Solving multiple kth smallest dissimilarity queries for non-metric dissimilarities with the GPU

Nearest and farthest spatial skyline queries under multiplicative weighted Euclidean distances

“…One of them solves the problem sequentially in the CPU and the other takes advantage of the parallel and compute capabilities of the GPU to accelerate the process. The GPU has been used in last years to accelerate the resolution of many problems and it is shown that it provides very good results [11][12][13][14][15]43,44]. Hence, we want to exploit its parallel and compute capabilities to try to solve the problem faster in parallel.…”

“…query points and searches in the space by visiting the neighbors of the visited data points over the Voronoi diagram. They used Lemmas 4,5,9,10,and 15. In their experiments V S 2 preformed better than B 2 S 2 . However, themselves posteriorly show that the version of the V S 2 that had proposed was not completely correct and fixed the errors in [39] by using Lemma 12.…”