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Power and energy consumed by main memory systems in data-center servers have increased as the DRAM capacity and bandwidth increase. Particularly, background power accounts for a considerable fraction of the total DRAM power consumption; the fraction will increase further in the near future, especially when slowing-down technology scaling forces us to provide necessary DRAM capacity through plugging in more DRAM modules or stacking more DRAM chips in a DRAM package. Although current DRAM architecture supports low power states at rank granularity that turn off some components during idle periods, techniques to exploit memory-level parallelism make the rank-granularity power state become ineffective. Furthermore, the long wake-up latency is one of obstacles to adopting aggressive power management (PM) with deep power-down states. By tackling the limitations, we propose OffDIMM that is a software-assisted DRAM PM collaborating with the OS-level memory onlining/offlining. OffDIMM maps a memory block in the address space of the OS to a subarray group or groups of DRAM, and sets a deep power-down state for the subarray group when offlining the block. Through the dynamic OS-level memory onlining/offlining based on the current memory usage, our experimental results show OffDIMM reduces background power by 24 percent on average without notable performance overheads. © 2002-2011 IEEE.
더보기Department of Electrical Engineering and Computer Science