Search Results (11)

This paper presents an approach that integrates tiered storage into the Log-Structured Merge (LSM)-tree to balance Key–Value Store (KVS) performance and storage financial cost trade-offs. The implementation focuses on applying tiered storage to LSM-tree-based KVS architectures, using both vertical and horizontal storage alignment strategies or a combination of both. Additionally, these configurations leverage key–value (KV) separation to further improve performance. Our experiments reveal that this approach reduces storage financial costs while offering trade-offs in write and read performance. For write-intensive workloads, our approach achieves competitive performance compared to a fast NVMe Solid State Drive (SSD)-only approach while storing 96% of data on more affordable SATA SSDs. Additionally, it exhibits lookup performance comparable to BlobDB, and improves range query performance by 1.8x over RocksDB on NVMe SSDs. Overall, the approach results in a 49.5% reduction in storage financial cost compared to RocksDB and BlobDB on NVMe SSDs. The integration of selective KV separation further advances these improvements, setting the stage for future research into offloading remote data in LSM-tree tiered storage systems. Full article

Today, energy and performance efficiency have become a crucial factor in modern computing environments, such as high-end mobile devices, desktops, and enterprise servers, because data volumes in cloud datacenters increase exponentially. Unfortunately, many researchers and engineers neglect the power consumption and internal performance incurred by storage devices. In this paper, we present a renewable-zoned namespace (ReZNS), an energy and performance-optimal mechanism based on emerging ZNS SSDs. Specifically, ReZNS recycles the remaining capacity of zones that are no longer used by adding a renewable concept into the mapping mechanism. We implemented a prototype of ReZNS based on NVMeVirt and performed comprehensive experiments with diverse workloads from synthetic to real-world workloads to quantitatively confirm power and performance benefits. Our evaluation results present that ReZNS improves overall performance by up to 60% and the total power consumption by up to 3% relative to the baseline on ZNS SSD. We believe ReZNS creates new opportunities to prolong the lifespan of various consumer electronics, such as TV, AV, and mobile devices, because storage devices play a crucial role in their replacement cycle. Full article

Key–value stores (KV stores) are becoming popular in both academia and industry due to their high performance and simplicity in data management. Unlike traditional database systems such as relational databases, KV stores manage data in key–value pairs and do not support relationships between the data. This simplicity enables KV stores to offer higher performance. To further improve the performance of KV stores, high-performance storage devices such as solid-state drives (SSDs) and non-volatile memory express (NVMe) SSDs have been widely adopted. These devices are intended to expedite data processing and storage. However, our studies indicate that, due to a lack of multi-thread-oriented programming, the performance of KV stores is far below the raw performance of high-performance storage devices. In this paper, we analyze the performance of existing KV stores utilizing high-performance storage devices. Our analysis reveals that the actual performance of KV stores is below the potential performance that these storage devices could offer. According to the profiling results, we argue that this performance gap is due to the coarse-grained locking mechanisms of existing KV stores. To alleviate this issue, we propose a multi-threaded compaction operation that leverages idle threads to participate in I/O operations. Our experimental results demonstrate that our scheme can improve the performance of KV stores by up to 16% by increasing the number of threads involved in I/O operations. Full article

Despite the technological achievements of unmanned aerial vehicles (UAVs) growing in academia and industry, there is a lack of studies on the storage devices in UAVs. However, this is an important aspect because the storage devices in UAVs have a limited lifespan and performance and are rarely replaced due to a system-on-chip architecture. In this paper, we study how UAVs impact the lifespan and performance of the underlying storage device while capturing images during overflight. We also propose a new lifespan and performance-saving mechanism, called Delay-D, which is designed at the kernel level to efficiently utilize the features of NAND flash-based storage devices. To confirm the effectiveness of Delay-D, we implement a simulator that replays realistic write patterns on UAVs and evaluate quantitative experiments in two different experimental environments. In our evaluation, Delay-D demonstrates the dramatic extension possibility of the lifespan by reducing the number of extra writes inside the storage device and improving the overall performance by up to 2.1× on the commercial NVMe SSD. Full article

NVMe-over-Fabrics (NVMeoF) is expected to have high-performance and be highly scalable for disaggregating NVMe SSDs to High-Speed Network (HSN)-attached storage servers, thus the aggregated NVMe SSDs in storage servers can be elastically allocated to remote host servers for better utilization. However, due to the well-known connection scalability issue of RDMA NICs (RNICs), RDMA-enabled HSN can only provide a limited scale of performant Queue Pairs (QPs) for NVMeoF I/O queues to transfer capsule and data between the storage server and remote host servers. However, in current NVMeoF implementations, multiplexing multiple NVMeoF I/O queues onto a single RNIC QP is not supported yet. In this paper, we investigate how NVMeoF capsule and data transfers are performed efficiently over HSN with a limited number of RNIC QPs, and propose SPANoF, a Scalable and Performant Architecture for NVMe-over-Fabrics. SPANoF dissolves the intrinsic one-to-one mapping relationship between NVMeoF I/O queues and RNIC QPs, allocates a dedicated send-list for each NVMeoF I/O queue rather than for each RNIC QP, transfers NVMeoF capsules and data in send-lists with a QP-centric manner to remove lock-contention overhead, and polls for transfer completion notifications to remove interrupt-caused context switch overhead. We implemented SPANoF in the Linux kernel and evaluated it by the FIO benchmarks. Our experimental results demonstrate that SPANoF can avoid the performance collapses for commercial RNICs with a limited number of performant QPs and avoid the system crash for domain-specific RNICs with only limited-scale available QPs. Compared with the native NVMeoF implementation in Linux kernel, SPANoF can saturate an RNIC of the storage server with only three RNIC QPs of the remote host server. Compared with lock-based QP-sharing mechanisms, SPANoF improves bandwidth by up to 1.55× under 64 KB sequential write requests, improves throughput by up to 4.18× and reduces the average latency by 28.31% under 4 KB random read requests. Full article

Emerging hardware devices (e.g., NVMe SSD, RISC-V, etc.) open new opportunities for improving the overall performance of computer systems. In addition, the applications try to fully utilize hardware resources to keep up with those improvements. However, these trends can cause significant file system overheads (i.e., fragmentation issues). In this paper, we first study the reason for the fragmentation issues on an F2FS file system and present a new tool, called FragTracer, which helps to analyze the ratio of fragmentation in real-time. For user-friendly usage, we designed FragTracer with three main modules, monitoring, pre-processing, and visualization, which automatically runs without any user intervention. We also optimized FragTracer in terms of performance to hide its overhead in tracking and analyzing fragmentation issues on-the-fly. We evaluated FragTracer with three real-world databases on the F2FS file system, so as to study the fragmentation characteristics caused by databases, and we compared the overhead of FragTracer. Our evaluation results clearly show that the overhead of FragTracer is negligible when running on commodity computing environments. Full article

The Non-Volatile Memory Express (NVMe) SSD provides high I/O performance for current computer systems, and direct memory access (DMA) is the critical enabling mechanism for direct I/O. However, the lengthy I/O stack becomes a new bottleneck that degrades the potential of NVMe SSD. This paper reveals that existing user-level DMA introduces additional overhead for pinning memory used by DMA from the user space. Moreover, it cannot adapt to I/O requests of different data sizes. This paper proposes an efficient and dynamically adaptive user-level DMA (uDMA) mechanism that can adapt to I/O requests for different data sizes and lighten the I/O software stack by amortizing per-request latency. The critical component of uDMA is the pinned memory pool, which avoids frequently pinning new memory blocks by reusing allocated and pinned memory blocks. In addition, it effectively connects the discrete pinned memory blocks by the scatter/gather lists, improving the utilization of the pinned memory pool. Compared with the latest user-level DMA method, uDMA has an improvement of at least 17% under various data sizes. Full article

Virtualization is a core technology for cloud computing, server consolidation and multi-platform support. However, there is a concern regarding performance degradation due to the duplicated I/O stacks virtualization environments. In this paper, we propose a new I/O framework, we refer to it as Direct-Virtio, that manipulates storage directly, which makes it feasible to avoid the duplicated overhead. In addition, we devise two novel mechanisms, called vectored I/O and adaptive polling, to process multiple I/O requests collectively and to check I/O completion efficiently. Real implementation-based evaluation shows that our proposal can enhance performance for both micro and macro benchmarks. Full article

Cloud computing as a service-on-demand architecture has grown in importance over the last few years. The storage subsystem in cloud computing has undergone enormous innovation to provide high-quality cloud services. Emerging Non-Volatile Memory Express (NVMe) technology has attracted considerable attention in cloud computing by delivering high I/O performance in latency and bandwidth. Specifically, multiple NVMe solid-state drives (SSDs) can provide higher performance, fault tolerance, and storage capacity in the cloud computing environment. In this paper, we performed an empirical evaluation study of performance on recent NVMe SSDs (i.e., Intel Optane SSDs) with different redundant array of independent disks (RAID) environments. We analyzed multiple NVMe SSDs with RAID in terms of different performance metrics via synthesis and database benchmarks. We anticipate that our experimental results and performance analysis will have implications for various storage systems. Experimental results showed that the software stack overhead reduced the performance by up to 75%, 52%, 76%, 91%, and 92% in RAID 0, 1, 10, 5, and 6, respectively, compared with theoretical and expected performance. Full article

When processing I/O requests, the current Linux kernel does not adequately consider the urgency of user-centric tasks closely related to user experience. To solve this critical problem, we developed a practical method in this study to enhance user experience in a computing environment wherein non-volatile memory express (NVMe) solid-state drives (SSDs) serve as storage devices. In our proposed scheme, I/O requests that originate from the user-centric tasks were preferentially served across various levels of queues by modifying the multi-queue block I/O layer of the Linux kernel, considering the dispatch method of NVMe SSDs. Our scheme tries to give as fast a path as possible for I/O requests from user-centric tasks among many queues with different levels. Especially, when the SSD is overburdened, it avoids the queues with many pending I/O requests and thus can significantly reduce the I/O latency of user-centric tasks. We implemented our proposed scheme in the Linux kernel and performed practical evaluations on a commercial SSD. The experimental results showed that the proposed scheme achieved significant enhancement in the launch time of five widely used applications by up to ~65%. Full article

Differentiated I/O services for applications with their own requirements are very important for user satisfaction. Nonvolatile memory express (NVMe) solid-state drive (SSD) architecture can improve the I/O bandwidth with its numerous submission queues, but the quality of service (QoS) of each I/O request is never guaranteed. In particular, if many I/O requests are pending in the submission queues due to a bursty I/O workload, urgent I/O requests can be delayed, and consequently, the QoS requirements of applications that need fast service cannot be met. This paper presents a scheme that handles urgent I/O requests without delay even if there are many pending I/O requests. Since the pending I/O requests in the submission queues cannot be controlled by the host, the host memory buffer (HMB), which is part of the DRAM of the host that can be accessed from the controller, is used to process urgent I/O requests. Instead of sending urgent I/O requests into the SSDs through legacy I/O paths, the latency is removed by directly inserting them into the HMB. Emulator experiments demonstrated that the proposed scheme could reduce the average and tail latencies by up to 99% and 86%, respectively. Full article