Recent Submissions

  • Heuristic-based task-to-thread mapping in multi-core processors 

    Samadi Gharajeh, Mohammad; Royuela Alcázar, Sara; Pinho, Luis Miguel; Carvalho, Tiago; Quiñones Moreno, Eduardo (Institute of Electrical and Electronics Engineers (IEEE), 2022)
    Conference report
    Open Access
    OpenMP can be used in real-time applications to enhance system performance. However, predictability of OpenMP applications is still a challenge. This paper investigates heuristics for the mapping of OpenMP task graphs in ...
  • OmpSs-2@Cluster: Distributed memory execution of nested OpenMP-style tasks 

    Aguilar Mena, Jimmy; Ali, Omar Shaaban Ibrahim; Beltran Querol, Vicenç; Carpenter, Paul Matthew; Ayguadé Parra, Eduard; Labarta Mancho, Jesús José (Springer Nature, 2022)
    Conference report
    Restricted access - publisher's policy
    State-of-the-art programming approaches generally have a strict division between intra-node shared memory parallelism and inter-node MPI communication. Tasking with dependencies offers a clean, dependable abstraction for ...
  • Sliding window support for image processing in autonomous vehicles 

    Taranco Serna, Raúl; Arnau Montañés, José María; González Colás, Antonio María (2022)
    Conference report
    Open Access
    Camera-based autonomous driving extensively ma-nipulates images for object detection, object tracking, or camera-based localization tasks. Therefore, efficient and fast image processing is crucial in those systems. ...
  • Functional and timing implications of transient faults in critical systems 

    Kritikakou, Angeliki; Nikolaou, Panagiota; Rodríguez Ferrández, Iván; Paturel, Joseph; Kosmidis, Leonidas; Michael, Maria K.; Sentieys, Olivier; Steenari, David (Institute of Electrical and Electronics Engineers (IEEE), 2022)
    Conference report
    Open Access
    Embedded systems in critical domains, such as auto-motive, aviation, space domains, are often required to guarantee both functional and temporal correctness. Considering transient faults, fault analysis and mitigation ...
  • Sources of single event effects in the NVIDIA Xavier SoC family under proton irradiation 

    Rodríguez Ferrández, Iván; Tali, Maris; Kosmidis, Leonidas; Rovituso, Marta; Steenari, David (Institute of Electrical and Electronics Engineers (IEEE), 2022)
    Conference report
    Open Access
    In this paper we characterise two embedded GPU devices from the NVIDIA Xavier family System-on-Chip (SoC) using a proton beam. We compare the NVIDIA Xavier NX and Industrial devices, that respectively target commercial and ...
  • DTexL: Decoupled raster pipeline for texture locality 

    Joseph, Diya; Aragón Alcaraz, Juan Luis; Parcerisa Bundó, Joan Manuel; González Colás, Antonio María (Institute of Electrical and Electronics Engineers (IEEE), 2022)
    Conference report
    Open Access
    Contemporary GPU architectures have multiple shader cores and a scheduler that distributes work (threads) among them, focusing on load balancing. These load balancing techniques favor thread distributions that are detrimental ...
  • End-to-end QoS for the open source safety-relevant RISC-V SELENE platform 

    Andreu Cerezo, Pablo; Hernández Luz, Carles; Picornell Sanjuan, Tomás; López Rodríguez, Pedro; Alcaide Portet, Sergi; Bas Jalón, Francisco; Benedicte Illescas, Pedro; Chang, Feng; Cabo Pitarch, Guillem; Fuentes Díaz, Francisco Javier; Abella Ferrer, Jaume (arXiv, 2022)
    Conference report
    Open Access
    This paper presents the end-to-end QoS approach to provide performance guarantees followed in the SELENEplatform, a high-performance RISC-V based heterogeneous SoC for safety-related real-time systems. Our QoS approach ...
  • Human-in-the-loop online multi-agent approach to increase trustworthiness in ML models through trust scores and data augmentation 

    Bravo Rocca, Gusseppe Jesus; Liu, Peini; Guitart Fernández, Jordi; Dholakia, Ajay; Ellison, David; Hodak, Miroslav (Institute of Electrical and Electronics Engineers (IEEE), 2022)
    Conference lecture
    Open Access
    Increasing a ML model accuracy is not enough, we must also increase its trustworthiness. This is an important step for building resilient AI systems for safety-critical applications such as automotive, finance, and healthcare. ...
  • SafeSoftDR: A library to enable software-based diverse redundancy for safety-critical tasks 

    Mazzocchetti, Fabio; Alcaide Portet, Sergi; Bas Jalón, Francisco; Benedicte Illescas, Pedro; Cabo Pitarch, Guillem; Chang, Feng; Fuentes Díaz, Francisco Javier; Abella Ferrer, Jaume (arXiv, 2022)
    Conference report
    Open Access
    Applications with safety requirements have become ubiquitous nowadays and can be found in edge devices of all kinds. However, microcontrollers in those devices, despite offering moderate performance by implementing multicores ...
  • OmpSs@cloudFPGA: An FPGA task-based programming model with message passing 

    Haro Ruiz, Juan Miguel de; Cano, Rubén; Álvarez Martínez, Carlos; Jiménez González, Daniel; Martorell Bofill, Xavier; Ayguadé Parra, Eduard; Labarta Mancho, Jesús José; Abel, François; Ringlein, Burkhard; Weiss, Beat (Institute of Electrical and Electronics Engineers (IEEE), 2022)
    Conference report
    Open Access
    Nowadays, a new parallel paradigm for energy-efficient heterogeneous hardware infrastructures is required to achieve better performance at a reasonable cost on high-performance computing applications. Under this new paradigm, ...
  • RouteNet-Erlang: A graph neural network for network performance evaluation 

    Ferriol Galmés, Miquel; Rusek, Krzysztof; Suárez-Varela Maciá, José Rafael; Xiao, Shihan; Shi, Xiang; Cheng, Xiangle; Wu, Bo; Barlet Ros, Pere; Cabellos Aparicio, Alberto (Institute of Electrical and Electronics Engineers (IEEE), 2022)
    Conference report
    Open Access
    Network modeling is a fundamental tool in network research, design, and operation. Arguably the most popular method for modeling is Queuing Theory (QT). Its main limitation is that it imposes strong assumptions on the ...
  • Accelerating deep reinforcement learning for digital twin network optimization with evolutionary strategies 

    Güemes Palau, Carlos; Almasan Puscas, Felician Paul; Xiao, Shihan; Cheng, Xiangle; Shi, Xiang; Barlet Ros, Pere; Cabellos Aparicio, Alberto (Institute of Electrical and Electronics Engineers (IEEE), 2022)
    Conference report
    Open Access
    The recent growth of emergent network applications (e.g., satellite networks, vehicular networks) is increasing the complexity of managing modern communication networks. As a result, the community proposed the Digital Twin ...

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