Experiences with OpenCL in PyFR: 2014-Present
Article No.: 11, Page 1
Abstract
PyFR is an open source high-performance computing (HPC) framework for performing scale-resolving computational fluid dynamics simulations [1]. The algorithmic core of PyFR is the flux reconstruction (FR) approach of Huynh [2], which combines the geometric flexibility of finite volume schemes with the high-order accuracy and efficiency of spectral schemes. Primarily written in Python, PyFR aims to be performance portable across a range of hardware platforms. This is accomplished through the use of a bespoke domain specific language based around the Mako templating engine and a range of run-time code generation backends. Our approach enables PyFR to target platforms through OpenMP annotated C kernels, CUDA kernels, and OpenCL kernels [3].
In this talk I will discuss our experiences with OpenCL in PyFR. This will include the current role of the OpenCL backend within PyFR and our plans for the future apropos SYCL and Intel's OpenAPI initiative. The performance of the OpenCL backend will be compared and contrasted to that of the 'native' backends in PyFR. Furthermore, we will also highlight the limitations of OpenCL and related standards; specifically in the areas of MPI-awareness and the availability of performance primitives. Implementation quality on the part of hardware vendors will also be discussed.
References
[1]
F. D. Witherden, A. M. Farrington, and P. E. Vincent, PyFR: An Open Source Framework for Solving Advection-Diffusion Type Problems on Streaming Architectures Using the Flux Reconstruction Approach. Computer Physics Communications, 185(11), 2014, 3028--3040.
[2]
H. T. Huynh, A flux reconstruction approach to high-order schemes including discontinuous Galerkin methods. 18th AIAA Computational Fluid Dynamics Conference, 2011.
[3]
F. D. Witherden, B. C. Vermeire, and P. E. Vincent, Heterogeneous computing on mixed unstructured grids with PyFR. Computers & Fluids, 120, 2015, 173--186.
Index Terms
- Experiences with OpenCL in PyFR: 2014-Present
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Published In
April 2020
104 pages
ISBN:9781450375313
DOI:10.1145/3388333
Copyright © 2020 Owner/Author.
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.
In-Cooperation
- Khronos: Khronos Group
- Codeplay: Codeplay Software Ltd.
- Intel: Intel
- The University of Bristol: The University of Bristol
- Tech Univ of Munich: Technical University of Munich
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 27 April 2020
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- Refereed limited
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IWOCL '20
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IWOCL '20 Paper Acceptance Rate 21 of 30 submissions, 70%;
Overall Acceptance Rate 84 of 152 submissions, 55%
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