An Empirical Evaluation and Analysis of Performance of Multiple Optane SSDs

Han, Jaehyun; Zhu, Guangyu; Lee, Eunseo; Lee, Sang-Mook; Son, Younghwan

doi:10.1109/icoin50884.2021.9333865

Cited by 4 publications

(5 citation statements)

References 21 publications

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“…Together, they form a SSD cluster and are managed by the Ceph file system, ready to process read and write requests sent by clients. The rationales of conducting performance evaluation on clusters with the aforementioned configuration are as follows: We follow previous works 23,38 to choose a SSD cluster with a relatively small size as the tested, which consists of less than eight nodes, each having less than five SSDs. Hence, our hardware configuration is comparable. The SSD cluster we utilised during experiments is representative to process moderate I/O requests in a production environment, 39 hence the results produced by the experiments are persuasive.…”

Section: Methodsmentioning

confidence: 99%

“…In each client, the popular disk pressure testing tool Fio 40 is used to generate workloads and send it from the client to the SSD cluster. The Fio 40, 41,42 is a popular open-sourced benchmarking tool that has been used to evaluate the performance of SSDs 43,38 . It simulates a given I/O workload by spawning a number of threads or processes doing a particular type of I/O action as specified by the user.…”

Section: Benchmarkingmentioning

confidence: 99%

“…1. We follow previous works 23,38 to choose a SSD cluster with a relatively small size as the tested, which consists of less than eight nodes, each having less than five SSDs. Hence, our hardware configuration is comparable.…”

Section: Hardware and File System Configurationmentioning

confidence: 99%

“…The Fio [40][41][42] is a popular open-sourced benchmarking tool that has been used to evaluate the performance of SSDs. 38,43 The size of the workload we used during our experiments is set to 32 GB that simulates the workload of a normal production environment, rather than applying the unrealistic pre-conditioning workload that represents worst-case scenarios. 27 The following settings are adjusted:…”

Section: Benchmarkingmentioning

confidence: 99%

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How does solid‐state drives cluster perform for distributed file systems: An empirical study

Wang

et al. 2023

Concurrency and Computation

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As the capacity of Solid-State Drives (SSDs) is constantly being optimised and boosted with gradually reduced cost, the SSD cluster is now widely deployed as part of the hybrid storage system in various scenarios such as cloud computing and big data processing. However, despite its rapid developments, the performance of the SSD cluster remains largely under-investigated, leaving its sub-optimal applications in reality. To address this issue, in this paper we conduct extensive empirical studies for a comprehensive understanding of the SSD cluster in diverse settings. To this end, we configure a real SSD cluster and gather the generated trace data based on some often-used benchmarks, then adopt analytical methods to analyse the performance of the SSD cluster with different configurations. In particular, regression models are built to provide better performance predictability under broader configurations, and the correlations between influential factors and performance metrics with respect to different numbers of nodes are investigated, which reveal the high scalability of the SSD cluster. Additionally, the cluster's network bandwidth is inspected to explain the performance bottleneck. Finally, the knowledge gained is summarised to benefit the SSD cluster deployment in practice.

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Section: Methodsmentioning

confidence: 99%

Section: Benchmarkingmentioning

confidence: 99%

Section: Hardware and File System Configurationmentioning

confidence: 99%

Section: Benchmarkingmentioning

confidence: 99%

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How does solid‐state drives cluster perform for distributed file systems: An empirical study

Wang

et al. 2023

Concurrency and Computation

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“…By doing so, we identified software bottlenecks that were exposed by the rapid storage growth. (This article is an extended version of our paper published in the International Conference on Information Networking (ICOIN'21) in January 2021 [10]. )…”

Section: Introductionmentioning

confidence: 99%

An Empirical Performance Evaluation of Multiple Intel Optane Solid-State Drives

et al. 2021

Self Cite

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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.

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