{"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}
引用次数: 2
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.