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Graph partitioning is a key problem to enable efficient solving of a wide range of computational tasks and querying over large-scale graph data, such as computing node centralities using iterative ...

Which Linux distributions will rise above the competition in 2026 to dethrone the old guard? These are my picks.

Abstract: EdgeAI represents a compelling approach for deploying DNN models at network edge through model partitioning. However, most existing partitioning strategies have primarily concentrated on ...

Abstract: As dynamic graph data have been actively used, incremental graph partition schemes have been studied to efficiently store and manage large graphs. In this paper, we propose a vertex-cut ...