Benchmarking and Performance Evaluations on Various Configurations of Virtual Machine and Containers for Cloud-Based Scientific Workloads

Abstract

Cloud computing manages system resources such as processing, storage, and networking by providing users with multiple virtual machines (VMs) as needed. It is one of the rapidly growing fields that come with huge computational power for scientific workloads. Currently, the scientific community is ready to work over the cloud as it is considered as a resource-rich paradigm. The traditional way of executing scientific workloads on cloud computing is by using virtual machines. However, the latest emerging concept of containerization is growing more rapidly and gained popularity because of its unique features. Containers are treated as lightweight as compared to virtual machines in cloud computing. In this regard, a few VMs/containers-associated problems of performance and throughput are encountered because of middleware technologies such as virtualization or containerization. In this paper, we introduce the configurations of VMs and containers for cloud-based scientific workloads in order to utilize the technologies to solve scientific problems and handle their workloads. This paper also tackles throughput and efficiency problems related to VMs and containers in the cloud environment and explores efficient resource provisioning by combining four unique methods: hyperthreading (HT), vCPU cores selection, vCPU affinity, and isolation of vCPUs. The HEPSCPEC06 benchmark suite is used to evaluate the throughput and efficiency of VMs and containers. The proposed solution is to implement four basic techniques to reduce the effect of virtualization and containerization. Additionally, these techniques are used to make virtual machines and containers more effective and powerful for scientific workloads. The results show that allowing hyperthreading, isolation of CPU cores, proper numbering, and allocation of vCPU cores can improve the throughput and performance of virtual machines and containers.

Performance of Communication- and Computation-Intensive SaaS on the OpenStack Cloud

“…The source codes of virtual infrastructure managers were modified to reduce instantiation times. Shah et al [28] evaluated the performance of VMs and containers for the HEPSCPEC06 benchmark. The results showed that hyperthreading, isolation of CPU cores, proper numbering, and allocation of vCPU cores improve the performance of VMs and containers on the OpenStack cloud.…”

Tendencias investigativas en el uso de Cloud Computing en contenerización entre 2015 y 2023

“…El cuadrante 2 del plano cartesiano, donde residen los conceptos emergentes en el campo de la contenerización y el cómputo en la nube, presentó términos cruciales para la actualidad y el futuro próximo del ámbito científico como Virtual Machines, Performance Evaluation y Container Orchestration; estas palabras clave son consideradas a menudo como la base de la virtualización, y han sido objeto de exhaustivas evaluaciones de rendimiento y comparaciones con tecnologías más recientes, como los contenedores. Un estudio relevante se centró en el benchmarking y la evaluación del rendimiento en diversas configuraciones de máquinas virtuales y contenedores para cargas de trabajo científicas basadas en la nube, proporcionando una visión crítica de la eficacia y eficiencia de las máquinas virtuales en entornos científicos en la nube (Shah et al, 2021).…”

Performance Evaluation of Virtualization Methodologies to Facilitate NFV Deployment

“…The type-1 hypervisor can control the guest OS directly on the host's hardware, whereas type-2 hypervisors are hosted on the primary operating system. We have selected three of the most well-known type-1 hypervisors in the market, including VMware vSphere, Microsoft Hyper-V, and Citrix XenServer, as they all run directly on top of the host's physical layer and are well-known for their competence in virtualization and cloud computing [23].…”