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LinnOS - Predictability on Unpredictable Flash Storage with a Light Neural Network

USENIX via YouTube

Overview

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Explore a groundbreaking conference talk on LinnOS, an operating system that employs a light neural network to predict SSD performance at a per-IO granularity, enhancing predictability for parallel storage applications. Delve into the innovative approach that supports black-box devices and real production traces without user input, outperforming industrial mechanisms. Discover how LinnOS improves average I/O latencies by 9.6-79.6% with 87-97% inference accuracy and minimal 4-6μs overhead per I/O. Learn about the potential of integrating machine learning into operating systems for real-time decision-making, covering topics such as the importance of storage, current solutions, design and mitigation challenges, and comprehensive evaluation results.

Syllabus

Introduction
Storage is important
Current solutions
Design challenges
Mitigation challenges
Evaluation

Taught by

USENIX

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