Processor virtualization allows concurrent operating system execution environments to co-exist and share a fixed set of hardware resources. One of its many advantages is that this technology facilitates server consolidation, reducing both operating costs and power consumption. However, virtualization incurs a performance penalty due to added complexity and the conflicts arising from sharing a fixed set of hardware resources. It is important to identify and understand the sources of the overheads in order to guide tuning/optimization efforts to reduce these performance costs. In this paper, the authors outline and use a performance evaluation framework and methodology that uses sampled event traces to identify and understand the virtualization overheads with respect to the memory subsystem performance.
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