Memory Energy Management Using Software and Hardware Directed Power Mode Control

The anticipated explosive growth of pervasive and mobile computing devices that are typically constrained by energy has brought hardware and software techniques for energy conservation into the spotlight. While there have been several studies and proposals for energy conservation for CPUs and peripherals, energy optimization techniques for selective operating mode control of DRAMs have not been fully explored. It has been shown that as much as 90% of overall system energy (excluding I/O) is consumed by the DRAM modules, serving as a good candidate for energy optimizations. Further, DRAM technology has also matured to provide several low energy operating modes (power modes), making it an opportunistic moment to conduct studies exploring the potential benefits of mode control techniques. This paper conducts an in-depth investigation of software and hardware techniques to avail of the DRAM mode control capabilities at a module granularity for energy savings. Using a memory system architecture capturing five different energy modes and corresponding resynchronization times, this paper presents several novel compilation techniques to both cluster the data across memory banks as well as to detect module idleness and perform energy mode transitions. In addition, hardware-assisted approaches (called self-monitoring) based on predictions of module inter-access times are proposed. These techniques are extensively evaluated using a set of a dozen benchmarks. It is shown that we get an average of 61% savings in main memory energy using compiler-directed mode control. One of the self-monitored approaches gives as much as 89% savings ( 72% on the average), coming as close as 8.8% to the optimal energy savings that one can ever hope to get with memory module mode control. The optimization techniques are demonstrated to be invaluable for energy savings as memory technologies continue to evolve as well.