A framework for readapting and running bioinformatics applications in the cloud

Edgar Sarmiento Calisaya, Karin Breitman, Alberto M.R. Dávila, José Viterbo

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Large scale experiments in the field of scientific computing, particularly in bioinformatics, typically require both processing of huge amounts of data and significant computing power. High performance computing (HPC) architectures, in particular cloud computing environments, may help meet these requirements by enabling fast, large-scale, and costeffective parallel job execution. However, for that to happen, we need efficient scheduling algorithms to distribute tasks to available resources in a uniform way. In this paper we propose an agent-based framework that allows modeling, implementing, deploying, and configuring parallel execution of bioinformatics experiments in the cloud. To demonstrate the feasibility of our approach, we implemented an instance of the proposed framework on the AWS platform. Experimental results show performance gains, scalability, and indicate that the proposed framework may be an efficient alternative for running parallel bioinformatics applications in the cloud.

Original languageEnglish
Title of host publicationProceeding of the 2012 ACM Research in Applied Computation Symposium, RACS 2012
Pages86-91
Number of pages6
DOIs
StatePublished - 2012
Externally publishedYes
Event2012 ACM Research in Applied Computation Symposium, RACS 2012 - San Antonio, TX, United States
Duration: 23 Oct 201226 Oct 2012

Publication series

NameProceeding of the 2012 ACM Research in Applied Computation Symposium, RACS 2012

Conference

Conference2012 ACM Research in Applied Computation Symposium, RACS 2012
Country/TerritoryUnited States
CitySan Antonio, TX
Period23/10/1226/10/12

Keywords

  • Bioinformatics
  • Parallelization and cloud computing

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