Title :
Operations of grid general type-2 fuzzy sets based on GPU computing platform
Author_Institution :
Dept. of Inf. Syst., Le Quy Don Tech. Univ., Hanoi, Vietnam
Abstract :
Nowadays, many studies have focused on representation of type-2 fuzzy sets for reducing complexity of computation of operations, especially type-2 fuzzy logic systems. Advances of nVIDIA computing technology allow to deploy of general purpose applications of GPU by parallelizing algorithms. This paper deals with an approach to representation of type-2 fuzzy sets by dividing domain into grid, called grid-based T2FS. Grid-based T2FS is easily to understand and deploy on platform of Graphics Processor Units (GPU) computing and Compute Unified Device Architecture(CUDA) by taking the advantages of computation on matrices. Experiments are implemented in various applications involving join, meet, negation operation and defuzzification. Results on runtime and accuracy are summarised in comparison with CPU computation to show efficiency of the approach.
Keywords :
computational complexity; fuzzy logic; fuzzy set theory; graphics processing units; matrix algebra; parallel algorithms; parallel architectures; GPU computing platform; compute unified device architecture; graphics processor units; grid general type-2 fuzzy set operation; grid-based T2FS; matrices; nVIDIA computing technology; operation computational complexity reduction; parallelizing algorithms; type-2 fuzzy logic systems; Accuracy; Approximation methods; Complexity theory; Fuzzy logic; Fuzzy sets; Graphics processing units; Instruction sets; GPU computing; Type-2 fuzzy sets; defuzzification; fuzzy operations;
Conference_Titel :
Systems, Man, and Cybernetics (SMC), 2012 IEEE International Conference on
Conference_Location :
Seoul
Print_ISBN :
978-1-4673-1713-9
Electronic_ISBN :
978-1-4673-1712-2
DOI :
10.1109/ICSMC.2012.6378231