research-article

Pipette: efficient fine-grained reads for SSDs

Authors:

Hu Wan,

Fei Wu,

Chun Jason XueAuthors Info & Claims

DAC '22: Proceedings of the 59th ACM/IEEE Design Automation Conference

Pages 385 - 390

https://doi.org/10.1145/3489517.3530467

Published: 23 August 2022 Publication History

Get Access

Abstract

Big data applications, such as recommendation system and social network, often generate a huge number of fine-grained reads to the storage. Block-oriented storage devices tend to suffer from these fine-grained read operations in terms of I/O traffic as well as performance. Motivated by this challenge, a fine-grained read framework, Pipette, is proposed in this paper, as an extension to the traditional I/O framework. With an adaptive caching design, Pipette framework offers a tremendous reduction in I/O traffic as well as achieves significant performance gain. A Pipette prototype was implemented with Ext4 file system on an SSD for two real-world applications, where the I/O throughput is improved by 31.6% and 33.5%, and the I/O traffic is reduced by 95.6% and 93.6%, respectively.

References

[1]

Ahmed Abulila, Vikram Sharma Mailthody, Zaid Qureshi, Jian Huang, Nam Sung Kim, Jinjun Xiong, and Wen-mei Hwu. 2019. FlatFlash: Exploiting the Byte-Accessibility of SSDs within a Unified Memory-Storage Hierarchy. In Proceedings of the Twenty-Fourth International Conference on Architectural Support for Programming Languages and Operating Systems. ACM, Providence, RI, USA, 971--985.

Digital Library

Google Scholar

[2]

Timothy G Armstrong, Vamsi Ponnekanti, Dhruba Borthakur, and Mark Callaghan. 2013. LinkBench: a database benchmark based on the Facebook social graph. In Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data. ACM, New York, NY, USA, 1185--1196.

Digital Library

Google Scholar

[3]

Duck-Ho Bae, Insoon Jo, Youra Adel Choi, Joo-Young Hwang, Sangyeun Cho, Dong-Gi Lee, and Jaeheon Jeong. 2018. 2B-SSD: The Case for Dual, Byte- and Block-Addressable Solid-State Drives. In Proceedings of the 45th Annual International Symposium on Computer Architecture. IEEE, Los Angeles, California, 425--438.

Digital Library

Google Scholar

[4]

Nathan Bronson, Zach Amsden, George Cabrera, Prasad Chakka, Peter Dimov, Hui Ding, Jack Ferris, Anthony Giardullo, Sachin Kulkarni, Harry Li, Mark Marchukov, Dmitri Petrov, Lovro Puzar, Yee Jiun Song, and Venkat Venkataramani. 2013. TAO: Facebook's Distributed Data Store for the Social Graph. In 2013 USENIX Annual Technical Conference. USENIX Association, San Jose, CA, USA, 49--60.

Google Scholar

[5]

Criteo. 2014. Kaggle Display Advertising Challenge Dataset. Criteo. https://labs.criteo.com/2014/02/kaggle-display-advertising-challenge-dataset/

Google Scholar

[6]

Assaf Eisenman, Maxim Naumov, Darryl Gardner, Misha Smelyanskiy, Sergey Pupyrev, Kim M. Hazelwood, Asaf Cidon, and Sachin Katti. 2019. Bandana: Using Non-Volatile Memory for Storing Deep Learning Models. In Proceedings of Machine Learning and Systems, Vol. 1. Systems and Machine Learning Foundation, Palo Alto, CA, USA, 40--52.

Google Scholar

[7]

Udit Gupta, Samuel Hsia, Vikram Saraph, Xiaodong Wang, Brandon Reagen, Gu-Yeon Wei, Hsien-Hsin S. Lee, David Brooks, and Carole-Jean Wu. 2020. Deep-RecSys: A System for Optimizing End-To-End At-Scale Neural Recommendation Inference. In 47th ACM/IEEE Annual International Symposium on Computer Architecture. IEEE, Valencia, Spain, 982--995.

Google Scholar

[8]

Udit Gupta, Carole-Jean Wu, Xiaodong Wang, Maxim Naumov, Brandon Reagen, David Brooks, Bradford Cottel, Kim Hazelwood, Mark Hempstead, Bill Jia, Hsien-Hsin S. Lee, Andrey Malevich, Dheevatsa Mudigere, Mikhail Smelyanskiy, Liang Xiong, and Xuan Zhang. 2020. The Architectural Implications of Facebook's DNN-Based Personalized Recommendation. In IEEE International Symposium on High Performance Computer Architecture. IEEE, San Diego, CA, USA, 488--501.

Crossref

Google Scholar

[9]

Jun He, Kan Wu, Sudarsun Kannan, Andrea Arpaci-Dusseau, and Remzi Arpaci-Dusseau. 2020. Read as Needed: Building WiSER, a Flash-Optimized Search Engine. In 18th USENIX Conference on File and Storage Technologies. USENIX Association, Santa Clara, CA, USA, 59--73.

Google Scholar

[10]

Yanqin Jin, Hung-Wei Tseng, Yannis Papakonstantinou, and Steven Swanson. 2017. Improving SSD Lifetime with Byte-Addressable Metadata. In Proceedings of the International Symposium on Memory Systems. ACM, New York, NY, USA, 374--384.

Digital Library

Google Scholar

[11]

Hu Wan, Xuan Sun, Yufei Cui, Chia-Lin Yang, Tei-Wei Kuo, and Chun Jason Xue. 2021. FlashEmbedding: Storing Embedding Tables in SSD for Large-Scale Recommender Systems. In Proceedings of the 12th ACM SIGOPS Asia-Pacific Workshop on Systems. ACM, New York, NY, USA, 9--16.

Digital Library

Google Scholar

[12]

Zhe Yang, Youyou Lu, Erci Xu, and Jiwu Shu. 2020. CoinPurse: A Device-Assisted File System with Dual Interfaces. In Proceedings of the 57th ACM/EDAC/IEEE Design Automation Conference. IEEE, Virtual Event, USA, Article 100, 6 pages.

Crossref

Google Scholar

[13]

YEESTOR. 2021. Yeestor YS9203 PCIe SSD Memory Controller. YEESTOR Micro-electronics. http://www.yeestor.com/

Google Scholar

Cited By

View all

Bai SWan HHuang YSun XWu FXie CHsieh HKuo TXue C(2023)Pipette: Efficient Fine-Grained Reads for SSDsIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2023.327652042:12(4721-4734)Online publication date: 15-May-2023
https://dl.acm.org/doi/10.1109/TCAD.2023.3276520

Index Terms

Pipette: efficient fine-grained reads for SSDs
1. Information systems
  1. Information storage systems
    1. Information storage technologies
      1. Storage class memory
        Flash memory
2. Software and its engineering
  1. Software organization and properties
    1. Contextual software domains
      1. Operating systems
        File systems management

Recommendations

CosaFS: A Cooperative Shingle-Aware File System
Special Issue on MSST 2017 and Regular Papers

In this article, we design and implement a cooperative shingle-aware file system, called CosaFS, on heterogeneous storage devices that mix solid-state drives (SSDs) and shingled magnetic recording (SMR) technology to improve the overall performance of ...
BetrFS: a compleat file system for commodity SSDs
EuroSys '22: Proceedings of the Seventeenth European Conference on Computer Systems

Despite the existence of file systems tailored for flash and over a decade of research into flash file systems, this paper shows that no single Linux file system performs consistently well on a commodity SSD across different workloads. We define a ...
Read-Performance Optimization for Deduplication-Based Storage Systems in the Cloud

Data deduplication has been demonstrated to be an effective technique in reducing the total data transferred over the network and the storage space in cloud backup, archiving, and primary storage systems, such as VM (virtual machine) platforms. However, ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

DAC '22: Proceedings of the 59th ACM/IEEE Design Automation Conference

July 2022

1462 pages

ISBN:9781450391429

DOI:10.1145/3489517

General Chair:
Rob Oshana
NXP

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 23 August 2022

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Funding Sources

Research Grants Council of the Hong Kong Special Administrative Region, China
National Natural Science Foundation of China

Conference

DAC '22

Sponsor:

SIGDA

DAC '22: 59th ACM/IEEE Design Automation Conference

July 10 - 14, 2022

California, San Francisco

Acceptance Rates

Overall Acceptance Rate 1,770 of 5,499 submissions, 32%

Upcoming Conference

DAC '25

Sponsor:
sigda

62nd ACM/IEEE Design Automation Conference

June 22 - 26, 2025

San Francisco , CA , USA

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

1
Total Citations
View Citations
360
Total Downloads

Downloads (Last 12 months)120
Downloads (Last 6 weeks)12

Reflects downloads up to 16 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

View all

Bai SWan HHuang YSun XWu FXie CHsieh HKuo TXue C(2023)Pipette: Efficient Fine-Grained Reads for SSDsIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2023.327652042:12(4721-4734)Online publication date: 15-May-2023
https://dl.acm.org/doi/10.1109/TCAD.2023.3276520

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Cited By

Index Terms

Recommendations

CosaFS: A Cooperative Shingle-Aware File System

BetrFS: a compleat file system for commodity SSDs

Read-Performance Optimization for Deduplication-Based Storage Systems in the Cloud