Software suites for ship simulations are typically used for statistical studies of ship dynamics, but also as a simulator for training ship crew in dangerous situations. One problem that arises during training is speeding-up a part of the session which does not involve actions from the crew. The aim of the study reported here is to accelerate solution of ship motion equations using general purpose computations on GPU. These equations describe dynamics of ship manoeuvring in wavy sea surface, and are central to the simulator programme. The equations are solved numerically via Runge-Kutta-Fehlberg method. Due to high number of floating point operations, computation on GPU achieves considerable speed-up over CPU. High performance solution allows to shorten training sessions and make them more efficient, but also beneficial for statistical studies as it reduces simulation time.

Original languageEnglish
Title of host publicationSelected Papers of the 8th International Conference ""Distributed Computing and Grid-Technologies in Science and Education"", GRID 2018
Pages410-414
Number of pages5
StatePublished - 2018
Event8th International Conference "Distributed Computing and Grid-Technologies in Science and Education", GRID 2018 - Dubna, Russian Federation
Duration: 10 Sep 201814 Sep 2018

Publication series

NameCEUR Workshop Proceedings
PublisherRWTH Aahen University
Volume2267
ISSN (Print)1613-0073

Conference

Conference8th International Conference "Distributed Computing and Grid-Technologies in Science and Education", GRID 2018
Country/TerritoryRussian Federation
CityDubna
Period10/09/1814/09/18

    Scopus subject areas

  • Computer Science(all)

    Research areas

  • GPGPU, Maritime simulator, Ocean waves, OpenCL, Ship Dynamics, Virtual testbed

ID: 36504092