
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| Zusammenfassung |
| The Met Office's numerical weather prediction and climate model code,
the Unified Model (UM), is almost 25 years old. Up to the present day
the UM has been able to be run efficiently on many of the worlds most
powerful computers, helping to keep the Met Office at the forefront of
climate prediction and weather forecasting.
However, with performance increases from each new generation of
computers now being primarily provided by an increase in the amount of
parallelism rather than an increase in the clock-speed of the
processors themselves, running higher resolutions of the UM now faces
the double challenge of code scalability and numerical accuracy.
The UM's atmospheric dynamical core makes use of a finite-difference
scheme on a regular latitude-longitude grid. The regular
latitude-longitude mesh results in an increasingly disparate grid
resolution as the mesh resolution increases due to lines of longitude
converging at the poles. For example, a 10km resolution at
mid-latitudes would result in a 12m resolution at the poles. The
difference in resolution leads to increased communication at the poles
and load balance issues which are known to impair scalability; it also
leads to issues with numerical accuracy and smaller time-steps due to
the difference in scale.
To address this problem the Met Office, NERC and STFC initiated the
GungHo project. The primary aim of this project is to deliver a
scalable, numerically accurate dynamical core. This dynamical core is
scheduled to become operational around the year 2022. The project is
currently investigating the use of quasi-uniform meshes, such as
triangular, icosahedral and cubed-sphere meshes, using finite element
methods.
The associated GungHo software infrastructure is being developed to
support multiple meshes and element types thus allowing for future
model development. GungHo is also proposing a novel separation of
concerns for the software implementation of the dynamical core. This
approach distinguishes between three layers: the Algorithm layer, the
Kernel layer and the Parallelisation System (PSy) layer. Together this
separation is termed PSyKAl.
The Algorithm layer specifies the algorithm that the scientist would
like to run (in terms of calls to kernel and infrastructure routines)
and logically operates on full fields.
The Kernel layer provides the implementation of the code kernels as
subroutines. These subroutines operate on local fields (a set of
elements, a vertical column, or a set of vertical columns, depending
on the kernel).
The PSy layer sits in-between the algorithm and kernel layers and its
primary role is to provide node-based parallel performance for the target
architecture. The PSy layer can be optimised for a particular hardware
architecture, such as multi-core, many-core, GPGPUs, or some
combination thereof with no change to the algorithm or kernel layer
code. This approach therefore offers the potential for portable
performance.
Rather than writing the PSy layer manually, the GungHo project is
proposing to develop a code generation system which can help a user to
optimise the code for a particular architecture (by providing
optimisations such as blocking, loop merging, inlining etc), or
alternatively, generate the PSy layer automatically.
whilst the PSyKAl approach has been developed for GungHo, it is
expected to be more generally applicable. In this talk we will
describe the PSyKAl approach, the code generation system and present
some early examples of their use. |
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