Recent Submissions

  • Machine learning-based recovery of thermophysical information from velocity data in supercritical fluids turbulence 

    Masclans Serrat, Núria; Vázquez-Novoa, Fernando; Bernades, Marc; Badia Sala, Rosa Maria; Jofre Cruanyes, Lluís (European Research Community on Flow, Turbulence, and Conbustion (ERCOFTAC), 2023)
    Conference report
    Open Access
    Recent research has shown the possibility to achieve microconfined turbulence utilizing supercritical fluids under high-pressure transcritical conditions. This has generated increasing interest in the hybrid nature of the ...
  • Autopsy of Ethereum's post-merge reward system 

    Cortes Goicoechea, Mikel; Mohandas Daryanani, Tarun; Muñoz Tapia, José Luis; Bautista Gómez, Leonardo (Institute of Electrical and Electronics Engineers (IEEE), 2023)
    Conference report
    Open Access
    Like most modern blockchain networks, Ethereum has relied on economic incentives to promote honest participation in the chain's consensus. The distributed character of the platform, together with the "randomness" or "luck" ...
  • SafeLS: An open source implementation of a lockstep NOEL-V RISC-V core 

    Sarraseca Julian, Marcel; Alcaide Portet, Sergi; Fuentes Díaz, Francisco Javier; Rodríguez Rivas, Juan Carlos; Chang, Feng; Lasfar, Ilham; Canal Corretger, Ramon; Cazorla Almeida, Francisco Javier; Abella Ferrer, Jaume (Institute of Electrical and Electronics Engineers (IEEE), 2023)
    Conference report
    Open Access
    Microcontrollers running safety-critical applications with high integrity requirements must provide appropriate safety measures to manage random hardware faults. For instance, automotive safety regulations (e.g., ISO26262) ...
  • Hierarchical management of extreme-scale task-based applications 

    Lordan Gomis, Francesc; Puigdemunt Schmolling, Gabriel; Vergés Boncompte, Pere; Conejero Bañón, Francisco Javier; Ejarque Artigas, Jorge; Badia Sala, Rosa Maria (Springer Cham, 2023)
    Conference report
    Restricted access - publisher's policy
    The scale and heterogeneity of exascale systems increment the complexity of programming applications exploiting them. Task-based approaches with support for nested tasks are a good-fitting model for them because of the ...
  • Scalable random forest with data-parallel computing 

    Vázquez-Novoa, Fernando; Conejero Bañón, Francisco Javier; Tatu, Cristian; Badia Sala, Rosa Maria (Springer Cham, 2023)
    Conference report
    Restricted access - publisher's policy
    In the last years, there has been a significant increment in the quantity of data available and computational resources. This leads scientific and industry communities to pursue more accurate and efficient Machine Learning ...
  • Space Shuttle: A test vehicle for the reliability of the SkyWater 130nm PDK for future space processors 

    Rodríguez Ferrández, Iván; Kosmidis, Leonidas; Tali, Maris; Steenari, David (Institute of Electrical and Electronics Engineers (IEEE), 2023)
    Conference lecture
    Open Access
    Recently the ASIC industry experiences a massive change with more and more small and medium businesses entering the custom ASIC development. This trend is fueled by the recent open hardware movement and relevant government ...
  • Framework for the Analysis and Configuration of Real-Time OpenMP Applications 

    Carvalho, Tiago; Pinho, Luis Miguel; Samadi, Mohammad; Royuela, Sara; Munera, Adrian; Quiñones, Eduardo (Institute of Electrical and Electronics Engineers (IEEE), 2023)
    Conference lecture
    Open Access
    High-performance cyber-physical applications impose several requirements with respect to performance, functional correctness and non-functional aspects. Nowadays, the design of these systems usually follows a model-driven ...
  • A Methodology for Selective Protection of Matrix Multiplications: A Diagnostic Coverage and Performance Trade-off for CNNs Executed on GPUs 

    Fernández, Javier; Agirre, Irune; Perez Cerrolaza, Jon; Abella Ferrer, Jaume; Cazorla Almeida, Francisco Javier (Institute of Electrical and Electronics Engineers (IEEE), 2023)
    Conference lecture
    Open Access
    The ability of CNNs to efficiently and accurately perform complex functions, such as object detection, has fostered their adoption in safety-related autonomous systems. These algorithms require high computational performance ...
  • Adaptation of AI-Accelerated CFD Simulations to the IPU Platform 

    Rościszewski, Paweł; Krzywaniak, Adam; Iserte, Sergio; Rojek, Krzysztof; Gepner, Paweł (Springer International Publishing, 2023)
    Conference lecture
    Restricted access - publisher's policy
    Intelligence Processing Units (IPU) have proven useful for many AI applications. In this paper, we evaluate them within the emerging field of AI for simulation, where traditional numerical simulations are supported by ...
  • Advanced synchronization techniques for task-based runtime systems 

    Álvarez Robert, David; Sala Penadés, Kevin; Maroñas Bravo, Marcos; Roca Nonell, Aleix; Beltran Querol, Vicenç (Association for Computing Machinery (ACM), 2021)
    Conference report
    Open Access
    Task-based programming models like OmpSs-2 and OpenMP provide a flexible data-flow execution model to exploit dynamic, irregular and nested parallelism. Providing an efficient implementation that scales well with small ...
  • Adding preferences and moral values in an agent-based simulation framework for high-performance computing 

    Marin Gutierrez, David; Vázquez Salceda, Javier; Álvarez Napagao, Sergio; Gnatyshak, Dmitry (2023)
    Conference report
    Open Access
    Agent-Based Simulation is a suitable approach used now-a-days to simulate and analyze complex societal environments and scenarios. Current Agent-Based Simulation frameworks either scale quite well in computation but implement ...
  • Explainable agents adapt to human behaviour 

    Tormos Llorente, Adrián; Giménez Ábalos, Víctor; Domènech Vila, Marc; Gnatyshak, Dmitry; Álvarez Napagao, Sergio; Vázquez Salceda, Javier (2023)
    Conference report
    Open Access
    When integrating artificial agents into physical or digital environments that are shared with humans, agents are often equipped with opaque Machine Learning methods to enable adapting their behaviour to dynamic human needs ...

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