摘要
针对大数据量图像处理的实时性,改进了BSP计算模型,解决了超步划分、超步丢失、数据传输等问题。设计了适合实时图像并行处理的集群结构。采用广播式的通信方式极大地缩短了通信时间,提高了实时性。从加速比、效率方面分析了并行计算的性能,实验证明了此方法的有效性。
Considering the real-time processing on large numbers of image data, an improvement on BSP computational model is made. Based on it, several issues have been settled such as the division of super-step, the loss of super-step, the transmission of data, etc. At the same time, the cluster architecture adapting to paralell computing for the real-time images has been designed. Meanwhile, radio-style communication greatly reduces the time of communication and improves capability using the of the real time. This article analyzes the performance of the parallel computing in the fields of the speedup-ratio and efficiency. The validity of this model has been verified by experiments.
出处
《西安科技大学学报》
CAS
北大核心
2011年第2期218-222,共5页
Journal of Xi’an University of Science and Technology
基金
西安科技大学培育基金项目(A515018)
关键词
BSP模型
并行处理
采样周期
加速比
BSP model
paralell computing
sampling cycle
speedup-ratio
