分布式并行计算对数字化人体图像重采样时间的影响

目的 探讨不同客户机规模的分布式并行计算对数字化人体图像重采样时间的影响.方法 将计算机分为1个串行计算组与5个并行计算组,对同一个数字化人体数据集重采样生成冠状面与矢状面图像,比较各组重采样时客户机与服务器的处理时间,以及并行计算加速比.结果 ①并行计算组与串行计算组比较,客户机重采样时间均显著减少(P＜0.01).②16台客户机组与8台客户机组、24台客户机组与16台客户机组比较,客户机重采样时间均显著减少(P＜0.01),但32台客户机组与24台客户机组、40台客户机组与32台客户机组比较,客户机重采样时间无显著差异(P＞0.05).结论 分布式并行计算能够大幅度减少数字化人体数据集重采样生成冠状面与矢状面图像的时间,但串行处理和通信开销制约了进一步并行化的规模.

Effect of distributed parallel-computing on the time of resampling of digitized human

Objective To explore the effect of distributed parallel-computing on the time of resampling of digitized human with different amounts of client.Methods Computers were randomly divided into one group of serial-computing and five groups of parallel-computing,and the same data of digitized human was resampled by each group.The resampling time of clients and server in each group,speedup of parallel-computing were compared.Results Compared with the group of serial-computing,the time of resampling of the groups of parallel-computing decreased greatly(P<0.01).Compared with the group of 8 clients,the time of resampling of the group of 16 clients decreased greatly(P<0.01).Compared with the group of 16 clients,the time of resampling of the group of 24 clients decreased greatly(P<0.01).Conclusion With distributed parallel-computing for resampling transverse sectional anatomical data from digitized human,the resampling time decreases greatly,but serial processing and communication restrict further parallel processing.