We present Dinomo, a novel key-value store for disaggregated persistent memory (DPM). Dinomo is the first key-value store for DPM that simultaneously achieves high common-case performance, scalability, and lightweight online reconfiguration. We observe that previously proposed key-value stores for DPM had architectural limitations that prevent them from achieving all three goals simultaneously. Dinomo uses a novel combination of techniques such as ownership partitioning, disaggregated adaptive caching, selective replication, and lock-free and log-free indexing to achieve these goals. Compared to a state-of-the-art DPM key-value store, Dinomo achieves at least 3.8X better throughput at scale on various workloads and higher scalability, while providing fast reconfiguration.

We present SplitFS, a file system for persistent memory (PM) that reduces software overhead significantly compared to state-of-the-art PM file systems. SplitFS presents a novel split of responsibilities between a user-space library file system and an existing kernel PM file system. The user-space library file system handles data operations by intercepting POSIX calls, memory-mapping the underlying file, and serving the read and overwrites using processor loads and stores. Metadata operations are handled by the kernel PM file system (ext4 DAX). SplitFS introduces a new primitive termed relink to efficiently support file appends and atomic data operations. SplitFS provides three consistency modes, which different applications can choose from, without interfering with each other. SplitFS reduces software overhead by up-to 4x compared to the NOVA PM file system, and 17x compared to ext4 DAX. On a number of micro-benchmarks and applications such as the LevelDB key-value store running the YCSB benchmark, SplitFS increases application performance by up to 2x compared to ext4 DAX and NOVA while providing similar consistency guarantees.

We present Recipe, a principled approach for converting concurrent DRAM indexes into crash-consistent indexes for persistent memory (PM). The main insight behind Recipe is that isolation provided by a certain class of concurrent in-memory indexes can be translated with small changes to crash-consistency when the same index is used in PM. We present a set of conditions that enable the identification of this class of DRAM indexes, and the actions to be taken to convert each index to be persistent. Based on these conditions and conversion actions, we modify five different DRAM indexes based on B+ trees, tries, radix trees, and hash tables to their crash-consistent PM counterparts. The effort involved in this conversion is minimal, requiring 30--200 lines of code. We evaluated the converted PM indexes on Intel DC Persistent Memory, and found that they outperform state-of-the-art, hand-crafted PM indexes in multi-threaded workloads by up-to 5.2x. For example, we built P-CLHT, our PM implementation of the CLHT hash table by modifying only 30 LOC. When running YCSB workloads, P-CLHT performs up to 2.4x better than Cacheline-Conscious Extendible Hashing (CCEH), the state-of-the-art PM hash table.

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This paper presents iDO, a compiler-directed approach to failure atomicity with nonvolatile memory. Unlike most prior work, which instruments each store of persistent data for redo or undo logging, the iDO compiler identifies idempotent instruction sequences, whose re-execution is guaranteed to be side-effect-free, thereby eliminating the need to log every persistent store. Using an extension of prior work on JUSTDO logging, the compiler then arranges, during recovery from failure, to back up each thread to the beginning of the current idempotent region and re-execute to the end of the current failure-atomic section. This extension transforms JUSTDO logging from a technique of value only on hypothetical future machines with nonvolatile caches into a technique that also significantly outperforms state-of-the art lock-based persistence mechanisms on current hardware during normal execution, while preserving very fast recovery times.

The advent of Persistent Memory (PM), which is anticipated to have byte-addressable access latency in par with DRAM and yet nonvolatile, has stepped up interest in using PM as storage. Hence, PM storage targeted file systems are being developed under the premise that legacy file systems are suboptimal on memory bus attached PM-based storage. However, many years of time and effort are ingrained in legacy file systems that are now time-tested and mature. Simply scrapping them altogether may be unwarranted. In this paper, we look into how we can leverage the maturity ingrained in legacy file systems to the fullest, while, at the same time, reaping the high performance offered by PM. To this end, we first go through a thorough analysis of legacy Ext4 file systems, and compare it with NOVA, PMFS, and Ext4 with DAX extension, which are new PM file systems available in Linux. Based on these analyses, we then propose the Persistent Memory Adaptation Layer (PMAL) module that is lightweight (roughly 180 LoC) and can easily be integrated into legacy file systems to take advantage of PM storage. Using Ext4, we show that the performance of PMAL integrated Ext4 is in par with PM file systems for the Filebench and key-value store benchmarks.