Two popular traditional join algorithms and their parallel versions are introduced. When designing join algorithms in serial computing environment, decomposing inner relation is considered as the right direction to sa...Two popular traditional join algorithms and their parallel versions are introduced. When designing join algorithms in serial computing environment, decomposing inner relation is considered as the right direction to save disk I/Os. However, two different decomposition algorithms are compared, such as inner vs. outer decomposition first algorithms for tuple-based and block-based nested loop joins, showing that the proposed approach is 20% better than general approach. Also lemmas are proved, when we have to use the outer decomposition first parallel join algorithms.展开更多
The coupler is fundamental for a coupled model to realize complex interactions among component models.This paper focuses on the coupling process of Wave-Circulation(W-C) coupled model which consists of MASNUM(key labo...The coupler is fundamental for a coupled model to realize complex interactions among component models.This paper focuses on the coupling process of Wave-Circulation(W-C) coupled model which consists of MASNUM(key laboratory of marine science and numerical modeling wave model)and POM(Princeton Ocean Model).The current coupling module of this coupled model is based on the inefficient I/O file,which has already become a performance bottleneck especially when the coupled model utilizes a large number of processes.To improve the performance of the W-C model,a flexible coupling module based on the model coupling toolkit(MCT) is designed and implemented to replace the current I/O file coupling module in the coupled model.Empirical studies that we have carried out demonstrate that our online coupling module can dramatically improve the parallel performance of the coupled model.The online coupling module outperforms the I/O file coupling module.When processes increase to 96,the whole process of EXP-C takes only 695.8 seconds,which is only 58.8%of the execution time of EXP-F.Based on our experiments under 2D Parallel Decomposition(2DPD),we suggest setting parallel decomposition strategies automatically to component models in order to achieve high parallel efficiency.展开更多
基金supported by the National Research Foundation (NRF) of Korea through contract N-14-NMIR06
文摘Two popular traditional join algorithms and their parallel versions are introduced. When designing join algorithms in serial computing environment, decomposing inner relation is considered as the right direction to save disk I/Os. However, two different decomposition algorithms are compared, such as inner vs. outer decomposition first algorithms for tuple-based and block-based nested loop joins, showing that the proposed approach is 20% better than general approach. Also lemmas are proved, when we have to use the outer decomposition first parallel join algorithms.
基金Supported by the National High Technology Research and Development Programme(No.2010AA012400,2010AA012302)the National Natural Science Foundation of China(No.61040048)
文摘The coupler is fundamental for a coupled model to realize complex interactions among component models.This paper focuses on the coupling process of Wave-Circulation(W-C) coupled model which consists of MASNUM(key laboratory of marine science and numerical modeling wave model)and POM(Princeton Ocean Model).The current coupling module of this coupled model is based on the inefficient I/O file,which has already become a performance bottleneck especially when the coupled model utilizes a large number of processes.To improve the performance of the W-C model,a flexible coupling module based on the model coupling toolkit(MCT) is designed and implemented to replace the current I/O file coupling module in the coupled model.Empirical studies that we have carried out demonstrate that our online coupling module can dramatically improve the parallel performance of the coupled model.The online coupling module outperforms the I/O file coupling module.When processes increase to 96,the whole process of EXP-C takes only 695.8 seconds,which is only 58.8%of the execution time of EXP-F.Based on our experiments under 2D Parallel Decomposition(2DPD),we suggest setting parallel decomposition strategies automatically to component models in order to achieve high parallel efficiency.
