GreenDIMM: OS-assisted DRAM Power Management for DRAM with a Sub-array Granularity Power-Down State
Seunghak Lee, Ki-Dong Kang, Hwanjun Lee, Hyoungwon Park, Younghoon Son, Nam Sung Kim, Daehoon Kim
Abstract
Power and energy consumed by DRAM comprising main memory of data-center servers have increased substantially as the capacity and bandwidth of memory increase. Especially, the fraction of DRAM background power in DRAM total power is already high, and it will continue to increase with the decelerating DRAM technology scaling as we will have to plug more DRAM modules in servers or stack more DRAM dies in a DRAM package to provide necessary DRAM capacity in the future. To reduce the background power, we may exploit low average utilization of the DRAM capacity in data-center servers (i.e., 40–60%) for DRAM power management. Nonetheless, the current DRAM power management supports low-power states only at the rank granularity, which becomes ineffective with memory interleaving techniques devised to disperse memory requests across ranks. That is, ranks need to be frequently woken up from low-power states with aggressive power management, which can significantly degrade system performance, or they do not get a chance to enter low-power states with conservative power management.