A Memory Allocation Framework for Optimizing Power Consumption and Controlling Fragmentation

Large physical memory modules are necessary to meet performance demands of today's ap- plications but can be a major bottleneck in terms of power consumption during idle periods or when systems are running with workloads which do not stress all the plugged memory resources. Contribution of physical memory in overall system power consumption becomes even more signi cant when CPU cores run on low power modes during idle periods with hardware support like Dynamic Voltage Frequency Scaling. Our experiments show that even 10% of memory allocations can make references to all the banks of physical memory on a long running system primarily due to the randomness in page allocation. We also show that memory hot-remove or memory migration for large blocks is often restricted, in a long running system, due to allocation policies of current Linux VM which mixes movable and unmovable pages. Hence it is crucial to improve page migration for large contiguous blocks for a practical realization of power management support provided by the hardware. Operating systems can play a decisive role in effectively utilizing the power management support of modern DIMMs like PASR(Partial Array Self Refresh) in these situations but have not been using them so far. We propose three different approaches for optimizing memory power consumption by in- ducing bank boundary awareness in the standard buddy allocator of Linux kernel as well as distinguishing user and kernel memory allocations at the same time to improve the movability of memory sections (and hence memory-hotplug) by page migration techniques. Through a set of minimal changes in the standard buddy system of Linux VM, we have been able to reduce the number of active memory banks significantly (upto 80%) as well as to improve performance of memory-hotplug framework (upto 85%)