Bieito
Beceiro Fernández

Research Publications

1. B. Beceiro, J. González-Domínguez, L. Morán-Fernández, V. Bolón-Canedo and J. Touriño, "CUDA Acceleration of MI-based Feature Selection Methods", Journal of Parallel and Distributed Computing, vol. 190, Aug. 2024, Art. no. 104901. [Online]. Available doi.org/10.1016/j.jpdc.2024.104901.
2. B. Beceiro, J. González-Domínguez and J. Touriño, "Biblioteca Paralela de Selección de Características para Sistemas Clúster", in Actas de las Jornadas SARTECO 2022, Alacant, Spain, Sep. 2022, pp. 23-32. [Online]. Available: doi.org/10.5281/zenodo.7180809.
   Slides: jp22_slides.pdf [es]
3. B. Beceiro, J. González-Domínguez and J. Touriño, "Parallel-FST: a Feature Selection Library for Multicore Clusters", Journal of Parallel and Distributed Computing, vol. 169, pp. 106-116, Nov. 2022. [Online]. Available: doi.org/10.1016/j.jpdc.2022.06.012.
4. B. Beceiro, J. González-Domínguez and J. Touriño, "Acceleration of a Feature Selection Algorithm Using High Performance Computing", in Proceedings 3rd XoveTIC Conference, A Coruña, Spain, Sep. 2020, pp. 171-173. [Online]. Available: doi.org/10.3390/proceedings2020054054.
   Slides: xovetic20_slides.pdf [gl]

Software

• Parallel-FST: Feature Selection Library for Clusters

  Repository parallel-fst

  Specific versions: jpdc21 [code, dockerhub]

  Description:

  

  Parallel Feature Selection toolbox containing several HPC implementations of FS methods. Based on FEAST [G. Brown, A. Pocock, M.-J. Zhao and M. Luján, 2012].

  Parallel-FST contains three implementations:

  • CLI-FEAST a CLI wrapper for the original sequential methods of FEAST
  • MPI-FEAST a hybrid MPI/multithreaded implementation for multicore clusters with CLI
  • cuFEAST a CUDA implementation for single-GPU nodes, as a CUDA library and also with a CLI (currently on development)

  You can find here some GIFs that show the feature selection process when applying MIM, JMI and mRMR to the MNIST dataset.

Short Bio

Bieito Beceiro received the B.S. in Computer Science and the M.S. in High Performance Computing (HPC) from the Universidade da Coruña (UDC), Spain, in 2020 and 2021, respectively.

He is currently a Ph.D. student at the Computer Architecture Group of the UDC. His work is focused on the acceleration of machine learning methods for computational science using HPC techniques.