Accelerating Lagrangian transport simulations on graphics processing units: performance optimizations of Massive-Parallel Trajectory Calculations (MPTRAC) v2.6

Hoffmann, Lars; Haghighi Mood, Kaveh; Herten, Andreas; Hrywniak, Markus; Kraus, Jiri; Clemens, Jan; Liu, Mingzhao

doi:https://doi.org/10.5194/gmd-17-4077-2024

Articles | Volume 17, issue 9

https://doi.org/10.5194/gmd-17-4077-2024

© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/gmd-17-4077-2024

© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 17, issue 9

Development and technical paper

|

17 May 2024

Development and technical paper |

| 17 May 2024

Accelerating Lagrangian transport simulations on graphics processing units: performance optimizations of Massive-Parallel Trajectory Calculations (MPTRAC) v2.6

Lars Hoffmann, Kaveh Haghighi Mood, Andreas Herten, Markus Hrywniak, Jiri Kraus, Jan Clemens, and Mingzhao Liu

Data sets

Supplementary material to `Accelerating Lagrangian transport simulations on graphics processing units: performance optimizations of MPTRAC v2.6' Lars Hoffmann https://doi.org/10.5281/zenodo.10065785

Browse reanalysis datasets ECMWF https://www.ecmwf.int/en/forecasts/datasets/browse-reanalysis-datasets

Model code and software

Massive-Parallel Trajectory Calculations (MPTRAC) v2.6 L. Hoffmann et al. https://doi.org/10.5281/zenodo.10067751

Short summary

Lagrangian particle dispersion models are key for studying atmospheric transport but can be computationally intensive. To speed up simulations, the MPTRAC model was ported to graphics processing units (GPUs). Performance optimization of data structures and memory alignment resulted in runtime improvements of up to 75 % on NVIDIA A100 GPUs for ERA5-based simulations with 100 million particles. These optimizations make the MPTRAC model well suited for future high-performance computing systems.