A Lower Bound for Dynamic Scheduling of Data Parallel Programs
نویسندگان
چکیده
Parallel job scheduling is the problem of how to run a work-load of multiple parallel jobs in a single parallel machine. Dynamic means that the possibility of arbitrary arrival times for new jobs is allowed. The scheduler is responsible for nding the best scheduling allocation, both temporal and spatial, as a function of the existing workload. In this study jobs are assumed to be data parallel with large degrees of paral-lelism, and the machine is assumed to have an MIMD architecture. The dynamic parallel job scheduling is considered here as an optimization problem, and after deening some metrics a theoretical solution is proposed and a lower bound on its complexity is found. Simulation is then used to compare the proposed solution with already existing policies.
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