In this paper, a new method for DO-loop parallelization based on the new collcept allocation-dependence and equivalence classification of iteration space is proposed. This method has many advantages: It is a general,...In this paper, a new method for DO-loop parallelization based on the new collcept allocation-dependence and equivalence classification of iteration space is proposed. This method has many advantages: It is a general,ullified method for DO-loop parallelization. It is used in coarse grain parallel partitioning on MINID and SPMD. While partitioning iteration space, it also does the does the partition and computation partition such that these partitions are independent each other. It can extract the potential parallelism of program accurately. Combining with task-level parallelization vectorization and pipeline,it can extract parallelism thoroughly.展开更多
In this paper,improvement on man-computer interactive classification of clouds based on hispeetral satellite imagery has been synthesized by using the maximum likelihood automatic clustering(MLAC)and the unit feature ...In this paper,improvement on man-computer interactive classification of clouds based on hispeetral satellite imagery has been synthesized by using the maximum likelihood automatic clustering(MLAC)and the unit feature space classification(UFSC)approaches.The improved classification not only shortens the time of sample-training in UFSC method,but also eliminates the inevitable shortcomings of the MLAC method.(e.g.,1.sample selecting and training is confined only to one cloud image:2.the result of clustering is pretty sensitive to the selection of initial cluster center:3.the actual classification basically can not satisfy the supposition of normal distribution required by MLAC method;4.errors in classification are difficult to be modified.) Moreover,it makes full use of the professionals'accumulated knowledge and experience of visual cloud classifications and the cloud report of ground observation,having ensured both the higher accuracy of classification and its wide application as well.展开更多
文摘In this paper, a new method for DO-loop parallelization based on the new collcept allocation-dependence and equivalence classification of iteration space is proposed. This method has many advantages: It is a general,ullified method for DO-loop parallelization. It is used in coarse grain parallel partitioning on MINID and SPMD. While partitioning iteration space, it also does the does the partition and computation partition such that these partitions are independent each other. It can extract the potential parallelism of program accurately. Combining with task-level parallelization vectorization and pipeline,it can extract parallelism thoroughly.
文摘In this paper,improvement on man-computer interactive classification of clouds based on hispeetral satellite imagery has been synthesized by using the maximum likelihood automatic clustering(MLAC)and the unit feature space classification(UFSC)approaches.The improved classification not only shortens the time of sample-training in UFSC method,but also eliminates the inevitable shortcomings of the MLAC method.(e.g.,1.sample selecting and training is confined only to one cloud image:2.the result of clustering is pretty sensitive to the selection of initial cluster center:3.the actual classification basically can not satisfy the supposition of normal distribution required by MLAC method;4.errors in classification are difficult to be modified.) Moreover,it makes full use of the professionals'accumulated knowledge and experience of visual cloud classifications and the cloud report of ground observation,having ensured both the higher accuracy of classification and its wide application as well.
