天津科技大学学报Issue(4)：48-52,5.DOI:10.13364/j.issn.1672-6510.2014.04.011
面向CPU＋GPU异构平台的模板匹配目标识别并行算法
Parallel Algorithm of CPU and GPU-oriented Heterogeneous Computation in Template Matching Target Recognition
摘要
Abstract
Moving object recognition algorithm with high-definition video data suffers from large computation complexities and slow speed. With NVIDIA Tesla K20,c GPU,a method of accelerating the template matching target tracking algorithm with the heterogeneous system integrated with CPU and GPU was proposed. The parallel algorithm was designed by three optimizing means:constant memory,the internal memory of SMX and the brief calculation of correlation coefficient. Finally,the program was coded on compute unified device architecture and tested. The results show that the designed algo-rithm can obviously improve the real-time performance of the algorithm and guarantee the recognition effect.关键词
模板匹配/目标识别/并行计算/统一设备计算架构/图形处理器Key words
template matching/target recognition/parallel computing/compute unified device architecture(CUDA)/graphic processing unit(GPU)分类
信息技术与安全科学引用本文复制引用
马永军,袁赢,李灏..面向CPU＋GPU异构平台的模板匹配目标识别并行算法[J].天津科技大学学报,2014,(4):48-52,5.基金项目
天津市科技支撑计划重点资助项目(12ZCZDGX02400) （12ZCZDGX02400）
