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8 Conclusion and Future Work

Due to better processing technology and a highly competitive market, systems are equipped with bigger-capacity and higher-performance main memory as workloads are becoming more data-centric. As a result, power dissipated by the memory is becoming increasingly significant. In this paper, we have presented the design and analysis of power-aware virtual memory (PAVM) to reduce total memory energy expenditure by managing power states of individual memory nodes. We have also shown a working implementation of PAVM in the Linux kernel, and described how it was later evolved to handle complex memory sharing among multiple processes and between processes and the kernel in a modern operating system.

By performing extensive experiments with real applications, we are able to show that even with a rudimentary version of PAVM, we can save 34-89% of the energy normally consumed in a 16-device RDRAM memory configuration. By applying more advanced techniques such as DLL aggregation and page migration in PAVM, we are able to reduce energy dissipation by an additional 25-50%. We have also shown the applicability of this approach for other SDRAM architectures such as DDR and SDR, which can also benefit greatly under PAVM.

We have used a NUMA abstraction to organize and manage memory in our PAVM implementation, and have borrowed some NUMA concepts such as the notion of a node and the page-migration technique. In the future, we would like to explore if other NUMA techniques, such as page replication, can be effective in the context of energy conservation. In addition, we would also like to investigate the interactions between OS-controlled and hardware-implemented power-management policies to further decrease energy consumption of memory.

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