针对词对齐算法在处理大规模平行语料时计算时间复杂度较高的问题,提出一种基于图形处理器(GPU)的词对齐并行计算方法。首先分析了大规模语料中句对长度的分布特征,结合现代GPU的体系架构,提出基于预排序的任务分配策略;然后基于统一计...针对词对齐算法在处理大规模平行语料时计算时间复杂度较高的问题,提出一种基于图形处理器(GPU)的词对齐并行计算方法。首先分析了大规模语料中句对长度的分布特征,结合现代GPU的体系架构,提出基于预排序的任务分配策略;然后基于统一计算设备架构(CUDA)完成对词对齐算法中的期望计算、期望最大化两个核心步骤的并行实现。在NVIDIA Tesla K40M图形处理器上进行了实验,结果表明,该方法与GIZA++相比最高达到246的加速比。展开更多
The development process of complex equipment involves multi-stage business processes,multi-level product architecture,and multi-disciplinary physical processes.The relationship between its system model and various dis...The development process of complex equipment involves multi-stage business processes,multi-level product architecture,and multi-disciplinary physical processes.The relationship between its system model and various disciplinary models is extremely complicated.In the modeling and integration process,extensive customized development is needed to realize model integration and interoperability in different business scenarios.Meanwhile,the differences in modeling and interaction between different modeling tools make it difficult to support the consistent representation of models in complex scenarios.To improve the efficiency of system modeling and integration in complex business scenarios,a system modeling and integration method was proposed.This method took the Sys ML language kernel as the core and system model function integration as the main line.Through the technical means of model view separation,abstract operation interface,and model view configuration,the model modeling and integration of multi-user,multi-model,multi-view,and different business logic in complex business scenarios were realized.展开更多
文摘针对词对齐算法在处理大规模平行语料时计算时间复杂度较高的问题,提出一种基于图形处理器(GPU)的词对齐并行计算方法。首先分析了大规模语料中句对长度的分布特征,结合现代GPU的体系架构,提出基于预排序的任务分配策略;然后基于统一计算设备架构(CUDA)完成对词对齐算法中的期望计算、期望最大化两个核心步骤的并行实现。在NVIDIA Tesla K40M图形处理器上进行了实验,结果表明,该方法与GIZA++相比最高达到246的加速比。
文摘The development process of complex equipment involves multi-stage business processes,multi-level product architecture,and multi-disciplinary physical processes.The relationship between its system model and various disciplinary models is extremely complicated.In the modeling and integration process,extensive customized development is needed to realize model integration and interoperability in different business scenarios.Meanwhile,the differences in modeling and interaction between different modeling tools make it difficult to support the consistent representation of models in complex scenarios.To improve the efficiency of system modeling and integration in complex business scenarios,a system modeling and integration method was proposed.This method took the Sys ML language kernel as the core and system model function integration as the main line.Through the technical means of model view separation,abstract operation interface,and model view configuration,the model modeling and integration of multi-user,multi-model,multi-view,and different business logic in complex business scenarios were realized.
