Parallel programming with MPI
IEEE Transactions on Knowledge and Data Engineering
Taverna: lessons in creating a workflow environment for the life sciences: Research Articles
Concurrency and Computation: Practice & Experience - Workflow in Grid Systems
Pegasus: A framework for mapping complex scientific workflows onto distributed systems
Scientific Programming
MapReduce: simplified data processing on large clusters
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
A distributed architecture for data mining and integration
Proceedings of the second international workshop on Data-aware distributed computing
Nearest neighbor pattern classification
IEEE Transactions on Information Theory
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In this paper, we investigate how MapReduce and Cloud computing can accelerate performance of applications and scale up the computing resources through a real data mining use case in the Biomedical Sciences. We have prototyped the data mining task using the MapReduce model and evaluated it in the Cloud. A performance evaluation model has been built for assessing the eff ciency of the prototype. The results, from both experiments and the evaluation model, show the performance and scalability can be enhanced through these advanced technologies.