Concurrent Scheduling of Parallel Task Graphs on Multi-Clusters Using Constrained Resource Allocations

Scheduling multiple applications on heterogeneous multi-clusters is challenging as the different applications have to compete to access the resources. A scheduler thus has to ensure a fair distribution of the resources among the applications and prevent harmful selfish behaviors while still trying to minimize their respective completion time. In this study we consider mixed-parallel applications, represented by graphs whose nodes are data-parallel tasks, that are scheduled in two steps: allocation and mapping. We investigate several strategies to constrain the amount of resources the scheduler can allocate to each submitted application. This study is then evaluated over a wide range of scenarios