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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Format: | Article |
Language: | English |
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Wiley
2012-01-01
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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. |
format | Article |
id | doaj-art-c1506405d36a4856b87e25d5dce9dfb5 |
institution | Kabale University |
issn | 1687-7101 1687-711X |
language | English |
publishDate | 2012-01-01 |
publisher | Wiley |
record_format | Article |
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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