An elastic virtual infrastructure for research applications (ELVIRA)

Voß, Alexander; Barker, Adam; Asgari-Targhi, M.; Ballegooijen, A. A. van; Sommerville, Ian

doi:10.1186/2192-113x-2-20

Cited by 7 publications

(5 citation statements)

References 15 publications

(23 reference statements)

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“…In (Jackson et al, 2010), the authors test a wide set of applications form atmosphere modelling and molecular structures to astro-physical flows, and although they consider the Cloud useful for a wide range applications they refer its utility not proven for tightly-coupled HPC applications. Authors in (Voss et al, 2013) test Magneto-Hydrodynamic Disturbances and report good results, but sustain that supports researchers and technological offerings adopted have to be tailored to the specific needs.…”

Section: Related Workmentioning

confidence: 94%

“…These dedicated datacenters, with a fixed throughput capacity, can be constrained with capacity and also become obsolete in a couple of years. Cloud bursting allows to maximize the utilization of HPC clusters and adds capacity beyond their limit (Voss, Barker, Asgari-Targhi, van Ballegooijen, & Sommerville, 2013).…”

Section: Introductionmentioning

confidence: 99%

“…Lending computational capacity from an external provider allows the users to benefit from the typical Cloud scalability, facing peak demands in a cost-effective manner. It also can implement a high availability strategy, transforming a standard infrastructure into an agile provisioning platform (Voss et al, 2013). Public Clouds are rather immature for HPC, being oriented to business applications (Ghoshal, Canon, & Ramakrishnan, 2011;He, Zhou, Kobler, Duffy, & McGlynn, 2010), even though lately some providers tried to increase HPC services and support offers (Barr, 2011).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

HPC in Weather Forecast

Monteiro

Teixeira

Pinto

2015

International Journal of Cloud Applications and Computing

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Many traditional High-Performance Computing systems rely on hardware performance as well as compiler parallelization. The increased demand on computing resources rapidly escalates costs, which are the bigger limitation nowadays in both public and private sector. Cutting costs stimulates the research for new solutions, which are being opened by Cloud Computing. Virtualization becomes the key to migration and delivering intensive computing applications becomes more proficient than ever, thus providing the motivation for a change to the Cloud. This paper presents a case study of how to migrate an application and optimize performance without significant cost growth based on Cloud Computing applied to weather forecasting.

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Section: Related Workmentioning

confidence: 94%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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HPC in Weather Forecast

Monteiro

Teixeira

Pinto

2015

International Journal of Cloud Applications and Computing

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“…One potential area that can be explored in this context are virtual private research environments using simple cloud tools but tailored to suit specific domain requirements. Such an approach is adopted in the ELVIRA [37] and CARMEN [38] projects. Another area that needs to be investigated is the development of environments that support budget-limited computation based on a set of user driven requirements.…”

Section: Five Opportunities For Academic Research Opportunity 1: User...mentioning

confidence: 99%

Academic Cloud Computing Research: Five Pitfalls and Five Opportunities

Barker,

Varghese,

Ward

et al. 2014

Preprint

Self Cite

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This discussion paper argues that there are five fundamental pitfalls, which can restrict academics from conducting cloud computing research at the infrastructure level, which is currently where the vast majority of academic research lies. Instead academics should be conducting higher risk research, in order to gain understanding and open up entirely new areas.We call for a renewed mindset and argue that academic research should focus less upon physical infrastructure and embrace the abstractions provided by clouds through five opportunities: user driven research, new programming models, PaaS environments, and improved tools to support elasticity and large-scale debugging. The objective of this paper is to foster discussion, and to define a roadmap forward, which will allow academia to make longer-term impacts to the cloud computing community.

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“…Organizations can scale up, scale down the resources, and pay for it according to the usage. Multitenancy provided by cloud architecture enabled the creation of domain and requirement specific virtual private research environments that expedited researchers for collaboration and sharing of the resources [3]. Several science clouds such as Nectar Research cloud [4] provides the infrastructure to run compute-intensive scientific applications [5], [6].…”

Section: Introductionmentioning

confidence: 99%

CCCORE: Cloud Container for Collaborative Research

Suresh

Rao²

2018

IJECE

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Cloud-based research collaboration platforms render scalable, secure and inventive environments that enabled academic and scientific researchers to share research data, applications and provide access to high-performance computing resources. Dynamic allocation of resources according to the unpredictable needs of applications used by researchers is a key challenge in collaborative research environments. We propose the design of Cloud Container based Collaborative Research (CCCORE) framework to address dynamic resource provisioning according to the variable workload of compute and data-intensive applications or analysis tools used by researchers. Our proposed approach relies on-demand, customized containerization and comprehensive assessment of resource requirements to achieve optimal resource allocation in a dynamic collaborative research environment. We propose algorithms for dynamic resource allocation problem in a collaborative research environment, which aim to minimize finish time, improve throughput and achieve optimal resource utilization by employing the underutilized residual resources. Keyword: Cloud computing Collaborative research Container Dynamic allocation Finish time Residual resources Throughput Copyright © 2018 Institute of Advanced Engineering and Science.All rights reserved. Corresponding Author:Salini Suresh, Computer Science, Bharathiar University, Coimbatore, India. Email: pnsalinisuresh@gmail.com INTRODUCTIONIn mid-1990's various grid-based cyberinfrastructures or e-infrastructures were constituted that integrated high-speed research networks and middleware services and endorsed researchers for collaborative sharing of distributed resources. These firmly unified science gateways served as resource providers for specialized as well as generic research initiatives [1]. However, restricted interface to the data, domainspecific nature of science gateways did not match the requirement of the researchers outside those domains [2]. With the advent of cloud computing, easy reconfigurable and adaptive Virtual private research environments and science clouds became a preferred alternative to a traditional grid or cluster-based einfrastructures. Cloud-based collaborative research platforms provide the researchers with computing, storage resources required to run their applications, and they can collaborate to share data and application, while he concentrates on his area of research. Cloud platform offers compute environment with the huge set of computing resources much bigger than what an individual research organization can afford. Organizations can scale up, scale down the resources, and pay for it according to the usage. Multitenancy provided by cloud architecture enabled the creation of domain and requirement specific virtual private research environments that expedited researchers for collaboration and sharing of the resources [3]. Several science clouds such as Nectar Research cloud [4] provides the infrastructure to run compute-intensive scientific applications [5], [6]. Even though a substant...

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An elastic virtual infrastructure for research applications (ELVIRA)

Cited by 7 publications

References 15 publications

HPC in Weather Forecast

HPC in Weather Forecast

Academic Cloud Computing Research: Five Pitfalls and Five Opportunities

CCCORE: Cloud Container for Collaborative Research

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