Enviaments recents

  • Event detection in location-based social networks 

    Capdevila Pujol, Joan; Cerquides, Jesús; Torres Viñals, Jordi (Springer, 2017)
    Capítol de llibre
    Accés restringit per política de l'editorial
    With the advent of social networks and the rise of mobile technologies, users have become ubiquitous sensors capable of monitoring various real-world events in a crowd-sourced manner. Location-based social networks have ...
  • Task-based crowd simulation for heterogeneous architectures 

    Perez, Hugo; Hernandez, Benjamin; Rudomin, Isaac; Ayguadé Parra, Eduard (2016-07-01)
    Capítol de llibre
    Accés restringit per política de l'editorial
    Industry trends in the coming years imply the availability of cluster computing with hundreds to thousands of cores per chip, as well as the use of accelerators. Programming presents a challenge due to this heterogeneous ...
  • AXIOM: a flexible platform for the smart home 

    Giorgi, Roberto; Bettin, Nicola; Gai, Paolo; Martorell Bofill, Xavier; Rizzo, Antonio (Springer, 2016-09-24)
    Capítol de llibre
    Accés restringit per política de l'editorial
    The AXIOM hardware/software platform aims at bringing easy programmability on top of a cluster of processors by using a fast interconnect and FPGA as a basis for building a scalable embedded system. The Smart Home is one ...
  • Scaling DBSCAN-like algorithms for event detection systems in Twitter 

    Capdevila Pujol, Joan; Pericacho, Gonzalo; Torres Viñals, Jordi; Cerquides, Jesús (Springer, 2016-11-25)
    Capítol de llibre
    Accés restringit per política de l'editorial
    The increasing use of mobile social networks has lately transformed news media. Real-world events are nowadays reported in social networks much faster than in traditional channels. As a result, the autonomous detection of ...
  • On the representativeness of convolutional neural networks layers 

    García Gasulla, Darío; Moreno, Jonatan; Ramos-Pollan, Raúl; Casadiegos Barrios, Romel; Béjar Alonso, Javier; Cortés García, Claudio Ulises; Ayguadé Parra, Eduard; Labarta Mancho, Jesús José; Suzumura, Toyotaro (IOS PRESS EBOOKS, 2016)
    Capítol de llibre
    Accés obert
    Convolutional Neural Networks (CNN) are the most popular of deep network models due to their applicability and success in image processing. Although plenty of effort has been made in designing and training better discriminative ...
  • Multiple target task sharing support for the OpenMP accelerator model 

    Ozen, Guray; Mateo, Sergi; Ayguadé Parra, Eduard; Labarta, Jesús; Beyer, James B. (Springer, 2016)
    Text en actes de congrés
    Accés restringit per política de l'editorial
    The use of GPU accelerators is becoming common in HPC platforms due to the their effective performance and energy efficiency. In addition, new generations of multicore processors are being designed with wider vector units ...
  • The secrets of the accelerators unveiled: tracing heterogeneous executions through OMPT 

    Llort, German; Filgueras Izquierdo, Antonio; Jiménez-González, Daniel; Servat, Harald; Teruel, Xavier; Mercadal, Estanislao; Álvarez, Carlos; Giménez, Judit; Martorell Bofill, Xavier; Ayguadé Parra, Eduard; Labarta, Jesús (Springer, 2016)
    Text en actes de congrés
    Accés restringit per política de l'editorial
    Heterogeneous systems are an important trend in the future of supercomputers, yet they can be hard to program and developers still lack powerful tools to gain understanding about how well their accelerated codes perform ...
  • Chapter One – An Overview of Architecture-Level Power- and Energy-Efficient Design Techniques 

    Ratković, Ivan; Bežanić, Nikola; Unsal, Osma S.; Cristal, Adrian; Milutinović, Veljko (Elsevier, 2015)
    Capítol de llibre
    Accés obert
    Power dissipation and energy consumption became the primary design constraint for almost all computer systems in the last 15 years. Both computer architects and circuit designers intent to reduce power and energy (without ...

Mostra'n més