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An opportunity cost approach for job assignment in a scalable computing cluster

机译:在可扩展计算集群中分配工作的机会成本方法

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A new method is presented for job assignment to and reassignment between machines in a computing cluster. Our method is based on a theoretical framework that has been experimentally tested and shown to be useful in practice. This "opportunity cost" method converts the usage of several heterogeneous resources in a machine to a single homogeneous "cost." Assignment and reassignment are then performed based on that cost. This is in contrast to traditional, ad hoc methods for job assignment and reassignment. These treated each resource as an independent entity with its own constraints, as there was no clean way to balance one resource against another. Our method has been tested by simulations, as well as real executions, and was found to perform well.
机译:提出了一种新的方法,用于在计算集群中对计算机进行作业分配和重新分配。我们的方法基于经过实验测试的理论框架,并在实践中证明是有用的。这种“机会成本”方法将机器中几种异构资源的使用转换为单一的同质“成本”。然后根据该成本执行分配和重新分配。这与用于作业分配和重新分配的传统的临时方法相反。这些人将每种资源视为具有其自身约束的独立实体,因为没有一种干净的方法来平衡一种资源与另一种资源。我们的方法已经通过仿真以及实际执行进行了测试,并被证明性能良好。

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