Adaptive hardware configuration for data analytics
Abstract:
A computer-implemented method uses a predictive time-sequence model to adapt hardware configurations at run-time for an application including multiple stages of execution. At each stage a system monitor is started at the launch of a first task in a first run to collect performance data. The system monitor is stopped at the completion of a last task in the first run, then a predictive optimal configuration is computed and applied to the remaining runs in the stage.
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