• openAccess   Reducing Power Consumption of the LU Factorization with Partial Pivoting on Multi-Core Processors 

      Alonso-Jordá, Pedro; Dolz, Manuel F.; Mayo, Rafael; Quintana-Orti, Enrique S. Departament d' Enginyeria i Ciència dels Computadors, Universitat Jaume I (2011-07)
      In this paper we analyze the trade-off between energy and performance for a data- parallel execution of the LU factorization with partial pivoting on a multi-core proces- sor. To improve power efficiency, we adapt the ...
    • openAccess   Robots Humanoides 

      Falomir, Zoe Departament d' Enginyeria i Ciència dels Computadors, Universitat Jaume I (2006-10)
      This technical report presents a state of the art in humanoid robots based on well-known European researchers' lectures wich took place at 6th International UJI Robotics School (IURS'2006) on Humanoid Robots. Some of the ...
    • openAccess   Sensores de Identificación por Radio-Frecuencia (RFID) 

      Falomir, Zoe Departament d' Enginyeria i Ciència dels Computadors, Universitat Jaume I (2006-10)
      This technical report presents an introduction to radio frequency identification (RFID) sensors and a state of the art in robotics applications where this kind of sensors was used.
    • openAccess   Solving Dense Linear Systems on Graphics Processors 

      Barrachina Mir, Sergio; Castillo Catalán, María Isabel; Igual, Francisco; Mayo, Rafael; Quintana-Orti, Enrique S. Departament d' Enginyeria i Ciència dels Computadors, Universitat Jaume I (2008-02)
      We present several algorithms to compute the solution of a linear system of equations on a GPU, as well as general techniques to improve their performance, such as padding and hybrid GPU-CPU computation. We also show how ...
    • openAccess   Solving “Large” Dense Matrix Problems on Multi-Core Processors and GPUs 

      Marqués-Andrés, Mercedes; Quintana-Ortí, Gregorio; Quintana-Orti, Enrique S.; Van de Geijn, Robert A. Departament d' Enginyeria i Ciència dels Computadors, Universitat Jaume I (2009-01)
      Few realize that, for large matrices, many dense matrix computations achieve nearly the same performance when the matrices are stored on disk as when they are stored in a very large main memory. Similarly, few realize ...