What question did this study set out to answer?

The research aims to address persisting tail latency in storage systems, particularly in SSDs and HDDs.

March 22, 2026ACM Transactions on Design Automation of Electronic Systems

LatVision: Attention-Driven Dual-Layer Prediction Model for Persisting Tail Latency in SSDs and HDDs

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The research aims to address persisting tail latency in storage systems, particularly in SSDs and HDDs.
Introduced LatVision, a dual-layer prediction model integrating attention mechanisms.
Leveraged eBPF for capturing I/O performance metrics at the OS kernel level.
Employed a two-layer detection pipeline for latency prediction.
Achieved prediction accuracy exceeding 90% across various SSD and HDD configurations.
Reduced computational overhead by 75.3% compared to traditional models.
Improved stability under diverse workload conditions using heuristic algorithm integration.

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Implication

LatVision demonstrates real-time, high-precision prediction accuracy for tail latency in SSDs and HDDs, indicating enhanced operational stability with heuristic algorithms.

Cite This Study

Bai et al. (2026) studied this question.

synapsesocial.com/papers/69bf3955c7b3c90b18b43d8f https://doi.org/10.1145/3800950

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Implication

LatVision demonstrates real-time, high-precision prediction accuracy for tail latency in SSDs and HDDs, indicating enhanced operational stability with heuristic algorithms.

LatVision: Attention-Driven Dual-Layer Prediction Model for Persisting Tail Latency in SSDs and HDDs

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Discussion

Implication

Cite This Study

LatVision: Attention-Driven Dual-Layer Prediction Model for Persisting Tail Latency in SSDs and HDDs

Key Points

Discussion

Implication

Cite This Study

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