Mostrando ítems 46-50 de 192

    • 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 ...
    • PATO: genome-wide prediction of lncRNA-DNA triple helices 

      Amatria Barral, Iñaki; González-Domínguez, Jorge; Touriño, Juan (Oxford University Press, 2023-03)
      [Abstract]: Motivation: Long non-coding RNA (lncRNA) plays a key role in many biological processes. For instance, lncRNA regulates chromatin using different molecular mechanisms, including direct RNA-DNA hybridization via ...
    • Implementation of a motion estimation algorithm for Intel FPGAs using OpenCL 

      Castro, Manuel de; Osorio, Roberto; López Vilariño, David; González-Escribano, Arturo; Llanos, Diego R. (Springer, 2023)
      [Abstract]: Motion Estimation is one of the main tasks behind any video encoder. It is a computationally costly task; therefore, it is usually delegated to specific or reconfigurable hardware, such as FPGAs. Over the years, ...
    • A pipeline architecture for feature-based unsupervised clustering using multivariate time series from HPC jobs 

      Enes, Jonatan; Expósito, Roberto R.; Fuentes Rodríguez, Jose; López Cacheiro, Javier; Touriño, Juan (Elsevier B.V., 2023-05)
      [Abstract]: Time series are key across industrial and research areas for their ability to model behaviour across time, making them ideal for a wide range of use cases such as event monitoring, trend prediction or anomaly ...