SSD论文优秀句子
1. Nonvolatile memory(e.g., Phase Change Memory) blurs the boundary between memory and storage and it could greatly facilitate the construction of in-memory durable data structures. Data structures can be processed and stored directly in NVRAM. To XXX, YYY is a widely adopted mechanism. However, XXXXXXXX. By leveraging the XXXXX, we can YYYYYY. We tested our YYYYYY. Experiment results show that ZZZZZZZ, which can help extend the lifetime of NVRAM and improve performance.
2. By enabling efficient XXXX, YYY serve as the foundation for ZZZ. For example: By enabling efficient insertions, point lookups, and range queries, key-value stores serve as the foundation for this growing group of important applications.
3. For write-intensive workloads, key-value stores based on Log-Structured Merge-Trees(LSM-trees)[1] have become the state of the art. Various distributed and local stores built on LSM-trees are widely deployed in large-scale production environments, such as BigTable [2] and LevelDB [3] at Google, Cassandra [4], HBase [5] and RocksDB [6] at Facebook, and Riak [7] at Basho. The main advantage of LSM-trees over other indexing structures (such as B-trees) is that they maintain sequential access patterns for writes. Small updates on B-trees may involve many random writes, and are hence not efficient on either solid-state storage devices or hard-disk drives.
-----
Reference
[1] Patrick ONeil, Edward Cheng, Dieter Gawlick, and Elizabeth ONeil. The Log-Structured MergeTree (LSM-tree). Acta Informatica, 33(4):351–385, 1996.
[2] Fay Chang, Jeffrey Dean, Sanjay Ghemawat, Wilson C. Hsieh, Deborah A. Wallach, Michael Burrows, Tushar Chandra, Andrew Fikes, and Robert Gruber. Bigtable: A Distributed Storage System for Structured Data. In Proceedings of the 7th Symposium on Operating Systems Design and Implementation (OSDI ’06), pages 205–218, Seattle, Washington, November 2006.
[3] Sanjay Ghemawat and Jeff Dean. LevelDB. http://code.google.com/p/leveldb, 2011.
[4] Avinash Lakshman and Prashant Malik. Cassandra – A Decentralized Structured Storage System. In The 3rd ACM SIGOPS International Workshop on Large Scale Distributed Systems and Middleware, Big Sky Resort, Montana, Oct 2009.
[5] Tyler Harter, Dhruba Borthakur, Siying Dong, Amitanand Aiyer, Liyin Tang, Andrea C. ArpaciDusseau, and Remzi H. Arpaci-Dusseau. Analysis of HDFS Under HBase: A Facebook Messages Case Study. In Proceedings of the 12th
USENIX Symposium on File and Storage Technologies (FAST ’14), Santa Clara, California, February 2014.
[6] Facebook. RocksDB. http://rocksdb.org/, 2013.
[7] Riak. http://docs.basho.com/riak/, 2015.
[8]
SSD论文优秀句子的更多相关文章
- 深度学习 目标检测算法 SSD 论文简介
深度学习 目标检测算法 SSD 论文简介 一.论文简介: ECCV-2016 Paper:https://arxiv.org/pdf/1512.02325v5.pdf Slides:http://w ...
- SSD论文理解
SSD论文贡献: 1. 引入了一种单阶段的检测器,比以前的算法YOLO更准更快,并没有使用RPN和Pooling操作: 2. 使用一个小的卷积滤波器应用在不同的feature map层从而预测BB的类 ...
- 翻译SSD论文(Single Shot MultiBox Detector)
转自http://lib.csdn.net/article/deeplearning/53059 作者:Ai_Smith 本文翻译而来,如有侵权,请联系博主删除.未经博主允许,请勿转载.每晚泡脚,闲来 ...
- 深度学习笔记(七)SSD 论文阅读笔记简化
一. 算法概述 本文提出的SSD算法是一种直接预测目标类别和bounding box的多目标检测算法.与faster rcnn相比,该算法没有生成 proposal 的过程,这就极大提高了检测速度.针 ...
- 深度学习笔记(七)SSD 论文阅读笔记
一. 算法概述 本文提出的SSD算法是一种直接预测目标类别和bounding box的多目标检测算法.与faster rcnn相比,该算法没有生成 proposal 的过程,这就极大提高了检测速度.针 ...
- 转 SSD论文解读
版权声明:本文为博主原创文章,遵循CC 4.0 BY-SA版权协议,转载请附上原文出处链接和本声明. 本文链接:https://blog.csdn.net/u010167269/article/det ...
- SSD论文学习
SSD: Single Shot MultiBox Detector——目标检测 参考https://blog.csdn.net/u010167269/article/details/52563573 ...
- ssd论文解读
https://www.sohu.com/a/168738025_717210 https://www.cnblogs.com/lillylin/p/6207292.html https://blog ...
- ssd算法论文理解
这篇博客主要是讲下我在阅读ssd论文时对论文的理解,并且自行使用pytorch实现了下论文的内容,并测试可以用. 开篇放下论文地址https://arxiv.org/abs/1512.02325,可以 ...
随机推荐
- 逗号分隔字符串转换为一张表--解决查询in(逗号分隔字符串)出错问题
CREATE PROCEDURE [dbo].[Pro_TEST] AS BEGIN ) ) SET @split=',' SET @c='025,023,014,015' )) ) BEGIN IN ...
- Spring技术内幕:Spring AOP的实现原理(二)
**二.AOP的设计与实现 1.JVM的动态代理特性** 在Spring AOP实现中, 使用的核心技术时动态代理.而这样的动态代理实际上是JDK的一个特性.通过JDK的动态代理特性,能够为随意Jav ...
- C++中的头文件和源文件
一.C++编译模式 通常,在一个C++程序中,只包含两类文件——.cpp文件和.h文件.其中,.cpp文件被称作C++源文件,里面放的都是C++的源代码:而.h文件则被称作C++头文件,里面放的也是C ...
- 9个使用前必须再三小心的Linux命令
Linux shell/terminal 命令非常强大,即使一个简单的命令就可能导致文件夹.文件或者路径文件夹等被删除.在一些情况下,Linux 甚至不会询问你而直接执行命令,导致你丢失各种数据信 ...
- HIDKomponente使用读写Hid设备一瞥
HIDKomponente 是delphi中使用的第三方Hid控件库,可以检测.控制连接到电脑的Hid设备.一般情况下多为usb设备.HIDKomponente的使用实际上很简单,只是因为第一次使用, ...
- 面试题总结之Linux/Shell
Linux Linux cshrc文件作用 Linux如何起进程/查看进程/杀进程 Linux 文件755 代表什么权限 Linux辅助线程 Linux进程间通信方法 pipeline,msgq... ...
- 文件I/O之sync、fsync和fdatasync函数
传统的UNIX实现在内核中设有缓冲区高速缓存或页面高速缓存,大多数磁盘I/O都通过缓冲进行.当将数据写入文件时,内核通常先将数据复制到其中一个缓冲区中,如果 该缓冲区尚未写满,则并不将其排入输出队列, ...
- oracle11g密码大小写敏感问题
密码大小写敏感是Oracle 11g数据库默认的一个新特性,数据库配置助手(DBCA)在创建数据库期间允许你将这个设置返回到11g以前的功能. SEC_CASE_SENSITIVE_LOGON初始化参 ...
- 有关于Algorithm的基础介绍
Niklaus Wirth:Algorithm + Data Structures = Programs 这句话呢,觉得很正确,算法和程序是不同的概念,算法的思想呢有递推,枚举,分治,贪婪,试探法,模 ...
- my_vimrc
" ----------------- Author: Ruchee" ----------------- Email: my@ruchee.com" --------- ...