郑臣明, 姚宣霞, 周芳, 郑雪峰, 杨晓君, 戴荣. 基于硬件虚拟化的云服务器设计与实现[J]. 工程科学学报, 2022, 44(11): 1935-1945. DOI: 10.13374/j.issn2095-9389.2022.01.12.005
引用本文: 郑臣明, 姚宣霞, 周芳, 郑雪峰, 杨晓君, 戴荣. 基于硬件虚拟化的云服务器设计与实现[J]. 工程科学学报, 2022, 44(11): 1935-1945. DOI: 10.13374/j.issn2095-9389.2022.01.12.005
ZHENG Chen-ming, YAO Xuan-xia, ZHOU Fang, ZHENG Xue-feng, YANG Xiao-jun, DAI Rong. Design and implementation of a cloud server based on hardware virtualization[J]. Chinese Journal of Engineering, 2022, 44(11): 1935-1945. DOI: 10.13374/j.issn2095-9389.2022.01.12.005
Citation: ZHENG Chen-ming, YAO Xuan-xia, ZHOU Fang, ZHENG Xue-feng, YANG Xiao-jun, DAI Rong. Design and implementation of a cloud server based on hardware virtualization[J]. Chinese Journal of Engineering, 2022, 44(11): 1935-1945. DOI: 10.13374/j.issn2095-9389.2022.01.12.005

基于硬件虚拟化的云服务器设计与实现

Design and implementation of a cloud server based on hardware virtualization

  • 摘要: 随着互联网服务、大数据、云计算的兴起,云服务器渐成需求主流。相对于传统基于虚拟机的解决方案,基于硬件虚拟化的云服务器因减少了软件的花销能更好地实现高效能、按需简约,能更好地满足云计算的需求。与传统云服务器相比,该服务器的特点是高密度、高效能成本比、高效能功耗比和高可扩展性。本文介绍了云服务器按需配置的设计理念、分布式硬件资源共享的系统结构和硬件资源虚拟化的方法。设计并实现了一个基于硬件虚拟化的16个处理器的云服务器原型系统。在该系统中,基于现场可编程门阵列(Field programmable gate array,FPGA)设计实现云服务器的互联架构控制器(IFC)。IFC集成网络、存储和通用I/O资源,为高密度的云服务器提供多处理器间的互联。借助于IFC,所有CPU能够共享网络、存储和通用I/O资源,实现硬件资源的虚拟化。对原型系统的网络和存储性能进行了测试,结果表明该系统不但具有传统云服务器的架构优点而且还提供更好的扩展性和更高的性能。

     

    Abstract: Traditional cloud computing is developed from a high-performance cluster. Every server in the high-performance cluster has its own resources, including a CPU, memory, a network, I/O (Input/Output), a power system, and a heat dissipation system. Using software virtualization technologies such as the kernel-based virtual machine (KVM), Xen, VMware, and Hyper-V, these exclusive resources can be shared among these servers to improve the utilization rate. Although these technologies provide a great improvement in the resource utilization rate, some overhead in the process of software virtualization is inevitable. Server architecture and virtualization technology are the two factors that mainly affect cloud computing efficiency. With the rapid development of internet services, big data, and cloud computing, the cloud server has become mainstream instead of the traditional server. On the other hand, hardware virtualization technology has gradually developed. Compared with the traditional cloud computing solutions based on virtual machines, the cloud server based on hardware virtualization can achieve much higher efficiency to better meet cloud computing requirements by removing the software overhead. The cloud server’s design concept of configuration on demand, distributed sharing of hardware resource architecture, and construction method of hardware resource virtualization are presented. A three-level interconnection architecture of the cloud server is designed. In Level-1, the computing pool and the memory pool are built, while Level-2 is for the network pool, and Level-3 is for all resource pools. Different applications in these levels can be realized in the cloud server: Level-1 for computing-intensive applications, Level-2 for transactional applications, and Level-3 for virtual applications. A prototype system of a 16-processor cloud server using hardware virtualization architecture is designed and implemented. In this system, there are sixteen physical nodes. Every physical node is composed of a CPU and two DIMMs (dual inline memory modules). Different types of CPUs may be used in these physical nodes. Every four physical nodes form a computing module. In every computing module, a field-programmable gate array (FPGA)-based interconnection fabric controller (IFC) integrated network, storage, and general I/O resources is designed to interconnect these processors. All IFCs are interlinked. All the processors in this prototype system can share the network, storage, and general I/O resources to realize hardware resource virtualization through these IFCs. For the prototyping system, evaluation experiments on network performance tests by the Netperf program and storage performance tests by the FIO program are performed. The test results show that the prototyping system not only keeps the traditional cloud server’s advantages but also provides better scalability and performance. The advantages of this cloud server are in providing a high-density, high performance-to-cost ratio, a high performance-to-Watt ratio, and high scalability compared with the existing traditional cloud server.

     

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