Enabling Large Scale Scientific Computations for Expressed Sequence Tag Sequencing over Grid and Cloud Computing Clusters

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This paper discusses expressed sequence tag sequencing over grid and cloud computing clusters, specifically for biological applications. In this paper, the authors propose a Web service framework for high-level job scheduling that is developed for scientific applications.

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10 p.

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Pallickara, Sangmi Lee; Pierce, Marlon; Dong, Qunfeng & Kong, ChinHua September 2009.

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This paper is part of the collection entitled: UNT Scholarly Works and was provided by UNT College of Arts and Sciences to Digital Library, a digital repository hosted by the UNT Libraries. It has been viewed 168 times , with 8 in the last month . More information about this paper can be viewed below.

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This paper discusses expressed sequence tag sequencing over grid and cloud computing clusters, specifically for biological applications. In this paper, the authors propose a Web service framework for high-level job scheduling that is developed for scientific applications.

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10 p.

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Abstract: Computer-intensive biological applications are heavily reliant on the availability of computing resources. Grid based HPC clusters and emerging Cloud computing clusters provide a large scale computing environment for scientific users. However, large scale biological application often involves various types of computational tasks which can benefit from different types of computing clusters. Therefore, a high level job scheduling environment which integrates the Grid style HPC clusters and the Cloud computing clusters and manages jobs accordingly based on the characteristics of the jobs is required. In this paper, the authors propose a Web service framework for high-level job scheduling - Swarm. Swarm is developed for scientific applications that must submit massive number of high-throughput jobs or workflows to highly distributed computing clusters. Swarm allows the users to submit jobs to both Grid HPC and Cloud computing clusters. The Swarm service itself is designed to be extensible, lightweight, and easily installable on a desktop or a small server. As a Web service, derivative services based on Swarm can be straightforwardly integrated with Web portals and science gateways. This paper provides the motivation for this research, the architecture of the Swarm framework, and a performance evaluation of the system prototype.

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  • Eighth International Conference on Parallel Processing and Applied Mathematics (PPAM), 2009, Wroclaw, Poland

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  • September 2009

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  • April 2, 2012, 4:46 p.m.

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  • Sept. 25, 2015, 1:09 p.m.

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Pallickara, Sangmi Lee; Pierce, Marlon; Dong, Qunfeng & Kong, ChinHua. Enabling Large Scale Scientific Computations for Expressed Sequence Tag Sequencing over Grid and Cloud Computing Clusters, paper, September 2009; [Berlin, Germany]. (digital.library.unt.edu/ark:/67531/metadc78330/: accessed October 19, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT College of Arts and Sciences.