Scientists Develop Custom Software to Accelerate High-Profile Ocean Model
In a breakthrough for climate research, a team of scientists from the Department of Energy’s Oak Ridge, Los Alamos, and Sandia National Laboratories has revolutionized the field by developing custom software that significantly accelerates the calculation of ocean waves in high-profile climate models. The software, which focuses on simulating barotropic waves, reduces the total run time of the Model for Prediction Across Scales-Ocean (MPAS-Ocean) by a remarkable 45%.
The researchers tested their software on several supercomputers, including the Summit supercomputer at Oak Ridge National Laboratory, the Compy supercomputer at Pacific Northwest National Laboratory, and the Cori and Perlmutter supercomputers at Lawrence Berkeley National Laboratory’s National Energy Research Scientific Computing Center. The results of their primary simulations were published in the International Journal of High Performance Computing Applications.
To overcome the challenge of simulating two different modes of ocean waves simultaneously, the team utilized Trilinos and ForTrilinos, open-source software libraries that are ideal for solving scientific problems on supercomputers. By incorporating Fortran interfaces into existing C++ packages, the team was able to design and customize a new solver algorithm specifically optimized for barotropic waves, which are characterized by fast wave propagation speed.
Lead author Hyun Kang, a computational Earth system scientist at Oak Ridge National Laboratory, highlighted the convenience and efficiency of the software, stating, A useful feature of this interface is that we can use every component of the C++ package in the Fortran language so we don’t need to translate anything.
This significant development builds upon previous research efforts aimed at improving MPAS-Ocean. The new solver algorithm addresses the limitations of the previously developed solver, particularly when running MPAS-Ocean with a small number of compute cores for a given problem size.
MPAS-Ocean’s default solver relies on a technique known as explicit subcyling, which requires smaller time steps to calculate the characteristics of barotropic waves accurately. However, this technique demands substantial computing power due to the increased number of iterations required for barotropic calculations. In contrast, the new semi-implicit solver algorithm is unconditionally stable, allowing the use of larger time steps without sacrificing accuracy. This results in significant time and computing power savings.
The development of this custom software is a testament to the collaboration between software developers and climate scientists. By leveraging the optimized algorithms within the Trilinos and ForTrilinos libraries, researchers can accelerate their simulations and advance their climate research without the need for extensive coding.
While the current solver still has limitations in terms of scalability on high-performance computing systems, it has exhibited exceptional performance on a certain number of processors. The team is currently working on optimizing processor communications and porting the solver to GPUs to overcome this limitation.
Moreover, the researchers have also made improvements to the time stepping method for the baroclinic system in MPAS-Ocean, further enhancing the model’s efficiency. These advancements aim to make climate predictions faster, more reliable, and more accurate, ultimately facilitating climate security and enabling timely decision-making and high-resolution projections.
Kang emphasized the far-reaching impact of this development, stating, By speeding up this model, we can reduce energy use, improve simulations, and more easily predict the effects of climate change decades or even thousands of years into the future.
This groundbreaking achievement not only streamlines climate research efforts but also contributes to a more sustainable and energy-efficient approach to modeling Earth’s climate system. With the acceleration of climate predictions, scientists can gain deeper insights into the complex dynamics of our changing planet and take crucial steps toward mitigating the impacts of climate change.
Reference: An implicit barotropic mode solver for MPAS-ocean using a modern Fortran solver interface by Hyun-Gyu Kang, Raymond S Tuminaro, Andrey Prokopenko, Seth R Johnson, Andrew G Salinger, and Katherine J Evans, The International Journal of High Performance Computing Applications.
This research was supported by the Energy Exascale Earth System Model (E3SM) and the Exascale Computing Project (ECP).
