DNS of hydrodynamically interacting droplets in turbulent clouds: Parallel implementation and scalability analysis using 2D domain decomposition

The study of turbulent collision of cloud droplets requires simultaneous considerations of the transport by background air turbulence (i.e., geometric collision rate) and influence of droplet disturbance flows (i.e., collision efficiency). In recent years, this multiscale problem has been addressed through a hybrid direct numerical simulation (HDNS) approach (Ayala et al., 2007). This approach, while currently is the only viable tool to quantify the effects of air turbulence on collision statistics, is computationally expensive. In order to extend the HDNS approach to higher flow Reynolds numbers, here we developed a highly scalable implementation of the approach using 2D domain decomposition. The scalability of the parallel implementation was studied using several parallel computers, at 5123 and 10243 grid resolutions with O(106)O(106)–O(107)O(107) droplets. It was found that the execution time scaled with number of processors almost linearly until it saturates and deteriorates due to communication latency issues.To better understand the scalability, we developed a complexity analysis by partitioning the execution tasks into computation, communication, and data copy. Using this complexity analysis, we were able to predict the scalability performance of our parallel code. Furthermore, the theory was used to estimate the maximum number of processors below which the approximately linear scalability is sustained. We theoretically showed that we could efficiently solved problems of up to 81923 with O(100,000)O(100,000) processors. The complexity analysis revealed that the pseudo-spectral simulation of background turbulent flow for a dilute droplet suspension typical of cloud conditions typically takes about 80% of the total execution time, except when the droplets are small (less than 5 μm in a flow with energy dissipation rate of 400 cm2/s3 and liquid water content of 1 g/m3), for which case the particle–particle hydrodynamic interactions become the bottleneck. The complexity analysis was also used to explore some alternative methods to handle FFT calculations within the flow simulation and to advance droplets less than 5 μm in radius, for better computational efficiency. Finally, preliminary results are reported to shed light on the Reynolds number-dependence of collision kernel of non-interacting droplets.