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PACMan: Coordinated Memory Caching for Parallel Jobs.
Carefully scheduling parallel jobs is essential for cloud providers to maintain their quality of service.
And this month he moved eight of 55 department managers into parallel jobs.
Simulation results demonstrate that our proposed On-Demand scheduling algorithm can significantly reduce the response time of parallel jobs.
The implications of our findings are the accelerated completion and improved reliability of parallel jobs executed across large distributed systems.
In modern parallel systems and distributed applications, a large number of cores work synergistically for parallel jobs.
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Where the task involves repeating a subtask a certain number of times, we can parallelize up to the extent where we have one repeat per parallel job.
This environment provides finer control of the parallel job execution, including the capability of job cancellation.
It clearly outperforms the other power-budgeting approaches at the parallel job scheduling level.
The available number of processors is not anymore the only limitation in parallel job scheduling.
We proposed MaxJobPerf, a new parallel job scheduling policy based on integer linear programming.
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