ThyNVM: Enabling Software-Transparent Crash Consistency in Persistent Memory Systems
Proceedings of the 48th International Symposium on Microarchitecture (MICRO), Waikiki, Hawaii, USA, December 2015.
Jinglei Ren†*, Jishen Zhao‡, Samira Khan†^, Jongmoo Choi^†, Yongwei Wu*, Onur Mutlu†
† Carnegie Mellon University
* Tsinghua University
‡ University of California, Santa Cruz
^ University of Virginia
Emerging byte-addressable nonvolatile memories (NVMs) promise persistent memory, which allows processors to directly access persistent data in main memory. Yet, persistent memory systems need to guarantee a consistent memory state in the event of power loss or a system crash (i.e., crash consistency). To guarantee crash consistency, most prior works rely on programmers to (1) partition persistent and transient memory data and (2) use specialized software interfaces when updating persistent memory data. As a result, taking advantage of persistent memory requires significant programmer effort, e.g., to implement new programs as well as modify legacy programs. Use cases and adoption of persistent memory can therefore be largely limited.
In this paper, we propose a hardware-assisted DRAM+NVM hybrid persistent memory design, Transparent Hybrid NVM (ThyNVM), which supports software-transparent crash consistency of memory data in a hybrid memory system. To efficiently enforce crash consistency, we design a new dual-scheme checkpointing mechanism, which efficiently overlaps checkpointing time with application execution time. The key novelty is to enable checkpointing of data at multiple granularities, cache block or page granularity, in a coordinated manner. This design is based on our insight that there is a tradeoff between the application stall time due to checkpointing and the hardware storage overhead of the metadata for checkpointing, both of which are dictated by the granularity of checkpointed data. To get the best of the tradeoff, our technique adapts the checkpointing granularity to the write locality characteristics of the data and coordinates the management of multiple-granularity updates. Our evaluation across a variety of applications shows that ThyNVM performs within 4.9% of an idealized DRAM-only system that can provide crash consistency at no cost.
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