Scientific Computing in the Cloud

Univ. of Washington, Seattle, WA, USA
Computing in Science and Engineering (Impact Factor: 1.73). 07/2010; DOI: 10.1109/MCSE.2010.70
Source: IEEE Xplore

ABSTRACT Large, virtualized pools of computational resources raise the possibility of a new, advantageous computing paradigm for scientific research. To help achieve this, new tools make the cloud platform behave virtually like a local homogeneous computer cluster, giving users access to high-performance clusters without requiring them to purchase or maintain sophisticated hardware.

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    ABSTRACT: Commercial Cloud services have been increasingly supplied to customers in industry. To facilitate customers' decision makings like cost-benefit analysis or Cloud provider selection, evaluation of those Cloud services are becoming more and more crucial. However, compared with evaluation of traditional computing systems, more challenges will inevitably appear when evaluating rapidly-changing and user-uncontrollable commercial Cloud services. This paper proposes an expert system for Cloud evaluation that addresses emerging evaluation challenges in the context of Cloud Computing. Based on the knowledge and data accumulated by exploring the existing evaluation work, this expert system has been conceptually validated to be able to give suggestions and guidelines for implementing new evaluation experiments. As such, users can conveniently obtain evaluation experiences by using this expert system, which is essentially able to make existing efforts in Cloud services evaluation reusable and sustainable.
    Cloud and Service Computing (CSC), 2012 International Conference on; 02/2012
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    ABSTRACT: Given the continually increasing amount of commercial Cloud services in the market, evaluation of different services plays a significant role in cost-benefit analysis or decision making for choosing Cloud Computing. In particular, employing suitable metrics is essential in evaluation implementations. However, to the best of our knowledge, there is not any systematic discussion about metrics for evaluating Cloud services. By using the method of Systematic Literature Review (SLR), we have collected the de facto metrics adopted in the existing Cloud services evaluation work. The collected metrics were arranged following different Cloud service features to be evaluated, which essentially constructed an evaluation metrics catalogue, as shown in this paper. This metrics catalogue can be used to facilitate the future practice and research in the area of Cloud services evaluation. Moreover, considering metrics selection is a prerequisite of benchmark selection in evaluation implementations, this work also supplements the existing research in benchmarking the commercial Cloud services.
    Grid 2012; 02/2012
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    ABSTRACT: Archaeological studies on battlefields may see great benefits from simulated military engagements: simulations help testing hypotheses based on historical data and may also help with validating methodologies used on the site. Such methods, however, require high-performance computing expertise and considerable computational power. With the emergence of on-demand computing instances in the cloud, distributed computations have become available to technically every organization or individual. This puts large-scale battlefield simulations within the reach of archaeologists, and the cloud paradigm also lowers the required technological expertise, potentially leading to a more widespread adoption of such simulation methods.
    Proceedings of CloudCom-12, 4th IEEE International Conference on Cloud Computing Technology and Science; 12/2012