Recent Submissions

  • Characterization of a coherent hardware accelerator framework for SoCs 

    López Paradís, Guillem; Venu, Balaji; Armejach Sanosa, Adrià; Moreto Planas, Miquel (Springer, 2023)
    Conference report
    Restricted access - publisher's policy
    Accelerators rich architectures have become the standard in today’s SoCs. After Moore’s law diminish, it is common to only dedicate a fraction of the area of the SoC to traditional cores and leave the rest of space for ...
  • Role-shifting threads: Increasing OpenMP malleability to address load imbalance at MPI and OpenMP 

    Criado Ledesma, Joel; López Herrero, Víctor; Vinyals Ylla Català, Joan; Ramirez Miranda, Guillem; Teruel García, Xavier; Garcia Gasulla, Marta (SAGE Publications, 2023-10)
    Article
    Open Access
    This paper presents the evolution of the free agent threads for OpenMP to the new role-shifting threads model and their integration with the Dynamic Load Balancing (DLB) library. We demonstrate how free agent threads can ...
  • On the use of deep learning and computational fluid dynamics for the estimation of uniform momentum source components of propellers 

    Martínez Cuenca, Raúl; Luis Gómez, Jaume; Iserte, Sergio; Chiva, Sergio (Cell Press, 2023-11)
    Article
    Open Access
    This article proposes a novel method based on Deep Learning for the resolution of uniform momentum source terms in the Reynolds-Averaged Navier-Stokes equations. These source terms can represent several industrial devices ...
  • DPU Offloading Programming with the OpenMP API 

    Usman, Muhammad; Iserte, Sergio; Ferrer Ibañez, Roger; Peña, Antonio (Association for Computing Machinery (ACM), 2023-11)
    Conference lecture
    Open Access
    Data processing units (DPUs) as network co-processors are an emerging trend in our community, with plenty of opportunities yet to be explored. These have been generally used as domain-specific accelerators transparent to ...
  • Can we trust undervolting in FPGA-based deep learning designs at harsh conditions? 

    Koc, Fahrettin; Salami, Behzad; Ergin, Oguz; Unsal, Osman Sabri; Cristal Kestelman, Adrián (2022-05)
    Article
    Open Access
    As more Neural Networks on Field Programmable Gate Arrays (FPGAs) are used in a wider context, the importance of power efficiency increases. However, the focus on power should never compromise application accuracy. One ...
  • Quantitative description of metal center organization and interactions in single-atom catalysts 

    Rossi, Kevin; Ruiz Ferrando, Andrea; Faust Akl, Dario; Giménez Ábalos, Víctor; Heras Domingo, Javier; Graux, Romain; Hai, Xiao; Lu, Jiong; Garcia Gasulla, Dario; López Alonso, Nuria; Pérez Ramírez, Javier; Mitchell, Sharon (2023-09-27)
    Article
    Open Access
    Ultra-high-density single-atom catalysts (UHD-SACs) present unique opportunities for harnessing cooperative effects between neighboring metal centers. However, the lack of tools to establish correlations between the density, ...
  • Challenges and opportunities for RISC-V architectures towards genomics-based workloads 

    Gómez Sánchez, Gonzalo; Call Barreiro, Aaron; Teruel García, Xavier; Alonso Parrilla, Lorena; Morán Castany, Ignasi; Pérez Elena, Miguel Ángel; Torrents Arenales, David; Berral García, Josep Lluís (Springer, 2023)
    Part of book or chapter of book
    Open Access
    The use of large-scale supercomputing architectures is a hard requirement for scientific computing Big-Data applications. An example is genomics analytics, where millions of data transformations and tests per patient need ...
  • Enabling HW-based task scheduling in large multicore architectures 

    Morais, Lucas Henrique; Álvarez Martínez, Carlos; Jiménez González, Daniel; Haro Ruiz, Juan Miguel de; Araujo, Guido; Frank, Michael; Goldman, Alfredo; Martorell Bofill, Xavier (Institute of Electrical and Electronics Engineers (IEEE), 2023)
    Article
    Open Access
    Dynamic Task Scheduling is an enticing programming model aiming to ease the development of parallel programs with intrinsically irregular or data-dependent parallelism. The performance of such solutions relies on the ability ...
  • Main sources of variability and non-determinism in AD software: taxonomy and prospects to handle them 

    Alcón Doganoc, Miguel; Brando Guillaumes, Axel; Mezzetti, Enrico; Abella Ferrer, Jaume; Cazorla Almeida, Francisco Javier (Springer Nature, 2023-09)
    Article
    Restricted access - publisher's policy
    Safety standards in domains like automotive and avionics seek for deterministic execution (lack of jittery behavior) as a stepping stone to build a certification argument on the correct timing behavior of the system. ...
  • On discrete symmetries of robotics systems: A group-theoretic and data-driven analysis 

    Ordoñez Apraez, Daniel Felipe; Martín Muñoz, Mario; Agudo Martínez, Antonio; Moreno-Noguer, Francesc (RSS Foundation, 2023)
    Conference report
    Restricted access - publisher's policy
    We present a comprehensive study on discrete morphological symmetries of dynamical systems, which are commonly observed in biological and artificial locomoting systems, such as legged, swimming, and flying animals/robots/virtual ...
  • Performance characterization of multi-container deployment schemes for online learning inference 

    Liu, Peini; Guitart Fernández, Jordi; Taherkordi, Amir (Institute of Electrical and Electronics Engineers (IEEE), 2023)
    Conference lecture
    Open Access
    Online machine learning (ML) inference services provide users with an interactive way to request for predictions in realtime. To meet the notable computational requirements of such services, they are increasingly being ...
  • Assessing biases through visual contexts 

    Arias Duart, Anna; Giménez Ábalos, Víctor; Cortés García, Claudio Ulises; Garcia Gasulla, Dario (2023-07)
    Article
    Open Access
    Bias detection in the computer vision field is a necessary task, to achieve fair models. These biases are usually due to undesirable correlations present in the data and learned by the model. Although explainability can ...

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