Dual-Page Checkpointing: An Architectural Approach to Efficient Data Persistence for In-Memory Applications.

Data persistence is necessary for many in-memory applications. However, the disk-based data persistence largely slows down in-memory applications. Emerging non-volatile memory (NVM) offers an opportunity to achieve in-memory data persistence at the DRAM-level performance. Nevertheless, NVM typically requires a software library to operate NVM data, which brings significant overhead. This article demonstrates that a hardware-based high-frequency checkpointing mechanism can be used to achieve efficient in-memory data persistence on NVM. To maintain checkpoint consistency, traditional logging and copy-on-write techniques incur excessive NVM writes that impair both performance and endurance of NVM; recent work attempts to solve the issue but requires a large amount of metadata in the memory controller. Hence, we design a new dual-page checkpointing system, which achieves low metadata cost and eliminates most excessive NVM writes at the same time. It breaks the traditional trade-off between metadata space cost and extra data writes. Our solution outperforms the state-of-the-art NVM software libraries by 13.6× in throughput, and leads to 34% less NVM wear-out and 1.28× higher throughput than state-of-the-art hardware checkpointing solutions, according to our evaluation with OLTP, graph computing, and machine-learning workloads.