GI-GAC - Artigos: Recent submissions

Now showing items 41-45 of 190

    • Real-time resource scaling platform for Big Data workloads on serverless environments 

      Enes, Jonatan; Expósito, Roberto R.; Touriño, Juan (2020)
      The serverless execution paradigm is becoming an increasingly popular option when workloads are to be deployed in an abstracted way, more specifically, without specifying any infrastructure requirements. Currently, such ...

    • Parallel feature selection for distributed-memory clusters 

      González-Domínguez, Jorge; Bolón-Canedo, Verónica; Freire, Borja; Touriño, Juan (2019)
      [Abstract]: Feature selection is nowadays an extremely important data mining stage in the field of machine learning due to the appearance of problems of high dimensionality. In the literature there are numerous feature ...

    • Interactive Visualization of Large Point Clouds Using an Autotuning Multiresolution Out-Of-Core Strategy 

      Teijeiro, Diego; Amor, Margarita; Doallo, Ramón; Deibe, David (Oxford University Press, 2023)
      [Abstract]: Due to the increasingly large amount of data acquired into point clouds, from LiDAR (Light Detection and Ranging) sensors and 2D/3D sensors, massive point clouds processing has become a topic with high interest ...

    • A Fast Solver for Large Tridiagonal Systems on Multi-Core Processors (Lass Library) 

      Valero-Lara, Pedro; Andrade, Diego; Sirvent, Raül; Labarta, Jesús; Fraguela, Basilio B.; Doallo, Ramón (Institute of Electrical and Electronics Engineers, 2019)
      [Abstract]: Many problems of industrial and scientific interest require the solving of tridiagonal linear systems. This paper presents several implementations for the parallel solving of large tridiagonal systems on ...

    • Parallel-FST: A feature selection library for multicore clusters 

      Beceiro, Bieito; González-Domínguez, Jorge; Touriño, Juan (Elsevier, 2022-11)
      [Abstract]: Feature selection is a subfield of machine learning focused on reducing the dimensionality of datasets by performing a computationally intensive process. This work presents Parallel-FST, a publicly available ...