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Current shared-memory multiprocessor CC-NUMA architectures provide a global address space to applications by hardware. However, even though the memory is virtually shared, it is actually physically distributed. Since memory nodes are distributed across the system, the cost of the memory accesses depends on the distance between the node that accesses the data and the node that physically contains the data. To reduce the impact of a bad initial memory placement, some operating systems offer a dynamic memory migration mechanism.In this paper, we want to demonstrate that memory migration mechanisms are a useful approach, but that their performance depends more on related issues, such as the processor scheduling, than on the mechanism itself. To show that, we evaluate the case of the automatic memory migration mechanism provided by IRIX, in Origin systems.We have evaluated several workloads of OpenMP applications under different system conditions such as the processor scheduling policy or the system load. In particular, we have focused on the effects of the page migration mechanism on the CPU time consumed by each application, the processor allocation received, and the speedup, when applying performance-driven scheduling policies.Results show that, if the scheduler is memory conscious, that is, it maintains as much as possible the system stable, the automatic memory page migration mechanism provided by IRIX will improve the execution time of OpenMPapplications. Experiments also show that the combination of performance-driven policies and the memory migration mechanism results in a system that can be automatically self-evaluated and self-configured.