megaloc:用于基于nvm的集群的快速分布式内存分配器

Songping Yu, Nong Xiao, Mingzhu Deng, Yuxuan Xing, Fang Liu, Wei Chen
{"title":"megaloc:用于基于nvm的集群的快速分布式内存分配器","authors":"Songping Yu, Nong Xiao, Mingzhu Deng, Yuxuan Xing, Fang Liu, Wei Chen","doi":"10.1109/NAS.2017.8026865","DOIUrl":null,"url":null,"abstract":"As the expected emerging Non-Volatile Memory (NVM) technologies, such as 3DXPoint, are in production, there has been a recent push in the big data processing community from storage-centric towards memory-centric. Generally, in large-scale systems, distributed memory management through traditional network with TCP/IP protocol exposes performance bottleneck. Briefly, CPU- centric network involves context switching, memory copy etc. Remote Direct Memory Access (RDMA) technology reveals the tremendous performance advantage over than TCP/IP: Allowing access to remote memory directly bypassing OS kernel. In this paper, we propose Megalloc, a distributed NVM allocator exposes NVMs as a shared address space of a cluster of machines based-on RDMA. Firstly, it makes memory allocation metadata accessed directly by each machine, allocating NVM in coarse-grained way; secondly, adopting fine-grained memory chunk for applications to read or store data; finally, it guarantees high distributed memory allocation performance.","PeriodicalId":222161,"journal":{"name":"2017 International Conference on Networking, Architecture, and Storage (NAS)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Megalloc: Fast Distributed Memory Allocator for NVM-Based Cluster\",\"authors\":\"Songping Yu, Nong Xiao, Mingzhu Deng, Yuxuan Xing, Fang Liu, Wei Chen\",\"doi\":\"10.1109/NAS.2017.8026865\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As the expected emerging Non-Volatile Memory (NVM) technologies, such as 3DXPoint, are in production, there has been a recent push in the big data processing community from storage-centric towards memory-centric. Generally, in large-scale systems, distributed memory management through traditional network with TCP/IP protocol exposes performance bottleneck. Briefly, CPU- centric network involves context switching, memory copy etc. Remote Direct Memory Access (RDMA) technology reveals the tremendous performance advantage over than TCP/IP: Allowing access to remote memory directly bypassing OS kernel. In this paper, we propose Megalloc, a distributed NVM allocator exposes NVMs as a shared address space of a cluster of machines based-on RDMA. Firstly, it makes memory allocation metadata accessed directly by each machine, allocating NVM in coarse-grained way; secondly, adopting fine-grained memory chunk for applications to read or store data; finally, it guarantees high distributed memory allocation performance.\",\"PeriodicalId\":222161,\"journal\":{\"name\":\"2017 International Conference on Networking, Architecture, and Storage (NAS)\",\"volume\":\"17 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 International Conference on Networking, Architecture, and Storage (NAS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NAS.2017.8026865\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Networking, Architecture, and Storage (NAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NAS.2017.8026865","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

随着新兴的非易失性内存(Non-Volatile Memory, NVM)技术(如3DXPoint)投入生产,最近在大数据处理社区中出现了从以存储为中心向以内存为中心的推动。在大型系统中,传统的基于TCP/IP协议的网络分布式内存管理存在性能瓶颈。简而言之,以CPU为中心的网络涉及上下文切换、内存复制等。远程直接内存访问(RDMA)技术显示了比TCP/IP更大的性能优势:允许直接绕过操作系统内核访问远程内存。在本文中,我们提出了Megalloc,一个分布式NVM分配器,将NVM作为基于RDMA的机器集群的共享地址空间。首先,它使内存分配元数据由每台机器直接访问,以粗粒度方式分配NVM;其次,采用细粒度的内存块供应用程序读取或存储数据;最后,它保证了高的分布式内存分配性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Megalloc: Fast Distributed Memory Allocator for NVM-Based Cluster
As the expected emerging Non-Volatile Memory (NVM) technologies, such as 3DXPoint, are in production, there has been a recent push in the big data processing community from storage-centric towards memory-centric. Generally, in large-scale systems, distributed memory management through traditional network with TCP/IP protocol exposes performance bottleneck. Briefly, CPU- centric network involves context switching, memory copy etc. Remote Direct Memory Access (RDMA) technology reveals the tremendous performance advantage over than TCP/IP: Allowing access to remote memory directly bypassing OS kernel. In this paper, we propose Megalloc, a distributed NVM allocator exposes NVMs as a shared address space of a cluster of machines based-on RDMA. Firstly, it makes memory allocation metadata accessed directly by each machine, allocating NVM in coarse-grained way; secondly, adopting fine-grained memory chunk for applications to read or store data; finally, it guarantees high distributed memory allocation performance.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信