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Gadget3 is nowadays one of the most frequently used high performing parallelcodes for cosmological hydrodynamical simulations. Recent analyses have shownt\ hat the Neighbour Search process of Gadget3 is one of the mosttime-consuming parts. Thus, a considerable speedup can be expected fromimprovements of the u\ nderlying algorithms. In this work we propose a novelapproach for speeding up the Neighbour Search which takes advantage of thespace-filling-curve particle ordering. Instead of performing Neighbour Searchfor all particles individually, nearby active particles can be grouped and onesingle Neighbour Search can be performed to obta\ in a common superset ofneighbours. Thus, with this approach we reduce the number of searches. On theother hand, tree walks are performed within a larger searching radius. There isan optimal size of grouping that maximize the speedup, which we found bynumerical experiments. We tested the algorithm within the boxes of theMagneticum project. As a result we obtained a speedup of $1.65$ in the Densityand of $1.30$ in the Hydrodynamics computation, respectively, and a totalspeedup of $1.34.$

Exploiting the Space Filling Curve Ordering of Particles in the Neighbour Search of Gadget3