Mlog: Multi-log Write Buffer upon Ultra-fast SSD RAID

Wang, Shucheng; Cao, Qiang; Lu, Ziyi; Yao, Jie

doi:10.1145/3545008.3545034

Cited by 2 publications

(1 citation statement)

References 16 publications

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“…SSD RAID has been extensively studied in the literature. Some studies follow traditional disk-based RAID (with in-place updates) [60] and focus on reducing read tail latencies [31], improving parity update performance [27,33,35,40,52], optimizing garbage collection [43,44,69], making I/O performance predictable [50], and enhancing the scalability of Linux software RAID [68,71]. To improve scalability, some studies organize RAID by distributing the controller function to multiple nodes [21] and further reducing the network traffic under disaggregated storage [66].…”

Section: Real-application Experimentsmentioning

confidence: 99%

Identity of university Chinese heritage language learners in Hong Kong

Li¹,

李蓁²

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The core of out-of-distribution (OOD) detection is to learn the in-distribution (ID) representation, which is distinguishable from OOD samples. Previous work applied recognition-based methods to learn the ID features, which tend to learn shortcuts instead of comprehensive representations. In this work, we find surprisingly that simply using reconstruction-based methods could boost the performance of OOD detection significantly. We deeply explore the main contributors of OOD detection and find that reconstructionbased pretext tasks have the potential to provide a generally applicable and efficacious prior, which benefits the model in learning intrinsic data distributions of the ID dataset. Specifically, we take Masked Image Modeling as a pretext task for our OOD detection framework (MOOD). Without bells and whistles, MOOD outperforms previous SOTA of one-class OOD detection by 5.7%, multi-class OOD detection by 3.0%, and near-distribution OOD detection by 2.1%. It even defeats the 10-shot-per-class outlier exposure OOD detection, although we do not include any OOD samples for our detection.

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Section: Real-application Experimentsmentioning

confidence: 99%

Identity of university Chinese heritage language learners in Hong Kong

Li¹,

李蓁²

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Explorations and Exploitation for Parity-based RAIDs with Ultra-fast SSDs

Wang,

Cao,

Jiang

et al. 2024

ACM Trans. Storage

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Following a conventional design principle that pays more fast-CPU-cycles for fewer slow-I/Os, popular software storage architecture Linux Multiple-Disk (MD) for parity-based RAID (e.g., RAID5 and RAID6) assigns one or more centralized worker threads to efficiently process all user requests based on multi-stage asynchronous control and global data structures, successfully exploiting characteristics of slow devices, e.g., Hard Disk Drives (HDDs). However, we observe that, with high-performance NVMe-based Solid State Drives (SSDs), even the recently added multi-worker processing mode in MD achieves only limited performance gain because of the severe lock contentions under intensive write workloads. In this paper, we propose a novel stripe-threaded RAID architecture, StRAID, assigning a dedicated worker thread for each stripe-write (one-for-one model) to sufficiently exploit high parallelism inherent among RAID stripes, multi-core processors, and SSDs. For the notoriously performance-punishing partial-stripe writes that induce extra read and write I/Os, StRAID presents a two-stage stripe write mechanism and a two-dimensional multi-log SSD buffer. All writes first are opportunistically batched in memory, and then are written into the primary RAID for aggregated full-stripe writes or conditionally redirected to the buffer for partial-stripe writes. These buffered data are strategically reclaimed to the primary RAID. We evaluate a StRAID prototype with a variety of benchmarks and real-world traces. StRAID is demonstrated to outperform MD by up to 5.8 times in write throughput.

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Mlog: Multi-log Write Buffer upon Ultra-fast SSD RAID

Cited by 2 publications

References 16 publications

Identity of university Chinese heritage language learners in Hong Kong

Identity of university Chinese heritage language learners in Hong Kong

Explorations and Exploitation for Parity-based RAIDs with Ultra-fast SSDs

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