New non-volatile memory (NVM) technologies enable direct, durable storage of data in an application's heap. Durable, randomly accessible memory facilitates the construction of applications that do not lose data at system shutdown or power failure. Existing NVM programming frameworks provide mechanisms to consistently capture a running application's state. They do not, however, fully support object-oriented languages or ensure that the persistent heap is consistent with the environment when the application is restarted. In this paper, we propose a new NVM language extension and runtime system that supports objectoriented NVM programming and avoids the pitfalls of prior approaches. At the heart of our technique is object reconstruction, which transparently restores and reconstructs a persistent object's state during program restart. It is implemented in NVMReconstruction, a Clang/LLVM extension and runtime library that provides: (i) transient fields in persistent objects, (ii) support for virtual functions and function pointers, (iii) direct representation of persistent pointers as virtual addresses, and (iv) type-specific reconstruction of a persistent object during program restart. In addition, NVMReconstruction supports updating an application's code, even if this causes objects to expand, by providing object migration. NVMReconstruction also can compact the persistent heap to reduce fragmentation. In experiments, we demonstrate the versatility and usability of object reconstruction and its low runtime performance cost.

Non-Volatile Memory offers the possibility of implementing high-performance, durable data structures. However, achieving performance comparable to well-designed data structures in non-persistent (transient) memory is difficult, primarily because of the cost of ensuring the order in which memory writes reach NVM. Often, this requires flushing data to NVM and waiting a full memory round-trip time.In this paper, we introduce two new techniques: Fine-Grained Checkpointing, which ensures a consistent, quickly recoverable data structure in NVM after a system failure, and In-Cache-Line Logging, an undo-logging technique that enables recovery of earlier state without requiring cacheline flushes in the normal case. We implemented these techniques in the Masstree data structure, making it persistent and demonstrating the ease of applying them to a highly optimized system and their low (5.9-15.4%) runtime overhead cost.

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