TY - GEN

T1 - Virtual Testbed: Ship Motion Simulation for Personal Workstations

AU - Degtyarev, Alexander

AU - Khramushin, Vasily

AU - Gankevich, Ivan

AU - Petriakov, Ivan

AU - Gavrikov, Anton

AU - Grigorev, Artemii

N1 - Conference code: 19

PY - 2019/6/29

Y1 - 2019/6/29

N2 - Virtual testbed is a computer programme that simulates ocean waves, ship motions and compartment flooding. One feature of this programme is that it visualises physical phenomena frame by frame as the simulation progresses. The aim of the studies reported here was to assess how much performance can be gained using graphical accelerators compared to ordinary processors when repeating the same computations in a loop. We rewrote programme’s hot spots in OpenCL to able to execute them on a graphical accelerator and benchmarked their performance with a number of real-world ship models. The analysis of the results showed that data copying in and out of accelerator’s main memory has major impact on performance when done in a loop, and the best performance is achieved when copying in and out is done outside the loop (when data copying inside the loop involves accelerator’s main memory only). This result comes in line with how distributed computations are performed on a set of cluster nodes, and suggests using similar approaches for single heterogeneous node with a graphical accelerator.

AB - Virtual testbed is a computer programme that simulates ocean waves, ship motions and compartment flooding. One feature of this programme is that it visualises physical phenomena frame by frame as the simulation progresses. The aim of the studies reported here was to assess how much performance can be gained using graphical accelerators compared to ordinary processors when repeating the same computations in a loop. We rewrote programme’s hot spots in OpenCL to able to execute them on a graphical accelerator and benchmarked their performance with a number of real-world ship models. The analysis of the results showed that data copying in and out of accelerator’s main memory has major impact on performance when done in a loop, and the best performance is achieved when copying in and out is done outside the loop (when data copying inside the loop involves accelerator’s main memory only). This result comes in line with how distributed computations are performed on a set of cluster nodes, and suggests using similar approaches for single heterogeneous node with a graphical accelerator.

KW - GPGPU

KW - OpenCL

KW - Pressure field

KW - Pressure force

KW - Ship

KW - Wavy surface

KW - Wetted surface

UR - http://www.scopus.com/inward/record.url?scp=85068622160&partnerID=8YFLogxK

UR - http://www.mendeley.com/research/virtual-testbed-ship-motion-simulation-personal-workstations

U2 - 10.1007/978-3-030-24305-0_53

DO - 10.1007/978-3-030-24305-0_53

M3 - Conference contribution

AN - SCOPUS:85068622160

SN - 9783030243043

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 717

EP - 728

BT - Computational Science and Its Applications- ICCSA 2019 - 19th International Conference, Proceedings

A2 - Murgante, Beniamino

A2 - Gervasi, Osvaldo

A2 - Stankova, Elena

A2 - Korkhov, Vladimir

A2 - Misra, Sanjay

A2 - Torre, Carmelo

A2 - Tarantino, Eufemia

A2 - Taniar, David

A2 - Rocha, Ana Maria A.C.

A2 - Apduhan, Bernady O.

PB - Springer Nature

T2 - 19th International Conference on Computational Science and Its Applications, ICCSA 2019

Y2 - 1 July 2019 through 4 July 2019

ER -