This paper describes a Wrapper Generator for wrapping high performance legacy codes as Java/CORBA components for use in a distributed component-based problem-solving environment. Using the Wrapper Generator we have au...
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ISBN:
(纸本)9780780398023
This paper describes a Wrapper Generator for wrapping high performance legacy codes as Java/CORBA components for use in a distributed component-based problem-solving environment. Using the Wrapper Generator we have automatically wrapped an MPI-based legacy code as a single CORBA object, and implemented a problem-solving environment for molecular dynamicsimulations. Performance comparisons between runs of the CORBA object and the original legacy code on a cluster of workstations and on a parallel computer are also presented.
This paper analyses the problems of some applications on the traditional distributed parallel computing and running on the grid, extends the Log P parallelcomputing model to the grid and presents the double Log P mod...
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This paper analyses the problems of some applications on the traditional distributed parallel computing and running on the grid, extends the Log P parallelcomputing model to the grid and presents the double Log P model. And then it presents the strategy to design parallel algorithm on the grid, finally improves the parallel algorithm of CG according to the characters of the grid.
Voltage fluctuations in distribution networks are usually caused by the stochastic volatility of photovoltaic generation system and load. The traditional deterministic power flow calculation method is difficult to ass...
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Voltage fluctuations in distribution networks are usually caused by the stochastic volatility of photovoltaic generation system and load. The traditional deterministic power flow calculation method is difficult to assess the voltage risk. Moreover, traditional serial computing technologies cannot provide rapid voltage risk assessment of large-scale distribution networks. To address these problems, the probabilistic characteristics of PV generation and load fluctuations are first analyzed. Then, the corresponding probabilistic model is established based on the Newton-Raphson algorithm. Finally, an indicator to evaluate voltage risk is proposed by using the Monte-Carlo simulation. In order to meet the computing speed requirement imposed by large-scale distribution networks, a parallelcomputing platform based on Apache Spark is designed, and a parallel implementation of the Monte-Carlo simulation on Spark Resilience distributed Datasets (RDD) is established. Simulation results based on real-world data illustrate the effectiveness of the proposed voltage risk assessment for large-scale distribution power networks and its computational efficiency.
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