Speedup of Interval Type 2 Fuzzy Logic Systems Based on GPU for Robot Navigation

As the number of rules and sample rate for type 2 fuzzy logic systems (T2FLSs) increases, the speed of calculations becomes a problem. The T2FLS has a large membership value of inherent algorithmic parallelism that modern CPU architectures do not exploit. In the T2FLS, many rules and algorithms can...

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Main Authors: Long Thanh Ngo, Dzung Dinh Nguyen, Long The Pham, Cuong Manh Luong
Format: Article
Language:English
Published: Wiley 2012-01-01
Series:Advances in Fuzzy Systems
Online Access:http://dx.doi.org/10.1155/2012/698062
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author Long Thanh Ngo
Dzung Dinh Nguyen
Long The Pham
Cuong Manh Luong
author_facet Long Thanh Ngo
Dzung Dinh Nguyen
Long The Pham
Cuong Manh Luong
author_sort Long Thanh Ngo
collection DOAJ
description As the number of rules and sample rate for type 2 fuzzy logic systems (T2FLSs) increases, the speed of calculations becomes a problem. The T2FLS has a large membership value of inherent algorithmic parallelism that modern CPU architectures do not exploit. In the T2FLS, many rules and algorithms can be speedup on a graphics processing unit (GPU) as long as the majority of computation a various stages and components are not dependent on each other. This paper demonstrates how to install interval type 2 fuzzy logic systems (IT2-FLSs) on the GPU and experiments for obstacle avoidance behavior of robot navigation. GPU-based calculations are high-performance solution and free up the CPU. The experimental results show that the performance of the GPU is many times faster than CPU.
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institution Kabale University
issn 1687-7101
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language English
publishDate 2012-01-01
publisher Wiley
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series Advances in Fuzzy Systems
spelling doaj-art-c1506405d36a4856b87e25d5dce9dfb52025-02-03T06:00:16ZengWileyAdvances in Fuzzy Systems1687-71011687-711X2012-01-01201210.1155/2012/698062698062Speedup of Interval Type 2 Fuzzy Logic Systems Based on GPU for Robot NavigationLong Thanh Ngo0Dzung Dinh Nguyen1Long The Pham2Cuong Manh Luong3Department of Information Systems, Le Quy Don Technical University, No 100, Hoang Quoc Viet St., Cau Giay, Hanoi, VietnamDepartment of Information Systems, Le Quy Don Technical University, No 100, Hoang Quoc Viet St., Cau Giay, Hanoi, VietnamDepartment of Information Systems, Le Quy Don Technical University, No 100, Hoang Quoc Viet St., Cau Giay, Hanoi, VietnamDepartment of Information Systems, Le Quy Don Technical University, No 100, Hoang Quoc Viet St., Cau Giay, Hanoi, VietnamAs the number of rules and sample rate for type 2 fuzzy logic systems (T2FLSs) increases, the speed of calculations becomes a problem. The T2FLS has a large membership value of inherent algorithmic parallelism that modern CPU architectures do not exploit. In the T2FLS, many rules and algorithms can be speedup on a graphics processing unit (GPU) as long as the majority of computation a various stages and components are not dependent on each other. This paper demonstrates how to install interval type 2 fuzzy logic systems (IT2-FLSs) on the GPU and experiments for obstacle avoidance behavior of robot navigation. GPU-based calculations are high-performance solution and free up the CPU. The experimental results show that the performance of the GPU is many times faster than CPU.http://dx.doi.org/10.1155/2012/698062
spellingShingle Long Thanh Ngo
Dzung Dinh Nguyen
Long The Pham
Cuong Manh Luong
Speedup of Interval Type 2 Fuzzy Logic Systems Based on GPU for Robot Navigation
Advances in Fuzzy Systems
title Speedup of Interval Type 2 Fuzzy Logic Systems Based on GPU for Robot Navigation
title_full Speedup of Interval Type 2 Fuzzy Logic Systems Based on GPU for Robot Navigation
title_fullStr Speedup of Interval Type 2 Fuzzy Logic Systems Based on GPU for Robot Navigation
title_full_unstemmed Speedup of Interval Type 2 Fuzzy Logic Systems Based on GPU for Robot Navigation
title_short Speedup of Interval Type 2 Fuzzy Logic Systems Based on GPU for Robot Navigation
title_sort speedup of interval type 2 fuzzy logic systems based on gpu for robot navigation
url http://dx.doi.org/10.1155/2012/698062
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