HPC on Competitive Cloud Resources

Bientinesi, Paolo; Iakymchuk, Roman; Napper, Jeff

doi:10.1007/978-1-4419-6524-0_21

Cited by 20 publications

(26 citation statements)

References 8 publications

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“…The above results are supported by the extensive work in [4] that performed a deeper analysis with results pointing to the diverse demands of Cloud environments facing scientific and commercial applications. Clouds demand a review of the metrics used to evaluate the performance of the environments.…”

Section: B Virtualization and Performancesupporting

confidence: 66%

The Impact of Hypervisor Layer on Database Applications

Yokoyama

Dias

Kloh

et al. 2012

2012 IEEE Fifth International Conference on Utility and Cloud Computing

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This paper presents the impact analysis of the hypervisor layer over database applications. The conclusions were reached by performing experiments with hybrid environments, composed by bare-metal servers and two types of hypervisors. The main objectives were to compare the behaviour of database applications and to determine the maximum service capacity of a virtualized database server on different environments. With the results, it was possible to assess the scalability of a database environment, according to the type of hypervisor and the number of simultaneous connections, and decide how and when to expand or reduce the virtualized infrastructure.

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Section: B Virtualization and Performancesupporting

confidence: 66%

The Impact of Hypervisor Layer on Database Applications

Yokoyama

Dias

Kloh

et al. 2012

2012 IEEE Fifth International Conference on Utility and Cloud Computing

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“…In line with the discussion regarding Cloud Co mputing fro m the view of Berkeley [20], the economics facet of a co mmercial Cloud service contains two properties: price and elasticity. Thus, we collected and organized relevant metrics for these two properties respectively, as shown in Table 3 [17,21,22]. …”

Section: B Economics Metricsmentioning

confidence: 99%

QoS Metrics for Cloud Computing Services Evaluation

Bardsiri¹,

Hashemi²

2014

IJISA

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Abstract-Cloud systems are transforming the Information Technology trade by facultative the companies to provide admission to their structure and also software products to the membership foundation. Because of the vast range within the delivered Cloud solutions, from the customer's perspective of an aspect, it's emerged as troublesome to decide whose providers they need to utilize and then what's the thought of his or her option. Especially, employing suitable metrics is vital in assessing practices. Nevertheless, to the most popular of our knowledge, there's no methodical explanation relating to metrics for estimating Cloud products and services. QoS (Quality of Service) metrics playing an important role in selecting Cloud providers and also optimizing resource utilization efficiency. While many reports have got to devote to exploitation QoS metrics, relatively not much equipment supports the remark and investigation of QoS metrics of Cloud programs. To guarantee a specialized product is published, describing metrics for assessing the QoS might be an essential necessity. So, this text suggests various QoS metrics for service vendors, especially thinking about the consumer's worry. This article provides the metrics list may stand to help the future study and also assessment within the field of Cloud service's evaluation.

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“…There are many proponents of cloud computing whom additionally advocate migrating high performance computing workloads to the cloud [10][11] [12]. However, there has been little existing work in creating a HPC Job Manager and Scheduler that is truly dynamic and elastic.…”

Section: A Backgroundmentioning

confidence: 99%

Advancing Research Infrastructure Using OpenStack

Kureshi¹,

Pulley²,

Brennan³

et al. 2013

SpecialIssue

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Abstract-Cloud computing, which evolved from grid computing, virtualisation and automation, has a potential to deliver a variety of services to the end user via the Internet. Using the Web to deliver Infrastructure, Software and Platform as a Service (SaaS/PaaS) has benefits of reducing the cost of investment in internal resources of an organisation. It also provides greater flexibility and scalability in the utilisation of the resources. There are different cloud deployment models -public, private, community and hybrid clouds. This paper presents the results of research and development work in deploying a private cloud using OpenStack at the University of Huddersfield, UK, integrated into the University campus Grid QGG.The aim of our research is to use a private cloud to improve the High Performance Computing (HPC) research infrastructure. This will lead to a flexible and scalable resource for research, teaching and assessment. As a result of our work we have deployed private QGG-cloud and devised a decision matrix and mechanisms required to expand HPC clusters into the cloud maximising the resource utilisation efficiency of the cloud.As part of teaching and assessment of computing courses an Automated Formative Assessment (AFA) system was implemented in the QGG-Cloud. The system utilises the cloud's flexibility and scalability to assign and reconfigure required resources for different tasks in the AFA. Furthermore, the throughput characteristics of assessment workflows were investigated and analysed so that the requirements for cloud-based provisioning can be adequately made.

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HPC on Competitive Cloud Resources

Cited by 20 publications

References 8 publications

The Impact of Hypervisor Layer on Database Applications

The Impact of Hypervisor Layer on Database Applications

QoS Metrics for Cloud Computing Services Evaluation

Advancing Research Infrastructure Using OpenStack

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