Listar GI-GAC - Artigos por autor "Veiga, Jorge"

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    • Analysis and evaluation of MapReduce solutions on an HPC cluster 

      Veiga, Jorge; Expósito, Roberto R.; Taboada, Guillermo L.; Touriño, Juan (Pergamon Press, 2016-02)
      [Abstract] The ever growing needs of Big Data applications are demanding challenging capabilities which cannot be handled easily by traditional systems, and thus more and more organizations are adopting High Performance ...

    • BDEv 3.0: energy efficiency and microarchitectural characterization of Big Data processing frameworks 

      Veiga, Jorge; Enes, Jonatan; Expósito, Roberto R.; Touriño, Juan (Elsevier BV * North-Holland, 2018-09)
      [Abstract] As the size of Big Data workloads keeps increasing, the evaluation of distributed frameworks becomes a crucial task in order to identify potential performance bottlenecks that may delay the processing of large ...

    • Flame-MR: An event-driven architecture for MapReduce applications 

      Veiga, Jorge; Expósito, Roberto R.; Taboada, Guillermo L.; Touriño, Juan (Elsevier BV * North-Holland, 2016)
      [Abstract] Nowadays, many organizations analyze their data with the MapReduce paradigm, most of them using the popular Apache Hadoop framework. As the data size managed by MapReduce applications is steadily increasing, the ...

    • MarDRe: efficient MapReduce-based removal of duplicate DNA reads in the cloud 

      Expósito, Roberto R.; Veiga, Jorge; González-Domínguez, Jorge; Touriño, Juan (Oxford University Press, 2017)
      [Abstract] This article presents MarDRe, a de novo cloud-ready duplicate and near-duplicate removal tool that can process single- and paired-end reads from FASTQ/FASTA datasets. MarDRe takes advantage of the widely adopted ...

    • Optimization of Real-World MapReduce Applications With Flame-MR: Practical Use Cases 

      Veiga, Jorge; Expósito, Roberto R.; Raffin, Bruno; Touriño, Juan (Institute of Electrical and Electronics Engineers, 2018-11-12)
      [Abstract] Apache Hadoop is a widely used MapReduce framework for storing and processing large amounts of data. However, it presents some performance issues that hinder its utilization in many practical use cases. Although ...