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 ...

Within each content area, there are one or more tutorials. Each tutorial consists of lessons. Each lesson should be a page detailing the concept being taught, along with sample code. Lesson and page ...

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 ...