Some useful optimisations for unstructured computational fluid dynamics codes on multicore and manycore architectures

Ioan Hadade, Feng Wang, Mauro Carnevale, Luca di Mare

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

This paper presents a number of optimisations for improving the performance of unstructured computational fluid dynamics codes on multicore and manycore architectures such as the Intel Sandy Bridge, Broadwell and Skylake CPUs and the Intel Xeon Phi Knights Corner and Knights Landing manycore processors. We discuss and demonstrate their implementation in two distinct classes of computational kernels: face-based loops represented by the computation of fluxes and cell-based loops representing updates to state vectors. We present the importance of making efficient use of the underlying vector units in both classes of computational kernels with special emphasis on the changes required for vectorising face-based loops and their intrinsic indirect and irregular access patterns. We demonstrate the advantage of different data layouts for cell-centred as well as face data structures and architectural specific optimisations for improving the performance of gather and scatter operations which are prevalent in unstructured mesh applications. The implementation of a software prefetching strategy based on auto-tuning is also shown along with an empirical evaluation on the importance of multithreading for in-order architectures such as Knights Corner. We explore the various memory modes available on the Intel Xeon Phi Knights Landing architecture and present an approach whereby both traditional DRAM as well as MCDRAM interfaces are exploited for maximum performance. We obtain significant full application speed-ups between 2.8 and 3X across the multicore CPUs in two-socket node configurations, 8.6X on the Intel Xeon Phi Knights Corner coprocessor and 5.6X on the Intel Xeon Phi Knights Landing processor in an unstructured finite volume CFD code representative in size and complexity to an industrial application. Program summary: Program Title: some_opt_for_unstructured_cfd Program Files doi: http://dx.doi.org/10.17632/zyh2zkf3jw.1 Licensing provisions: GNU General Public License 3 (GPL) Programming language: C/C++ Nature of problem: The solution of fluid flow problems in the vicinity of complex geometries mandates the utilisation of unstructured grids. However, this flexibility of unstructured mesh methods in dealing with complicated geometries comes at a cost of increased difficulty in extracting high performance out of modern processors. We provide implementations for a number of optimisations useful for improving the performance of unstructured CFD codes on modern multicore and manycore architectures. Solution method: grid renumbering via Reverse Cuthill–Mckee, code transformations necessary for enabling vectorisation, face colouring/reordering for removing dependencies at the face end-points when accumulating residuals, data layout transformations for reducing cache misses, hand-tuned gather and scatter primitives for in-register transpositions, software prefetching via auto-tuning and multithreading for exploiting SMT features of modern processors.

Original languageEnglish
Pages (from-to)305-323
Number of pages18
JournalComputer Physics Communications
Volume235
Early online date18 Jul 2018
DOIs
Publication statusPublished - 1 Feb 2019

Keywords

  • Code optimisation
  • Computational fluid dynamics
  • High performance computing
  • Parallel programming
  • Unstructured grids

ASJC Scopus subject areas

  • Hardware and Architecture
  • Physics and Astronomy(all)

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