Article

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.

0 Bookmarks
 · 
102 Views
  • Source
    [Show abstract] [Hide abstract]
    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
  • [Show abstract] [Hide abstract]
    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
  • [Show abstract] [Hide abstract]
    ABSTRACT: Spatial overlay processing is a widely used compute-intensive GIS application that involves aggregation of two or more layers of maps to facilitate intelligent querying on the collocated output data. When large GIS data sets are represented in polygonal (vector) form, spatial analysis runs for extended periods of time, which is undesirable for time-sensitive applications such as emergency response. We have, for the first time, created an open-architecture-based system named Crayons for Azure cloud platform using state-of-the-art techniques. During the course of development of Crayons system, we faced numerous challenges and gained invaluable insights into Azure cloud platform, which are presented in detail in this paper. The challenges range from limitations of cloud storage and computational services to the choices of tools and technologies used for high performance computing (HPC) application design. We report our findings to provide concrete guidelines to an eScience developer for 1) choice of persistent data storage mechanism, 2) data structure representation, 3) communication and synchronization among nodes, 4) building robust failsafe applications, and 5) optimal cost-effective utilization of resources. Our insights into each challenge faced, the solution to overcome it, and the discussion on the lessons learnt from each challenge can be of help to eScience developers starting application development on Azure and possibly other cloud platforms.
    Cloud Computing (CLOUD), 2012 IEEE 5th International Conference on; 01/2012