PARALLEL IMPLEMENTATION AND OPTIMIZATION OF THE SEBVHOS ALGORITHM  

作　　者：Li Wen Guo Li Yuan Hongxing Wei Yifang Guan Hua 

机构地区：[1]Deptartmen of Electronic Science and Technology, University of Science and Technology of China, Hefei 230027, China

出　　处：《Journal of Electronics(China)》2011年第3期277-283,共7页电子科学学刊（英文版）

基　　金：Supported by the National Natural Science Foundation of China(No.61071173)

摘　　要：In this paper, a parallel Surface Extraction from Binary Volumes with Higher-Order Smoothness (SEBVHOS) algorithm is proposed to accelerate the SEBVHOS execution. The original SEBVHOS algorithm is parallelized first, and then several performance optimization techniques which are loop optimization, cache optimization, false sharing optimization, synchronization overhead op-timization, and thread affinity optimization, are used to improve the implementation's performance on multi-core systems. The performance of the parallel SEBVHOS algorithm is analyzed on a dual-core system. The experimental results show that the parallel SEBVHOS algorithm achieves an average of 1.86x speedup. More importantly, our method does not come with additional aliasing artifacts, com-paring to the original SEBVHOS algorithm.In this paper, a parallel Surface Extraction from Binary Volumes with Higher-Order Smoothness （SEBVHOS） algorithm is proposed to accelerate the SEBVHOS execution. The original SEBVHOS algorithm is parallelized first, and then several performance optimization techniques which are loop optimization, cache optimization, false sharing optimization, synchronization overhead op-timization, and thread affinity optimization, are used to improve the implementation＇s performance on multi-core systems. The performance of the parallel SEBVHOS algorithm is analyzed on a dual-core system. The experimental results show that the parallel SEBVHOS algorithm achieves an average of 1.86x speedup. More importantly, our method does not come with additional aliasing artifacts, com-paring to the original SEBVHOS algorithm.

关 键 词：MULTI-CORE Parallel algorithm Performance optimization 3D reconstruction 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]