86,770 research outputs found

    A CUDA-based implementation of an improved SPH method on GPU

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    We present a CUDA-based parallel implementation on GPU architecture of a modified version of the Smoothed Particle Hydrodynamics (SPH) method. This modified formulation exploits a strategy based on the Taylor series expansion, which simultaneously improves the approximation of a function and its derivatives with respect to the standard formulation. The improvement in accuracy comes at the cost of an additional computational effort. The computational demand becomes increasingly crucial as problem size increases but can be addressed by employing fast summations in a parallel computational scheme. The experimental analysis showed that our parallel implementation significantly reduces the runtime, with speed-ups of up to 90,when compared to the CPU-based implementation

    A Framework for the Development and Monitoring of Digital Control in Power Converters

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    The design of advanced digital controllers for power converters requires dedicated hardware which may result in increased complexity and development time. As the number of control variables increases, operations such as monitoring, debugging, testing and optimization become more difficult. The paper presents a methodology and a prototype of a system that have facilitated non-invasive monitoring of the controller of power converter in real-time and performing more effective automated tests. This has been achieved by leveraging the tremendous reconfigurability of modern System-on-Chip (SoC) devices that integrate both Field Programmable Gate Arrays (FPGA) and high-performance standard Hard Processor System (HPS) in one package with built-in, programmable interconnects. In this proposed architecture, FPGA section implements digital controller and HPS handles monitoring and interfacing for remote supervision by re-using standard Linux system libraries. The monitoring system sets the controller parameters, collects all internal controller signals and organizes them. It provides an interface through ethernet for external data processing environments such as MATLA

    An Efficient Data Aggregation Algorithm for Cluster-based Sensor Network

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    Data aggregation in wireless sensor networks eliminates redundancy to improve bandwidth utilization and energy-efficiency of sensor nodes. One node, called the cluster leader, collects data from surrounding nodes and then sends the summarized information to upstream nodes. In this paper, we propose an algorithm to select a cluster leader that will perform data aggregation in a partially connected sensor network. The algorithm reduces the traffic flow inside the network by adaptively selecting the shortest route for packet routing to the cluster leader. We also describe a simulation framework for functional analysis of WSN applications taking our proposed algorithm as an exampl
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