摘要
随着军事信息化建设,物联网广泛应用于战场感知、智能控制等军事领域,产生了海量的半结构化、非结构化的数据,受到I/O性能尤其是网络传输、硬盘读写的限制,传统的计算系统难以满足海量数据处理的应用需求。因此,提出了一种计算存储融合方法,通过扩展Linux内核,将集群内所有节点上的内存、处理器等计算存储资源在系统空间映射成一个统一的资源池,实现了单一进程空间和单一内存空间,并在内存空间内建立一个分布式内存文件系统。计算时可将数据完全加载到内存中,计算过程中仅与内存文件系统交互,避免了硬盘读写对系统性能的影响;另外,通过进程迁移,避免了节点之间的大量数据传输。实验结果表明,该方法对数据密集型计算是有效的,能够大幅提升系统的计算性能。
With the development of military information, the internet of things is applied widely in some military domains as battlefield perception, intelligent control and so on. As a result, massive semi-structured and no-structure data is produced. Traditional computing system cannot deal with so much data because of the low performance of I/O interfaces especially net- work and hard disks. In this paper, a fusion method of computing and memory is proposed. By extending the Linux kernel, all memory and processors in a cluster are mapped a union resource pool in the system space and form a single memory space and process space. Based on this, distributed RAM file system is build in DRAM. So all data can be loaded into memory and application only read/write RAM file system and reduce hard disk access influence on computing system. On the side, by mi- grating processes between each node, data transportation on the network is avoided. The experimental results show that the method is efficient for data intensive applications and increase computing performance greatly.
出处
《指挥控制与仿真》
2015年第3期1-7,共7页
Command Control & Simulation
关键词
计算存储融合
内存计算
进程迁移
分布式内存文件系统
computing and storage fusion
in memory computing
process migration
distributed RAM files system
