Recent Submissions

  • TrackSign: guided Web tracking discovery 

    Castell Uroz, Ismael; Solé Pareta, Josep; Barlet Ros, Pere (Institute of Electrical and Electronics Engineers (IEEE), 2021)
    Conference report
    Open Access
    Current web tracking practices pose a constant threat to the privacy of Internet users. As a result, the research community has recently proposed different tools to combat well-known tracking methods. However, the early ...
  • Enhancing OpenMP tasking model: performance and portability 

    Yu, Chenle; Royuela Alcázar, Sara; Quiñones Moreno, Eduardo (Springer, 2021)
    Conference report
    Open Access
    OpenMP, as the de-facto standard programming model in symmetric multiprocessing for HPC, has seen its performance boosted continuously by the community, either through implementation enhancements or specification augmentations. ...
  • Understanding power consumption and reliability of high-bandwidth memory with voltage underscaling 

    Nabavilarimi, Seyed Saber; Salami, Behzad; Unsal, Osman Sabri; Cristal Kestelman, Adrián; Sarbazi-Azad, Hamid; Mutlu, Onur (Institute of Electrical and Electronics Engineers (IEEE), 2021)
    Conference report
    Open Access
    Modern computing devices employ High-Bandwidth Memory (HBM) to meet their memory bandwidth requirements. An HBM-enabled device consists of multiple DRAM layers stacked on top of one another next to a compute chip (e.g, ...
  • Efficiently running SpMV on long vector architectures 

    Gómez Crespo, Constantino; Mantovani, Filippo; Focht, Erich; Casas Guix, Marc (Association for Computing Machinery (ACM), 2021)
    Conference report
    Restricted access - publisher's policy
    Sparse Matrix-Vector multiplication (SpMV) is an essential kernel for parallel numerical applications. SpMV displays sparse and irregular data accesses, which complicate its vectorization. Such difficulties make SpMV to ...
  • Empirical evidence for MPSoCs in critical systems: The case of NXP’s T2080 cache coherence 

    Pujol Torramorell, Roger; Tabani, Hamid; Abella Ferrer, Jaume; Hassan, Mohamed; Cazorla Almeida, Francisco Javier (IEEE, 2021)
    Conference lecture
    Open Access
    The adoption of complex MPSoCs in critical real-time embedded systems mandates a detailed analysis their architecture to facilitate certification. This analysis is hindered by the lack of a thorough understanding of the ...
  • The UP2DATE baseline research platforms 

    Jover Álvarez, Álvaro; Calderón Torres, Alejandro Josué; Rodríguez Ferrández, Iván; Kosmidis, Leonidas; Asifuzzaman, Kazi; Uven, Patrick; Gruttner, Kim; Poggi, Tomaso; Agirre, Irune (IEEE, 2021)
    Conference report
    Open Access
    The UP2DATE H2020 project focuses on highperformance heterogeneous embedded platforms for critical systems. We will develop observability and controllability solutions to support online updates while ensuring safety and ...
  • GPU4S: Major project outcomes, lessons learnt and way forward 

    Kosmidis, Leonidas; Rodríguez Ferrández, Iván; Jover Álvarez, Álvaro; Alcaide Portet, Sergi; Lachaize, Jérôme; Notebaert, Olivier; Certain, Antoine; Steenari, David (IEEE, 2021)
    Conference report
    Open Access
    Embedded GPUs have been identified from both private and government space agencies as promising hardware technologies to satisfy the increased needs of payload processing. The GPU4S (GPU for Space) project funded from the ...
  • An oracle for guiding large-scale model/hybrid parallel training of convolutional neural networks 

    Njoroge Kahira, Albert; Nguyen, Truong Thao; Bautista Gomez, Leonardo; Takano, Ryousei; Badia Sala, Rosa Maria; Wahib, Mohamed (Association for Computing Machinery (ACM), 2021)
    Conference report
    Open Access
    Deep Neural Network (DNN) frameworks use distributed training to enable faster time to convergence and alleviate memory capacity limitations when training large models and/or using high dimension inputs. With the steady ...
  • Architecting more than Moore: wireless plasticity for massive heterogeneous computer architectures (WiPLASH) 

    Klein, Joshua; Levisse, Alexandre; Ansaloni, Giovanni; Atienza Alonso, David; Zapater Sancho, Marina; Dazzi, Martino; Karunaratne, Geethan; Boybat, Irem; Sebastian, Abu; Rossi, Davide; Jain, Akshay; Guirado Liñan, Robert; Taghvaee, Hamidreza; Abadal Cavallé, Sergi (Association for Computing Machinery (ACM), 2021)
    Conference report
    Open Access
    This paper presents the research directions pursued by the WiPLASH European project, pioneering on-chip wireless communications as a disruptive enabler towards next-generation computing systems for artificial intelligence ...
  • PLANAR: a programmable accelerator for near-memory data rearrangement 

    Barredo Ferreira, Adrián; Armejach Sanosa, Adrià; Beard, Jonathan C.; Moreto Planas, Miquel (Association for Computing Machinery (ACM), 2021)
    Conference report
    Open Access
    Many applications employ irregular and sparse memory accesses that cannot take advantage of existing cache hierarchies in high performance processors. To solve this problem, Data Layout Transformation (DLT) techniques ...
  • Applying interposition techniques for performance analysis of OPENMP parallel applications 

    González Tallada, Marc; Serra, Albert; Martorell Bofill, Xavier; Oliver Segura, José; Ayguadé Parra, Eduard; Labarta Mancho, Jesús José; Navarro, Nacho (Institute of Electrical and Electronics Engineers (IEEE), 2000)
    Conference report
    Open Access
    Tuning parallel applications requires the use of effective tools for detecting performance bottlenecks. Along a parallel program execution, many individual situations of performance degradation may arise. We believe that ...
  • VIA: A smart scratchpad for vector units with application to sparse matrix computations 

    Pavón Rivera, Julián; Vargas Valdivieso, Iván; Barredo Ferreira, Adrián; Marimon Illana, Joan; Moreto Planas, Miquel; Moll Echeto, Francisco de Borja; Unsal, Osman Sabri; Valero Cortés, Mateo; Cristal Kestelman, Adrián (Institute of Electrical and Electronics Engineers (IEEE), 2021)
    Conference report
    Open Access
    Sparse matrix operations are critical kernels in multiple application domains such as High Performance Computing, artificial intelligence and big data. Vector processing is widely used to improve performance on mathematical ...

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