By the same authors

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Author(s)

  • Richard O. Kirk
  • Gihan R. Mudalige
  • Istvan Z. Reguly
  • Steven A. Wright
  • Matt J. Martineau
  • Stephen A. Jarvis

Department/unit(s)

Publication details

Title of host publicationProceedings - 2017 IEEE International Conference on Cluster Computing, CLUSTER 2017
DatePublished - 26 Sep 2017
Pages834-841
Number of pages8
PublisherInstitute of Electrical and Electronics Engineers Inc.
Volume2017-September
Original languageEnglish
ISBN (Electronic)9781538623268

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.

Bibliographical note

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    Research areas

  • Kokkos, Mini-Apps, OPS, Performance Portability, RAJA

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