IT2NFS-GPU

•  IT2NFS-GPU realizes an interval type-2 neural fuzzy system on graphic processing units (GPU) to reduce training time.

•  The software platform used is the compute unified device architecture (CUDA) with C language.

•  This document explains the use of IT2NFS-GPU. Detailed implementation techniques of IT2NFS-GPU can be found in the following paper:

C. F. Juang, W. Y. Cheng, and C. W. Liang, “Speedup of learning in interval type-2 neural fuzzy systems through graphic processing units,” accepted to be published in IEEE Trans. Fuzzy Systems, 2015.

•   For GPU implementation of type-1 neural fuzzy systems, please visit the following website to download the implementation source code

Table of Contents

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- Quick Start

- Installation and Data description

- ' IT2NFS-GPU' Usage

- Additional Information

Quick Start

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If you are new to GUDA, please visit the website as follows:

"http://developer.nvidia.com/category/zone/cuda-zone"

which provides all the necessary tools for running CUDA on different systems which includes  developer Drives, GPU Computing SDK, CUDA toolkit and Started Guide.

The Started Guide provides installation and verification in great details on Windows, Linux and Mac.

The CUDA Toolkit has all the development tools, libraries,

and documentation you need to create applications for the CUDA architecture, including:

-CUDA C/C++ Compiler

-GPU Debugging & Profiling Tools

-GPU-Accelerated Math Libraries

-GPU-Accelerated Performance Primitives

Installation and Data description

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On windows systems, we run CUDA on Visual Studio 2008

What you require are:

1) Visual Studio 2008

2) CUDA SDK

3) CUDA Toolkit

Step 1: Add cuda.rules to your project

Step 2: Setup your BIN, INCLUDE, and LIB directories.

Final Step: Specify the CUDA Runtime and CUTIL32D Linkers

If everything has been properly setup, the "build" command should work.

Data description:

 This example studies prediction of the Mackey-Glass chaotic time series. (See Eq. (39) in the paper). Four inputs are used to predict one output. A total of 3000 patterns are used for training and 500 patterns for testing.

Data format: Each row represents an input-output data pair. The first four columns contain inputs and the final column contains the desired outputs.

IT2NFS-GPU Usage

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On Unix systems, type

'cd /home/username/NVIDIA_GPU_Computing_SDK/C/src/ IT2NFS-GPU/'

to change to target folder

and then compile  IT2NFS-GPU.cu by NVCC

'nvcc  IT2NFS-GPU.cu -o  IT2NFS-GPU -arch sm_13'

run the ouput file  IT2NFS-GPU

'./ IT2NFS-GPU'