The Group

The High Performance Computing & Architectures (HPC&A) group is a research group at the University Jaume I (Spain) that works on the optimization of numerical algorithms for general-purpose processors and specific hardware, as well as their parallelization in different systems (clusters of multicores w/wo GPU). The group focuses on the application of high-performance computing techniques to solve problems in control theory, computational chemistry, electromagnetics, aeronautical engineering, and scientific and engineering applications in general. Current interests of the group also include dynamic resource management, power-aware computing, hardware-software co-design, reconfigurable architectures, quantum computing, and the use of HPC to improve cibersecurity, machine learning techniques and deep neural network processing.

Work Lines

  • Solution to linear algebra problems on current high performance processors, hardware accelerators (GPUs and FPGAs), and parallel systems (multicore processors and clusters)
  • Optimisation and tuning of codes and software packages for scientific and engineering applications
  • Hardware-software codesign, computation and reconfigurable architectures
  • Energy-aware computing, approximate computing and fault tolerance
  • High performance computing for machine learning techniques and deep neural networks

Meet our Members

Vacancies

21670 BORSA DE PERSONAL VINCULAT A LA INVESTIGACIÓ. PROJECTES DEL GRUP: HIGH PERFORMANCE COMPUTING & ARCHITECTURES PI

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Latest Publications

Few-View CT Image Reconstruction via Least-Squares Methods: Assessment and Optimization

Mónica Chillarón Pérez, Vicente E. Vidal, Gumersindo J. Verdú, Gregorio Quintana Ortí
NUCLEAR SCIENCE AND ENGINEERING ; Num. 2 Vol. 198 pp. 193-206. (2024). ISSN: 0029-5639

Comparative analysis of soft-error sensitivity in LU decomposition algorithms on diverse GPUs

Germán León Navarro, José Manuel Badia Contelles, José Antonio Belloch Rodriguez, Almudena Lindoso, Luis Entrena
JOURNAL OF SUPERCOMPUTING ; Num. 9 Vol. 80 pp. 12844-12862. (2024). ISSN: 0920-8542

Applying machine learning to assess emotional reactions to video game content streamed on Spanish Twitch channels

Noemí Merayo, Rosalía Cotelo, Rocío Carratalá Sáez, Francisco J. Andújar
COMPUTER SPEECH AND LANGUAGE ; Vol. 88 pp. 1-23. (2024). ISSN: 0885-2308