Synergistic coupling of SSD and hard disk for QoS-aware virtual memory


With significant advantages in capacity, power consumption, and price, solid state disk (SSD) has good potential to be employed as an extension of DRAM (memory), such that applications with large working sets could run efficiently on a modestly configured system. While initial results reported in recent works show promising prospects for this use of SSD by incorporating it into the management of virtual memory, frequent writes from write-intensive programs could quickly wear out SSD, making the idea less practical. We propose a scheme, HybridSwap, that integrates a hard disk with an SSD for virtual memory management, synergistically achieving the advantages of both. In addition, HybridSwap can constrain performance loss caused by swapping according to user-specified QoS requirements. To minimize writes to the SSD without undue performance loss, HybridSwap sequentially swaps a set of pages of virtual memory to the hard disk if they are expected to be read together. Using a history of page access patterns HybridSwap dynamically creates an out-of-memory virtual memory page layout on the swap space spanning the SSD and hard disk such that random reads are served by SSD and sequential reads are asynchronously served by the hard disk with high efficiency. In practice HybridSwap can effectively exploit the aggregate bandwidth of the two devices to accelerate page swapping. We have implemented HybridSwap in a recent Linux kernel, version Our evaluation with representative benchmarks, such as Memcached for key-value store, and scientific programs from the ALGLIB cross-platform numerical analysis and data processing library, shows that the number of writes to SSD can be reduced by 40% with the system's performance comparable to that with pure SSD swapping, and can satisfy a swapping-related QoS requirement as long as

DOI: 10.1109/ISPASS.2013.6557143

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@article{Liu2013SynergisticCO, title={Synergistic coupling of SSD and hard disk for QoS-aware virtual memory}, author={Ke Liu and Xuechen Zhang and Kei Davis and Song Jiang}, journal={2013 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)}, year={2013}, pages={24-33} }