University of Warsaw Lagrangian Cloud Model (UWLCM) 2.0: Adaptation of a mixed Eulerian-Lagrangian numerical model for heterogeneous computing clusters

Abstract

Abstract. A numerical cloud model with Lagrangian particles coupled to an Eulerian flow is adapted for distributed memory systems. Eulerian and Lagrangian calculations can be done in parallell on CPUs and GPUs, respectively. Scaling efficiency and the amount of parallelization of CPU and GPU calculations both exceed 50 % for up to 40 nodes. A sophisticated Lagrangian microphysics model slows down simulation by only 50 % compared to a simplistic bulk microphysics model, thanks to the use of GPUs. Overhead of communications between cluster nodes is mostly related to the pressure solver. Presented method of adaptation for computing clusters can be used in any numerical model with Lagrangian particles coupled to an Eulerian fluid flow.

Modeling Collision-Coalescence in Particle Microphysics: Numerical Convergence of Mean and Variance of Precipitation in Cloud Simulations Using University of Warsaw Lagrangian Cloud Model (UWLCM) 2.1

“…Plotting of UWLCM results was done with the UWLCM_plotting package. In the study, the following code versions were used: UWLCM v2.1 , libmpdata++ v2.1 (Arabas et al, 2023b), libcloudph++ v3.1 (Arabas et al, 2023a), UWLCM_plotting v1.0 (Dziekan and Zmijewski, 2023), coal_fluctu v2.0 (Dziekan, 2023). Dataset, run scripts, and plotting scripts are available at Zmijewski et al (2023).…”