Fantastic SSD internals and how to learn and use them

Li, Nanqinqin; Hao, Mingzhe; Li, Huaicheng; Lin, Xing; Emami, Tim; Gunawi, Haryadi S.

doi:10.1145/3534056.3534940

Cited by 10 publications

(1 citation statement)

References 21 publications

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“…To get a sense of the actual possible values, columns 5 through 10 of Table 2 show parameters of six SSD models we analyzed, including a simulated device that mimics a consumer SSD (Sim), a flash emulator used for our firmware prototyping ("FEMU") [24], an OpenChannel-SSD (OCSSD) [25] whose parameters are publicly known, and three commercial SSDs from different vendors. We used an SSD prober [72] to profile the hardware parameters of the commercial SSDs. Some of the SSD internal parameters are known to be "guessable" based on the observed latencies [73].…”

Section: Tw Examplementioning

confidence: 99%

Extending and Programming the NVMe I/O Determinism Interface for Flash Arrays

Putra

Shi

et al. 2023

ACM Trans. Storage

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Predictable latency on flash storage is a long-pursuit goal, yet, unpredictability stays due to the unavoidable disturbance from many well-known SSD internal activities. To combat this issue, the recent NVMe IO Determinism (IOD) interface advocates host-level controls to SSD internal management tasks. While promising, challenges remain on how to exploit it for truly predictable performance. We present IODA , an I/O deterministic flash array design built on top of small but powerful extensions to the IOD interface for easy deployment. IODA exploits data redundancy in the context of IOD for a strong latency predictability contract. In IODA , SSDs are expected to quickly fail an I/O on purpose to allow predictable I/Os through proactive data reconstruction. In the case of concurrent internal operations, IODA introduces busy remaining time exposure and predictable-latency-window formulation to guarantee predictable data reconstructions. Overall, IODA only adds 5 new fields to the NVMe interface and a small modification in the flash firmware, while keeping most of the complexity in the host OS. Our evaluation shows that IODA improves the 95–99.99þ latencies by up to 75 ×. IODA is also the nearest to the ideal, no disturbance case compared to 7 state-of-the-art preemption, suspension, GC coordination, partitioning, tiny-tail flash controller, prediction, and proactive approaches.

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Section: Tw Examplementioning

confidence: 99%