Recent Submissions

  • Omega-Test: A predictive early-Z culling to improve the graphics pipeline energy-efficiency 

    Corbalán Navarro, David; Aragón Alcaraz, Juan Luis; Anglada Sánchez, Martí; Lucas Casamayor, Enrique de; Parcerisa Bundó, Joan Manuel; González Colás, Antonio María (2021-06-09)
    Article
    Open Access
    The most common task of GPUs is to render images in real time. When rendering a 3D scene, a key step is to determine which parts of every object are visible in the final image. There are different approaches to solve the ...
  • Pronóstico de capacidad efectiva y prestaciones en una cache no volátil de último nivel 

    Escuín Blasco, Carlos; Monreal Arnal, Teresa; Llaberia Griñó, José M.; Ibáñez Marín, Pablo Enrique; Viñals Yúfera, Victor (Sociedad de Arquitectura y Tecnología de Computadores (SARTECO), 2021)
    Conference report
    Open Access
    La degradación debida a las escrituras que sufren las bitcells implementadas con tecnologi´as de memoria no volátil (NVM) es uno de los principales escollos que se presentan a la hora de construir la cache de último nivel ...
  • Results and achievements of the ALLIANCE Project: New network solutions for 5G and beyond 

    Careglio, Davide; Spadaro, Salvatore; Cabellos Aparicio, Alberto; Lázaro Villa, José Antonio; Barlet Ros, Pere; Gené Bernaus, Joan M.; Perelló Muntan, Jordi; Agraz Bujan, Fernando; Suárez-Varela Maciá, José Rafael; Pagès Raventós, Albert; Paillissé Vilanova, Jordi; Almasan Puscas, Felician Paul; Domingo Pascual, Jordi; Solé Pareta, Josep (Multidisciplinary Digital Publishing Institute, 2021-09-30)
    Article
    Open Access
    Leaving the current 4th generation of mobile communications behind, 5G will represent a disruptive paradigm shift integrating 5G Radio Access Networks (RANs), ultra-high-capacity access/metro/core optical networks, and ...
  • MoRS: An approximate fault modelling framework for reduced-voltage SRAMs 

    Yuksel, Ismail Emir; Salami, Behzad; Ergin, Oguz; Unsal, Osman Sabri; Cristal Kestelman, Adrián (2021)
    Article
    Open Access
    On-chip memory (usually based on Static RAMs-SRAMs) are crucial components for various computing devices including heterogeneous devices, e.g, GPUs, FPGAs, ASICs to achieve high performance. Modern workloads such as Deep ...
  • Tools for embedding and assessing sustainable development goals in engineering education 

    Sánchez Carracedo, Fermín; Segalàs Coral, Jordi; Bueno Mendieta, Gorka; Busquets Rubio, Pere; Climent Vilaró, Joan; Garcia Galofré, Victor; Lazzarini, Boris; López Álvarez, David; Martín Escofet, Carme; Miñano Rubio, Rafael; Sáez de Cámara Oleaga, Estíbaliz; Sureda Carbonell, Bàrbara; Tejedor Papell, Gemma; Vidal López, Eva María (Multidisciplinary Digital Publishing Institute (MDPI), 2021-11-03)
    Article
    Open Access
    This paper presents three tools developed within the framework of the project EDINSOST2-SDG, aimed at embedding and assessing the Education for Sustainable Development (ESD) in Engineering curricula. ESD is promoted through ...
  • Recurrent autoencoder with skip connections and exogenous variables for traffic forecasting 

    Herruzo Sánchez, Pedro; Larriba Pey, Josep (Proceedings of Machine Learning Research (PMLR), 2020)
    Conference lecture
    Open Access
    The increasing complexity of mobility plus the growing population in cities, together with the importance of privacy when sharing data from vehicles or any device, makes traffic forecasting that uses data from infrastructure ...
  • Microarchitectural design-space exploration of an in-order RISC-V processor in a 22nm CMOS technology 

    Doblas Font, Max; Wright, Andrew; Sonmez, Nehir; Moreto Planas, Miquel; Arvind (European Network of Excellence on High Performance and Embedded Architecture and Compilation (HiPEAC), 2021)
    Conference lecture
    Open Access
    The purpose of this paper is to explore the trade-offs between IPC and maximum clock frequency in an in-order processor design. This work evaluates the impact on the performance and frequency of different pipeline ...
  • An oracle for guiding large-scale model/hybrid parallel training of convolutional neural networks 

    Njoroge Kahira, Albert; Nguyen, Truong Thao; Bautista Gomez, Leonardo Arturo; Takano, Ryousei; Badia Sala, Rosa Maria; Wahib, Mohamed (European Network of Excellence on High Performance and Embedded Architecture and Compilation (HiPEAC), 2021)
    Conference lecture
    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 ...
  • PrioRAT: criticality-driven prioritization inside the on-chip memory hierarchy 

    Dimic, Vladimir; Moreto Planas, Miquel; Casas Guix, Marc; Valero Cortés, Mateo (Springer Nature, 2021)
    Conference report
    Open Access
    The ever-increasing gap between the processor and main memory speeds requires careful utilization of the limited memory link. This is additionally emphasized for the case of memory-bound applications. Prioritization of ...
  • On-device training of machine learning models on microcontrollers with a look at federated learning 

    Monfort Grau, Marc; Pueyo Centelles, Roger; Freitag, Fèlix (Association for Computing Machinery (ACM), 2021)
    Conference report
    Open Access
    Recent progress in machine learning frameworks makes it now possible to run an inference with sophisticated machine learning models on tiny microcontrollers. Model training, however, is typically done separately on powerful ...
  • How2Sign: A large-scale multimodal dataset for continuous American sign language 

    Cardoso Duarte, Amanda; Palaskar, Shruti; Ventura Ripol, Lucas; Ghadiyaram, Deepti; DeHaan, Kenneth; Metze, Florian; Torres Viñals, Jordi; Giró Nieto, Xavier (Institute of Electrical and Electronics Engineers (IEEE), 2021)
    Conference lecture
    Open Access
    One of the factors that have hindered progress in the areas of sign language recognition, translation, and production is the absence of large annotated datasets. Towards this end, we introduce How2Sign, a multimodal and ...
  • Characterizing self-driving tasks in general-purpose architectures 

    Exenberger Becker, Pedro Henrique; Arnau Montañés, José María; González Colás, Antonio María (European Network of Excellence on High Performance and Embedded Architecture and Compilation (HiPEAC), 2021-09-15)
    Part of book or chapter of book
    Open Access
    Autonomous Vehicles (AVs) have the potential to radically change the automotive industry. How- ever, computing solutions for AVs have to meet severe performance constraints to guarantee a safe driving experience. Current ...

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