Titlebook: Job Scheduling Strategies for Parallel Processing; 13th International W Eitan Frachtenberg,Uwe Schwiegelshohn Conference proceedings 2008 S

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多骨

Avi Nissimov,Dror G. Feitelsonat the DSS models lacked in comprehensive problem representation was more than compensated for by the ease with which they could be run under alternative assumptions. The popularity of PCs at the managerial level and the development of friendly, generic software over the following decade greatly fac

FLING

Martin W. Margo,Kenneth Yoshimoto,Patricia Kovatch,Phil Andrewsat the DSS models lacked in comprehensive problem representation was more than compensated for by the ease with which they could be run under alternative assumptions. The popularity of PCs at the managerial level and the development of friendly, generic software over the following decade greatly fac

Ordnance

交響樂(lè)

A Job Self-scheduling Policy for HPC Infrastructures,niques for dispatching the jobs that are submitted to a set of distributed computational hosts that are managed by independent schedulers (such as MOAB or LoadLeveler). It is a non-centralized and job-guided scheduling policy whose main goal is to optimize the job wait time. Thus, the scheduling dec

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considerable

Impact of Reservations on Production Job Scheduling,equest data to investigate different scheduling scenarios. We explored the effect of reservations and policies using job log data from two different months within consecutive years and present our initial results. Results from the simulations suggest that utilization, expansion factor and queue wait

煩擾

A Self-optimized Job Scheduler for Heterogeneous Server Clusters,s based on the Reinforcement Learning paradigm; it learns its estimation policy on-line and dynamically modifies it according to the overall cluster load. The paper includes simulation results which indicate that our algorithm can yield an improvement of over 30% in utilization (overall throughput)

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