DINOMO: An Elastic, Scalable, High-Performance Key-Value Store for Disaggregated Persistent Memory (Extended Version)

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 on various workloads at scale and higher scalability, while providing fast reconfiguration.Comment: This is an extended version of the full paper to appear in PVLDB 15.13 (VLDB 2023

CRAID: Online RAID upgrades using dynamic hot data reorganization

Current algorithms used to upgrade RAID arrays typically require large amounts of data to be migrated, even those that move only the minimum amount of data required to keep a balanced data load. This paper presents CRAID, a self-optimizing RAID array that performs an online block reorganization of frequently used, long-term accessed data in order to reduce this migration even further. To achieve this objective, CRAID tracks frequently used, long-term data blocks and copies them to a dedicated partition spread across all the disks in the array. When new disks are added, CRAID only needs to extend this process to the new devices to redistribute this partition, thus greatly reducing the overhead of the upgrade process. In addition, the reorganized access patterns within this partition improve the array’s performance, amortizing the copy overhead and allowing CRAID to offer a performance competitive with traditional RAIDs. We describe CRAID’s motivation and design and we evaluate it by replaying seven real-world workloads including a file server, a web server and a user share. Our experiments show that CRAID can successfully detect hot data variations and begin using new disks as soon as they are added to the array. Also, the usage of a dedicated partition improves the sequentiality of relevant data access, which amortizes the cost of reorganizations. Finally, we prove that a full-HDD CRAID array with a small distributed partition (<1.28% per disk) can compete in performance with an ideally restriped RAID-5 and a hybrid RAID-5 with a small SSD cache.Peer ReviewedPostprint (published version

Understanding (Un)Written Contracts of NVMe ZNS Devices with zns-tools

Operational and performance characteristics of flash SSDs have long been associated with a set of Unwritten Contracts due to their hidden, complex internals and lack of control from the host software stack. These unwritten contracts govern how data should be stored, accessed, and garbage collected. The emergence of Zoned Namespace (ZNS) flash devices with their open and standardized interface allows us to write these unwritten contracts for the storage stack. However, even with a standardized storage-host interface, due to the lack of appropriate end-to-end operational data collection tools, the quantification and reasoning of such contracts remain a challenge. In this paper, we propose zns.tools, an open-source framework for end-to-end event and metadata collection, analysis, and visualization for the ZNS SSDs contract analysis. We showcase how zns.tools can be used to understand how the combination of RocksDB with the F2FS file system interacts with the underlying storage. Our tools are available openly at \url{https://github.com/stonet-research/zns-tools}