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Titlebook: Supercomputing; 6th Russian Supercom Vladimir Voevodin,Sergey Sobolev Conference proceedings 2020 Springer Nature Switzerland AG 2020 cloud

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發(fā)表于 2025-3-28 15:22:16 | 只看該作者
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發(fā)表于 2025-3-29 02:35:45 | 只看該作者
Application of Supercomputing Technologies for Numerical Implementation of an Interaction Graph Modevity. Based on it, the analysis of pulse propagation in computing environment from the vertices is performed in the context of research situation of valuable fish degradation of the Azov Sea that are subject to excessive commercial fishing withdrawal. The model takes into account the convective tran
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發(fā)表于 2025-3-29 05:59:58 | 只看該作者
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發(fā)表于 2025-3-29 07:17:30 | 只看該作者
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發(fā)表于 2025-3-29 14:42:10 | 只看該作者
New Compact Streaming in LBM with ConeFold LRnLA Algorithmse model. It is implemented with the ConeFold LRnLA algorithm so that the operational intensity is increased further. The compactness of the streaming allows for more asynchrony in multidimensional LRnLA decomposition. The obtained one desktop CPU performance reaches 1 billion cell updates per second.
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發(fā)表于 2025-3-29 16:11:03 | 只看該作者
Developing Efficient Implementation of Label Propagation Algorithm for Modern NVIDIA GPUssing, efficient load-balancing, using unified memory for out-of-core graph processing, and several others. The performance of the developed implementation has been evaluated on synthetic and medium-scaled real-world graphs, resulting in up?to 2 times better results compared to existing approaches.
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發(fā)表于 2025-3-29 22:45:42 | 只看該作者
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發(fā)表于 2025-3-30 03:10:37 | 只看該作者
Optimization of Load Balancing Algorithms in Parallel Modeling of Objects Using a Large Number of Gr of the algorithms, an elastic wave propagation model in a medium with many non-parallel cracks will be used..Modeling with using of researched algorithms was carried out on the “Kurchatov Data Processing Center” programming complex, which is part of the “Kurchatov Institute” National Research Center.
50#
發(fā)表于 2025-3-30 07:09:12 | 只看該作者
A Visual-Based Approach for Evaluating Global Optimization Methodsst optimization problems is considered including a new global constrained optimization problem generator (GCGen). Main performance measures and comparative criteria of efficiency are presented. The ways of visual presentation of computational results are suggested.
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