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Comparison of parallelisation approaches, languages, and compilers for unstructured mesh algorithms on GPUs

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Balogh, G. D., Reguly, Istvan Z. and Mudalige, Gihan R. (2017) Comparison of parallelisation approaches, languages, and compilers for unstructured mesh algorithms on GPUs. In: 8th IEEE International Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS17), Denver CO. US, 13 Nov 2017. Published in: Lecture Notes in Computer Science, 10724 (10724). pp. 22-43. ISBN 9783319729701. ISSN 0302-9743. doi:10.1007/978-3-319-72971-8_2

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Official URL: http://www.springer.com/gb/book/9783319729701

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Abstract

Efficiently exploiting GPUs is increasingly essential in scientific computing, as many current and upcoming supercomputers are built using them. To facilitate this, there are a number of programming approaches, such as CUDA, OpenACC and OpenMP 4, supporting different programming languages (mainly C/C++ and Fortran). There are also several compiler suites (clang, nvcc, PGI, XL) each supporting different combinations of languages. In this study, we take a detailed look at some of the currently available options, and carry out a comprehensive analysis and comparison using computational loops and applications from the domain of unstructured mesh computations. Beyond runtimes and performance metrics (GB/s), we explore factors that influence performance such as register counts, occupancy, usage of different memory types, instruction counts, and algorithmic differences. Results of this work show how clang’s CUDA compiler frequently outperform NVIDIA’s nvcc, performance issues with directive-based approaches on complex kernels, and OpenMP 4 support maturing in clang and XL; currently around 10% slower than CUDA.

Item Type: Conference Item (Paper)
Subjects: Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software
Divisions: Faculty of Science > Computer Science
Library of Congress Subject Headings (LCSH): Graphics processing units, Compilers (Computer programs), Algorithms
Series Name: Lecture Notes in Computer Science
Journal or Publication Title: Lecture Notes in Computer Science
Publisher: Springer
Place of Publication: Cham, Switzerland
ISBN: 9783319729701
ISSN: 0302-9743
Book Title: High Performance Computing Systems. Performance Modeling, Benchmarking, and Simulation. PMBS 2017
Editor: Jarvis, Stephen A. and Wright, S. and Hammond, S.
Official Date: 23 December 2017
Dates:
DateEvent
23 December 2017Published
9 October 2017Accepted
Volume: 10724
Number: 10724
Number of Pages: 261
Page Range: pp. 22-43
DOI: 10.1007/978-3-319-72971-8_2
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Restricted or Subscription Access
RIOXX Funder/Project Grant:
Project/Grant IDRIOXX Funder NameFunder ID
Janos Bolyai Research ScholarshipMagyar Tudományos Akadémiahttp://dx.doi.org/10.13039/501100003825
EFOP-3.6.2-16-2017-00013European Social Fundhttp://dx.doi.org/10.13039/501100004895
Conference Paper Type: Paper
Title of Event: 8th IEEE International Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS17)
Type of Event: Workshop
Location of Event: Denver CO. US
Date(s) of Event: 13 Nov 2017
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