Abstract: In heterogeneous distributed computing platforms, task execution containers (e.g., Spark executors) often exhibit significant performance variations. However, most task schedulers greedily ...
Abstract: Task scheduling is a classical problem in AI-driven optimization, traditionally tackled using machine learning or heuristic search algorithms. However, most existing methods primarily focus ...
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