Concurrency and Computation: Practice & Experience
Exploring Williams--Beuren syndrome using myGrid
Bioinformatics
Grid Approach to Embarrassingly Parallel CPU-Intensive Bioinformatics Problems
E-SCIENCE '06 Proceedings of the Second IEEE International Conference on e-Science and Grid Computing
MapReduce: simplified data processing on large clusters
Communications of the ACM - 50th anniversary issue: 1958 - 2008
OrthoSearch: a scientific workflow approach to detect distant homologies on protozoans
Proceedings of the 2008 ACM symposium on Applied computing
Agent-Grid Integration Language
Multiagent and Grid Systems
ESCIENCE '08 Proceedings of the 2008 Fourth IEEE International Conference on eScience
Exploring many task computing in scientific workflows
Proceedings of the 2nd Workshop on Many-Task Computing on Grids and Supercomputers
Cloud technologies for bioinformatics applications
Proceedings of the 2nd Workshop on Many-Task Computing on Grids and Supercomputers
Biodoop: Bioinformatics on Hadoop
ICPPW '09 Proceedings of the 2009 International Conference on Parallel Processing Workshops
An opportunistic algorithm for scheduling workflows on grids
VECPAR'06 Proceedings of the 7th international conference on High performance computing for computational science
Applications of grid computing in genetics and proteomics
PARA'06 Proceedings of the 8th international conference on Applied parallel computing: state of the art in scientific computing
EvolvingSpace: A Data Centric Framework for Integrating Bioinformatics Applications
IEEE Transactions on Computers
AzureBlast: a case study of developing science applications on the cloud
Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing
Data parallelism in bioinformatics workflows using Hydra
Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing
Parallelizing BLAST and SOM Algorithms with MapReduce-MPI Library
IPDPSW '11 Proceedings of the 2011 IEEE International Symposium on Parallel and Distributed Processing Workshops and PhD Forum
Parallel data processing with MapReduce: a survey
ACM SIGMOD Record
Parallelism in bioinformatics workflows
VECPAR'04 Proceedings of the 6th international conference on High Performance Computing for Computational Science
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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 cost-effective 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.