Scan primitives for vector computers
Proceedings of the 1990 ACM/IEEE conference on Supercomputing
Opportunistic algorithms for eliminating supersets
Acta Informatica
Finding extremal sets in less than quadratic time
Information Processing Letters
A simple sub-quadratic algorithm for computing the subset partial order
Information Processing Letters
Mersenne twister: a 623-dimensionally equidistributed uniform pseudo-random number generator
ACM Transactions on Modeling and Computer Simulation (TOMACS) - Special issue on uniform random number generation
Multi-visibility maps of triangulated terrains
International Journal of Geographical Information Science
Frequent itemset mining on graphics processors
Proceedings of the Fifth International Workshop on Data Management on New Hardware
On-line discovery of flock patterns in spatio-temporal data
Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Computing Popular Places Using Graphics Processors
ICDMW '10 Proceedings of the 2010 IEEE International Conference on Data Mining Workshops
Research note: Connected component labeling on a 2D grid using CUDA
Journal of Parallel and Distributed Computing
Itemset support queries using frequent itemsets and their condensed representations
DS'06 Proceedings of the 9th international conference on Discovery Science
Effective preprocessing in SAT through variable and clause elimination
SAT'05 Proceedings of the 8th international conference on Theory and Applications of Satisfiability Testing
Efficient local search on the GPU-Investigations on the vehicle routing problem
Journal of Parallel and Distributed Computing
Solving very large instances of the scheduling of independent tasks problem on the GPU
Journal of Parallel and Distributed Computing
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The extremal sets of a family F of sets consist of all sets of F that are maximal or minimal with respect to the partial order induced by the subset relation in F. In this paper we present efficient parallel GPU-based algorithms, designed under CUDA architecture, for finding the extremal sets of a family F of sets. The complexity analysis of the presented algorithms together with experimental results showing the efficiency and scalability of the approach is provided.