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This paper presents SMARTPARTITION, an efficient approach to partition large-scala natural graphs [5]. We design a new partitioning algorithm which can perceive graph layout locality to improve the performance of graph computation. Experimental results demonstrate that SMARTPARTITION can achieve significant reduction in ingress time and execution time for both real-world and synthetic graph datasets.
With the help of simulation tools, users can evaluate new proposals in cluster environment efficiently. However, current cloud simulators cannot meet the needs of application-driven simulation scenarios. In this paper, we propose Pallas, a task and network simulation framework that supports various cloud applications. Task-aware network scheduling and network-perceived task placement algorithms can...
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