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SCHEDULE: NOV 15-20, 2015

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GPU Acceleration of a Non-Hydrostatic Ocean Model Using a Mixed Precision Multigrid Preconditioned Conjugate Gradient Method

SESSION: Regular & ACM Student Research Competition Poster Reception

EVENT TYPE: Posters, Receptions, ACM Student Research Competition

EVENT TAG(S): HPC Beginner Friendly, Regular Poster

TIME: 5:15PM - 7:00PM

SESSION CHAIR(S): Michela Becchi, Manish Parashar, Dorian C. Arnold

AUTHOR(S):Takateru Yamagishi, Yoshimasa Matsumura

ROOM:Level 4 - Lobby


To meet the demand for fast and detailed calculations in numerical ocean simulation, we implemented a non-hydrostatic ocean model on the GPU, using basic and essential methods such as exploitation of large-scale parallelism in threads and instructions, coalesced access to the global memory, and minimization of memory transfer between the CPU host and GPU device. We also studied and evaluated the application of mixed precision calculation to the multigrid preconditioning of a Poisson/Helmholtz solver, which would deteriorate in performance due to the small number of threads in the multigrid method. The GPU-implemented model ran 4.3 times faster on NVIDIA K20C than on Fujitsu SPARC64 VIIIfx. The application of mixed precision achieved a 16% acceleration of the Poisson/Helmholtz solver, which is consistent with the decrease of global memory transfer due to the switch to mixed precision. No specific errors were found in the outputs.

Chair/Author Details:

Michela Becchi, Manish Parashar, Dorian C. Arnold (Chair) - University of Missouri|Rutgers University|University of New Mexico|

Takateru Yamagishi - Research Organization for Information Science and Technology

Yoshimasa Matsumura - Hokkaido University

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