Vectorizing disks blocks for efficient storage system via deep learning-Reference-Cited by-同舟云学术

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Vectorizing disks blocks for efficient storage system via deep learning

Published:2019-02 Issue: Volume:82 Page:75-90
ISSN:0167-8191
Container-title:Parallel Computing
language:en
Short-container-title:Parallel Computing

Author:

Dai Dong^ORCID,Bao Forrest Sheng,Zhou Jiang,Shi Xuanhua,Chen Yong

Funder

National Science Foundation

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Graphics and Computer-Aided Design,Computer Networks and Communications,Hardware and Architecture,Theoretical Computer Science,Software

Reference41 articles.

1. Lustre: building a file system for 1000-node clusters;Schwan,2003

2. Ceph: a scalable, high-performance distributed file system;Weil,2006

3. The Google file system;Ghemawat,2003

4. Sedna: a memory based key-value storage system for realtime processing in cloud;Dai,2012

5. SUORA: a scalable and uniform data distribution algorithm for heterogeneous storage systems;Jiang,2016

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Multigraph learning for parallelism discovery in sequential programs;Concurrency and Computation: Practice and Experience;2023-02-13

2. Efficient Big-Data Access: Taxonomy and a Comprehensive Survey;IEEE Transactions on Big Data;2020

3. Work-in-Progress: A Deep Learning Strategy for I/O Scheduling in Storage Systems;2019 IEEE Real-Time Systems Symposium (RTSS);2019-12

4. Optimizing Data Placement on Hierarchical Storage Architecture via Machine Learning;Lecture Notes in Computer Science;2019

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