Acceleration of image blurring algorithm on multicore architecture

Aman Arora, N. A. Pande
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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.
多核结构下图像模糊算法的加速研究
具有工业视觉的生产链越来越普遍。这些过程通常是繁重的,并应用于具有重要帧率的高清图像。因此,需要强大的计算器来跟上不断增长的生产速度。NVIDIA目前正在设计提供CUDA(计算统一设备架构)架构的接口,允许并行数据计算。这可以提高使用图形处理单元(GPU)的每个操作系统的性能。纯数据,由于其图形模块化开发环境,允许快速原型开发。这些因素促使我们开始了一个研究项目,致力于实现用CUDA编写的纯数据图像处理模块。因此,我们实现了图像模糊算法来熟悉GPGPU。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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