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Achieving performance portability for a heat conduction solver mini-application on modern multi-core systems

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Kirk, Richard, Mudalige, Gihan R., Reguly, Istvan Z., Wright, Steven A., Martineau, Matt and Jarvis, Stephen A. (2017) Achieving performance portability for a heat conduction solver mini-application on modern multi-core systems. In: Second International Workshop on Representative Applications (WRAp 2017), Honolulu, Hawaii, USA, 05-08 Sep 2017. Published in: 2017 IEEE International Conference on Cluster Computing (CLUSTER) ISSN 2168-9253. doi:10.1109/CLUSTER.2017.122

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Official URL: https://doi.org/10.1109/CLUSTER.2017.122

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Abstract

Modernizing production-grade, often legacy applications to take advantage of modern multi-core and many-core architectures can be a difficult and costly undertaking. This is especially true currently, as it is unclear which architectures will dominate future systems. The complexity of these codes can mean that parallelisation for a given architecture requires significant re-engineering. One way to assess the benefit of such an exercise would be to use mini-applications that are representative of the legacy programs.

In this paper, we investigate different implementations of TeaLeaf, a mini-application from the Mantevo suite that solves the linear heat conduction equation. TeaLeaf has been ported to use many parallel programming models, including OpenMP, CUDA and MPI among others. It has also been re-engineered to use the OPS embedded DSL and template libraries Kokkos and RAJA. We use these different implementations to assess the performance portability of each technique on modern multi-core systems.

While manually parallelising the application targeting and optimizing for each platform gives the best performance, this has the obvious disadvantage that it requires the creation of different versions for each and every platform of interest. Frameworks such as OPS, Kokkos and RAJA can produce executables of the program automatically that achieve comparable portability.

Based on a recently developed performance portability metric, our results show that OPS and RAJA achieve an application performance portability score of 71% and 77% respectively for this application.

Item Type: Conference Item (Paper)
Subjects: Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software
Q Science > QC Physics
T Technology > T Technology (General)
T Technology > TA Engineering (General). Civil engineering (General)
Divisions: Faculty of Science > Computer Science
Library of Congress Subject Headings (LCSH): Graphics processing units , Parallel programming (Computer science) , C++ (Computer program language), Computer architecture, Heat--Conduction, Heat--Conduction--Computer programs
Journal or Publication Title: 2017 IEEE International Conference on Cluster Computing (CLUSTER)
Publisher: IEEE Computer Society
ISSN: 2168-9253
Official Date: 26 September 2017
Dates:
DateEvent
26 September 2017Published
29 July 2017Accepted
DOI: 10.1109/CLUSTER.2017.122
Status: Not Peer Reviewed
Publication Status: Published
Access rights to Published version: Restricted or Subscription Access
Funder: Atomic Weapons Establishment (Great Britain) (AWE), Engineering and Physical Sciences Research Council (EPSRC), Magyar Tudományos Akadémia‏ [Hungarian Academy of Sciences], Hungary. Foglalkoztatáspolitikai és Munkaügyi Minisztérium [Hungary. Ministry of Employment and Labour] (HRDOP)
Grant number: CDK0724 (AWE), EP/K038494/1 (EPSR), EP/K038486/1 (EPSR), EP/K038451/1 (EPSR), EP/K038567/1 (EPSR), EFOP-3.6.2-16-2017-00013 (HRDOP)
Conference Paper Type: Paper
Title of Event: Second International Workshop on Representative Applications (WRAp 2017)
Type of Event: Workshop
Location of Event: Honolulu, Hawaii, USA
Date(s) of Event: 05-08 Sep 2017
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