We present a new method for estimating missing values or correcting unreliable observed values of time dependent physical fields. This method, is based on Hidden Markov Models and Self-Organizing Maps, and is named PR...We present a new method for estimating missing values or correcting unreliable observed values of time dependent physical fields. This method, is based on Hidden Markov Models and Self-Organizing Maps, and is named PROFHMM_UNC. PROFHMM_UNC combines the knowledge of the physical process under study provided by an already known dynamic model and the truncated time series of observations of the phenomenon. In order to generate the states of the Hidden Markov Model, Self-Organizing Maps are used to discretize the available data. We make a modification to the Viterbi algorithm that forces the algorithm to take into account a priori information on the quality of the observed data when selecting the optimum reconstruction. The validity of PROFHMM_UNC was endorsed by performing a twin experiment with the outputs of the ocean biogeochemical NEMO-PISCES model.展开更多
All-to-all personalized communication,or complete exchange,is at the heart of numerous applications in paral-lel computing.It is one of the most dense communication patterns.In this paper,we consider this problem in a...All-to-all personalized communication,or complete exchange,is at the heart of numerous applications in paral-lel computing.It is one of the most dense communication patterns.In this paper,we consider this problem in a2D/3D mesh and a multidimensional interconnection network with the wormhole-routing capability.We propose complete ex-change algorithms for them respectively.We propose O(mn 2 )phase algorithm for2D mesh P m ×P n and O(mn 2 l 2 )phase algo-rithm for3D mesh P m ×P n ×P l ,where m,n,l are any positive integers.Also O(ph(G 1 )n 2 )phase algorithm is proposed for a multidimensional interconnection network G 1 ×G 2 ,where ph(G 1 )stands for complete exchange phases of G 1 and|G 2 |=n.展开更多
文摘We present a new method for estimating missing values or correcting unreliable observed values of time dependent physical fields. This method, is based on Hidden Markov Models and Self-Organizing Maps, and is named PROFHMM_UNC. PROFHMM_UNC combines the knowledge of the physical process under study provided by an already known dynamic model and the truncated time series of observations of the phenomenon. In order to generate the states of the Hidden Markov Model, Self-Organizing Maps are used to discretize the available data. We make a modification to the Viterbi algorithm that forces the algorithm to take into account a priori information on the quality of the observed data when selecting the optimum reconstruction. The validity of PROFHMM_UNC was endorsed by performing a twin experiment with the outputs of the ocean biogeochemical NEMO-PISCES model.
文摘All-to-all personalized communication,or complete exchange,is at the heart of numerous applications in paral-lel computing.It is one of the most dense communication patterns.In this paper,we consider this problem in a2D/3D mesh and a multidimensional interconnection network with the wormhole-routing capability.We propose complete ex-change algorithms for them respectively.We propose O(mn 2 )phase algorithm for2D mesh P m ×P n and O(mn 2 l 2 )phase algo-rithm for3D mesh P m ×P n ×P l ,where m,n,l are any positive integers.Also O(ph(G 1 )n 2 )phase algorithm is proposed for a multidimensional interconnection network G 1 ×G 2 ,where ph(G 1 )stands for complete exchange phases of G 1 and|G 2 |=n.
