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Architecture exploration for embedded systems is becoming an indispensable tool for System-on-Chip designers. This process requires the evaluation of many architectures that are generated during the exploration process. The evaluation process has a significant impact on the quality of the results and could consume a substantial amount of CPU time. Accordingly, the evaluation process should provide...
In this paper we present a system for online power prediction in vir-tualized environments. It is based on Gaussian mixture models that use architectural metrics of the physical and virtual machines (VM) collected dynamically by our system to predict both the physical machine and per VM level power consumption. A real implementation of our system shows that it can achieve average prediction error...
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