research-article

SSD-based Workload Characteristics and Their Performance Implications

Authors:

Shehbaz Jaffer,

Bianca SchroederAuthors Info & Claims

ACM Transactions on Storage (TOS), Volume 17, Issue 1

Article No.: 8, Pages 1 - 26

https://doi.org/10.1145/3423137

Published: 08 January 2021 Publication History

Abstract

Storage systems are designed and optimized relying on wisdom derived from analysis studies of file-system and block-level workloads. However, while SSDs are becoming a dominant building block in many storage systems, their design continues to build on knowledge derived from analysis targeted at hard disk optimization. Though still valuable, it does not cover important aspects relevant for SSD performance. In a sense, we are “searching under the streetlight,” possibly missing important opportunities for optimizing storage system design.

We present the first I/O workload analysis designed with SSDs in mind. We characterize traces from four repositories and examine their “temperature” ranges, sensitivity to page size, and “logical locality.” We then take the first step towards correlating these characteristics with three standard performance metrics: write amplification, read amplification, and flash read costs. Our results show that SSD-specific characteristics strongly affect performance, often in surprising ways.

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Index Terms

SSD-based Workload Characteristics and Their Performance Implications
1. Information systems
  1. Information storage systems

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Published In

cover image ACM Transactions on Storage

ACM Transactions on Storage Volume 17, Issue 1

Special Section on Usenix Fast 2020

February 2021

165 pages

ISSN:1553-3077

EISSN:1553-3093

DOI:10.1145/3446939

Editor:
Sam H. Noh
Ulsan National Institute of Science and Technology, Ulsan, Republic of Korea

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Publication History

Published: 08 January 2021

Accepted: 01 September 2020

Revised: 01 July 2020

Received: 01 January 2020

Published in TOS Volume 17, Issue 1

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