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Distributed media indexing based on MPI and MapReduce
2012
2012 10th International Workshop on Content-Based Multimedia Indexing (CBMI)
Web-scale digital assets comprise millions or billions of documents. Due to such increase, sequential algorithms cannot cope with this data, and parallel and distributed computing become the solution of choice. MapReduce is a programming model proposed by Google for scalable data processing. MapReduce is mainly applicable for data intensive algorithms. In contrast, the message passing interface (MPI) is suitable for high performance algorithms. This paper proposes an adapted structure of the
doi:10.1109/cbmi.2012.6269841
dblp:conf/cbmi/MohamedM12
fatcat:u2zslj5nazg4rnm23cqhrkdc6y