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Due to the larger scale of power systems and larger number of converters involved, the simulation of power systems becomes slower, with lower accuracy. FPGA is the new generation computation hardware, which is an integrated circuit designed for a special function. However, FPGA simulation still requires the parallel technology to extend the simulation scale. Network tearing interfaces can be used...
Spatial event forecasting from social media is potentially extremely useful but suffers from critical challenges, such as the dynamic patterns of features (keywords) and geographic heterogeneity (e.g., spatial correlations, imbalanced samples, and different populations in different locations). Most existing approaches (e.g., LASSO regression, dynamic query expansion, and burst detection) address some,...
Coupled application workflows composed of applications implemented using task-based models present new coupling and data exchange challenges, due to the asynchronous interaction and coupling behaviors between tasks of the component applications. In this paper, we present an adaptive data placement approach that addresses these challenges by dynamically adjusting to the asynchronous coupling patterns...
The ship deformation is an inevitable and severe problem for surface ships, especially when the ship is large or the sea condition is rough. Moreover, the positioning or detecting precision of the shipboard equipment will significantly decreases due to the ship deformation. So it is of great significance that estimating the ship deformation angle and restraining its effect in practice. Since ship...
Data staging and in-situ/in-transit data processing are emerging as attractive approaches for supporting extreme scale scientific workflows. These approaches improve end-to-end performance by enabling runtime data sharing between coupled simulations and data analytics components of the workflow. However, the complex and dynamic data exchange patterns exhibited by the workflows coupled with the varied...
Next generation in-situ/in-transit data processing has been proposed for addressing data challenges at extreme scales. However, further research is necessary in order to understand how growing data sizes from data intensive simulations coupled with limited DRAM capacity in High End Computing clusters will impact the effectiveness of this approach. In this work, we propose using deep memory levels...
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