{"title":"Acceleration of image blurring algorithm on multicore architecture","authors":"Aman Arora, N. A. Pande","doi":"10.1109/I2CT.2014.7092182","DOIUrl":null,"url":null,"abstract":"Production chains featuring industrial vision are becoming more and more widespread. Those processes are often heavy and applied to high definition images with important frame rate. Powerful calculators are thus needed to follow the ever growing production rate. NVIDIA is currently designing interfaces providing a CUDA (Compute Unified Device Architecture) architecture allowing parallel data computation. This could increase the performance of every operating system using graphical processing units (GPU). Pure Data, thanks to its graphical modular development environment, allows fast prototype developments. Those factors led us to start a research program dedicated to the realizations of image processing modules for Pure Data written in CUDA. So in this we have implemented image blurring algorithm to get familiar with GPGPU.","PeriodicalId":384966,"journal":{"name":"International Conference for Convergence for Technology-2014","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference for Convergence for Technology-2014","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/I2CT.2014.7092182","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Production chains featuring industrial vision are becoming more and more widespread. Those processes are often heavy and applied to high definition images with important frame rate. Powerful calculators are thus needed to follow the ever growing production rate. NVIDIA is currently designing interfaces providing a CUDA (Compute Unified Device Architecture) architecture allowing parallel data computation. This could increase the performance of every operating system using graphical processing units (GPU). Pure Data, thanks to its graphical modular development environment, allows fast prototype developments. Those factors led us to start a research program dedicated to the realizations of image processing modules for Pure Data written in CUDA. So in this we have implemented image blurring algorithm to get familiar with GPGPU.