Submitted as: development and technical paper
10 Jun 2022
Submitted as: development and technical paper | 10 Jun 2022
Status: a revised version of this preprint was accepted for the journal GMD.

Porting the WAVEWATCH III (v6.07) Wave Action Source Terms to GPU

Olawale James Ikuyajolu1,2, Luke Van Roekel3, Steven R. Brus4, Erin E. Thomas3, and Yi Deng1,2 Olawale James Ikuyajolu et al.
  • 1Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, GA, USA
  • 2Program in Ocean Science and Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA
  • 3Fluid Dynamics and Solid Mechanics (T-3), Los Alamos National Laboratory, Los Alamos, NM, USA
  • 4Mathematics and Computer Science Division, Argonne National Laboratory, Lemont, IL, USA

Abstract. Surface gravity waves play a critical role in several processes, including mixing, coastal inundation and surface fluxes. Despite the growing literature on the importance of ocean surface waves, wind-wave processes have traditionally been excluded from Earth system models due to the high computational costs of running spectral wave models. The Next Generation Ocean Model Development in the DOE’s (Department of Energy) E3SM (Energy Exascale Earth System Model) project partly focuses on the inclusion of a wave model, WAVEWATCH III (WW3), into the E3SM. WW3, which was originally developed for operational wave forecasting, needs to be computationally less expensive before it can be integrated into ESMs. To accomplish this, we take advantage of heterogeneous architectures at DOE leadership computing facilities and the increasing computing power of general-purpose graphics processing units (GPU). This paper identifies the wave action source terms as the most computationally intensive module in WW3 and then accelerates them via GPU. Using one GPU, our experiments on two computing platforms, Kodiak (P100 GPU & Intel(R) Xeon(R) CPU E5-2695 v4) and Summit (V100 GPU & IBM POWER9), show speedups of up to 2.4x and 6.6x respectively over one MPI task on CPU. Using different combinations of multiple CPUs and GPUs, we obtained an average speedup of 2x and 4x on Kodiak and Summit. We also discuss how the trade off between occupancy, register and latency affects the GPU performance of WW3.

Olawale James Ikuyajolu et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on gmd-2022-141', Anonymous Referee #1, 10 Jul 2022
    • AC1: 'Reply on RC1', Olawale Ikuyajolu, 01 Dec 2022
  • RC2: 'Comment on gmd-2022-141', Anonymous Referee #2, 12 Aug 2022
    • AC2: 'Reply on RC2', Olawale Ikuyajolu, 01 Dec 2022
  • RC3: 'Comment on gmd-2022-141', Anonymous Referee #3, 13 Sep 2022
    • AC3: 'Reply on RC3', Olawale Ikuyajolu, 01 Dec 2022

Olawale James Ikuyajolu et al.

Olawale James Ikuyajolu et al.


Total article views: 1,002 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
759 218 25 1,002 8 6
  • HTML: 759
  • PDF: 218
  • XML: 25
  • Total: 1,002
  • BibTeX: 8
  • EndNote: 6
Views and downloads (calculated since 10 Jun 2022)
Cumulative views and downloads (calculated since 10 Jun 2022)

Viewed (geographical distribution)

Total article views: 893 (including HTML, PDF, and XML) Thereof 893 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
Latest update: 30 Jan 2023
Executive editor
Having major Earth system model components make full use of new architectures is a critical step on the pathway to exascale climate simulation. This paper documents just this for the widely used WAVEWATCH III model.
Short summary
Wind-generated waves play an important role in modifying physical processes at the air-sea interface, but they have been traditionally excluded from climate models due to the high computational cost of running spectral wave models for climate simulations. To address this, our work identified and accelerated the computationally intensive section of WAVEWATCH III on GPU using OpenACC. This allows for high-resolution modeling of atmosphere-wave-ocean feedbacks in century-scale climate integrations.