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<h2 align="center">BINGHAMTON UNIVERSITY / SPRING 2012 / CS486</h2>
= Project Resources =
==Senior Project ==
* [[CUDA_Programming/ProjectDescription|Project Description]]
<h3 align="center"> Learning CUDA and Implement it with ANOVA </h3>
* [[CUDA_Programming/InformationSources|List of papers, documents, books etc. that I have/will read]]
* [[CCUDA Parallel Programming/Terminology|Terminology]]
* [[CUDA Parallel Programming/BenchmarkingTools|Benchmarking Tools]]
* [[CUDA Parallel Programming/DeviceQuery|[Tutorial] How to query the properties of a CUDA device using the corresponding API?]]


==Project Members:==
Alper ALIMOGLU


= Project Resources =
<h2 align="center">BINGHAMTON UNIVERSITY</h2>
* [[CUDA Parallel Programming/ProjectDescription|Project Description]]
<h2 align="center">SPRING 2012</h2>
* [[CUDA Parallel Programming/Anova with CUDA|Anova with CUDA]]
<h2 align="center">CS486</h2 >
* [[CUDA Parallel Programming/Learn CUDA and Implementation with ANOVA|Learn CUDA and Implementation with ANOVA]]
<h2 align="center">CUDA with FastAnova</h2 >
* [[CUDA Parallel Programming/References|References]]

<h3 align="left">Alper ALIMOGLU</h3 >
<h3 align="center">INDEX</h3 >

<h4 align="left">1.Introduction</h4>
<p> CUDA stands for Compute Unified Device Architecture and is a new hardware and software architecture for issuing and managing computations on the GPU as a data-parallel computing device without the need of mapping them to a graphics API. CUDA includes a programming model along with hardware support that simplifies parallel implementation. CUDA is one of the main programming languages that increase the speed of result more than any other languages. Programmers need training in parallel programming to be fully effective in computer science. CUDA forms a platform that contains both high-performance applications for heterogeneous platforms that contain both central and graphics processing units. Data-parallel processing maps data elements to parallel processing threads. Many applications that process large data sets such as arrays can use a data-parallel programming model to speed up the computations. In that case I aimed to use CUDA in order to do a helpful analyze on the medical area (bad-genes). As a first step I search a string under a 1 Mb of a text file under parallel programming. My aim was to observe how parallel programming might increase the performance of the process.</p>
<hr>

<h4 align="left">2.Definition of SNP-Genes</h4>

Latest revision as of 06:06, 15 May 2012

BINGHAMTON UNIVERSITY / SPRING 2012 / CS486

Senior Project

Learning CUDA and Implement it with ANOVA

Project Members:

Alper ALIMOGLU

Project Resources