Memory semantic Solid State Drives (MS-SSDs) provide a promising opportunity to enable the hybrid memory architecture (HMA). The memory semantic interface enables the CPUs to directly access structured data in SSDs and eliminate bulk data copy/swap between the memory and storage devices. However, existing hash indexings issue many random writes, resulting in two problems when directly deployed on MS-SSD-based HMA: 1) Highly random traffic persisted to the underlying NAND flash of MS-SSDs incurs significant garbage collection (GC) overhead. 2) Placing frequently updated memory pages of hash indexings in persistent memories (PMs) is anticipated to reduce write latency, failing to work effectively due to the lack of skewness. To address the above problems, we propose a novel MS-SSD-friendly hash indexing scheme called TieredHM. It employs a multi-layer structure and opportunistic data movement (ODM) to construct skewed writes. Hence, the MS-SSD can transform the writes into multi-streamed writes, separating data with different update frequencies to reduce GC overhead. Besides, since the top layer is updated much more frequently (more skewed) than other layers, placing the top layer of TieredHM into persistent memory can significantly reduce write latency. TieredHM further leverages a prefetch mechanism based on the internal parallelism of NAND flash to reduce search overhead incurred by ODM. Experimental results show that TieredHM reduces the average write latency and GC overhead by up to 8.3X and 20.0X compared to state-of-the-art hash indexings without sacrificing read performance.

NVMe zoned namespace (ZNS) SSDs present a new class of storage devices with attractive features including low cost, software definability, and stable performance. However, one primary culprit that hinders the adoption of ZNS is the high garbage collection (GC) overhead it brings to host software. The ZNS interface divides the logical address space into size-fixed zones that must be written sequentially. Despite being friendly to flash memory, ZNS requires host software to perform out-of-place updates and GC on individual zones. Current ZNS SSDs typically employ a large zone size (e.g., of GBs) to be conducive to die-level RAID protection on flash memory. This impedes flexible data placement, such as mixing data with different lifetimes in the same zone, and incurs sizable data migrations during zone GC. To address this problem, we propose FlexZNS, a novel ZNS SSD design that provides reliable zoned storage allowing host software to configure the zone size flexibly as well as multiple zone sizes. The size variability of zones poses two interrelated challenges, one for the SSD controller to establish per-zone RAID protection, and the other for host software to manage variable zone capacity loss caused by parity storage. To tackle the challenges, FlexZNS decouples the storage of parity from individual zones on flash memory and hides the zone capacity loss from the host software. We verify FlexZNS on a ZNS-compatible file system F2FS and a popular key-value store RocksDB. Extensive experiments demonstrate that FlexZNS can significantly improve the system performance and reduce GC-induced write amplification, compared with a conventional ZNS SSD with large-sized zones.

NAND flash-based Solid State Drives (SSDs) provide a promising opportunity to enable the unified memory-storage hierarchy (UMH). The UMH renders a single memory address space for heterogeneous memories. Thus, the CPUs can directly access structured data in SSDs and eliminate bulk data copy/swap between the memory and storage devices. However, applying traditional indexing structures directly on SSDs may lead to poor performance. Particularly, the popular hash indexing generates highly randomized write traffic, incurring significant garbage collection overhead in SSDs. To address this problem, we propose a novel SSD-friendly hash indexing scheme called Tiered Hashing. It employs a multi-layer structure and opportunistic data movement (ODM) to construct skewed writes. Hence, the SSD can transform the writes into multi-streamed writes, where hot and cold data are separated to reduce GC overhead. Experimental results show Tiered Hashing reduces the average write latency and GC overhead by up to 94.98% and 90.71% compared to state-of-the-art hash indexings, without sacrificing read performance.

In large-scale cloud storage systems, Solid-State Drive (SSD) has been broadly used as the mainstream storage device because it has the advantages of low access latency and high throughput. However, conventional SSD is a black-box system to host softwares, thus failing to fully exploit the benefits of NAND flash and provide high quality of service (QoS). On the other hand, Open-Channel SSD (OCSSD) which exposes its internal information to the host software, has the potential to solve this problem. However, existing OCSSD fails to achieve anticipated performance under heavy workloads. To this end, we propose an advanced OCSSD-based driver developed with the novel data placement policy, redefined garbage collection (GC) with copyback technique, efficient prefetch read scheme, and fast live upgrade method. Our work describes the consistent efforts to pursue high performance and QoS in OCSSDs with different approaches. The evaluation results show that our novel Open-Channel SSD is able to provide high I/O throughputs and predictable I/O latencies. For example, our Open-Channel SSD can improve I/O throughputs by 103% and reduce the 99th percentile latency by 62.9% on average compared with the state-of-the-art NVMe SSDs.