Recent Submissions

  • Building graph representations of deep vector embeddings 

    Garcia Gasulla, Dario; Vilalta Arias, Armand; Parés Pont, Ferran; Moreno Vázquez, Jonatan; Ayguadé Parra, Eduard; Labarta Mancho, Jesús José; Cortés García, Claudio Ulises; Suzumura, Toyotaro (Association for Computational Linguistics, 2017)
    Conference lecture
    Open Access
    Patterns stored within pre-trained deep neural networks compose large and powerful descriptive languages that can be used for many different purposes. Typically, deep network representations are implemented within vector ...
  • Full-network embedding in a multimodal embedding pipeline 

    Vilalta Arias, Armand; Garcia Gasulla, Dario; Parés Pont, Ferran; Moreno Vázquez, Jonatan; Ayguadé Parra, Eduard; Labarta Mancho, Jesús José; Cortés García, Claudio Ulises; Suzumura, Toyotaro (Association for Computational Linguistics, 2017)
    Conference lecture
    Open Access
    The current state-of-the-art for image annotation and image retrieval tasks is obtained through deep neural networks, which combine an image representation and a text representation into a shared embedding space. In this ...
  • RICH: implementing reductions in the cache hierarchy 

    Dimic, Vladimir; Moreto Planas, Miquel; Casas Guix, Marc; Ciesko, Jan; Valero Cortés, Mateo (Association for Computing Machinery (ACM), 2020)
    Conference report
    Open Access
    Reductions constitute a frequent algorithmic pattern in high-performance and scientific computing. Sophisticated techniques are needed to ensure their correct and scalable concurrent execution on modern processors. Reductions ...
  • Modeling and optimizing NUMA effects and prefetching with machine learning 

    Sánchez Barrera, Isaac; Black-Schaffer, David; Casas Guix, Marc; Moreto Planas, Miquel; Stupnikova, Anastasiia; Popov, Mihail (Association for Computing Machinery (ACM), 2020)
    Conference report
    Open Access
    Both NUMA thread/data placement and hardware prefetcher configuration have significant impacts on HPC performance. Optimizing both together leads to a large and complex design space that has previously been impractical to ...
  • Improving accuracy and speeding up document image classification through parallel systems 

    Ferrando Monsonís, Javier; Domínguez, Juan Luis; Torres Viñals, Jordi; García Fuentes, Raul; García Doménech, David; Garrido Miñambres, Daniel; Cortada, Jordi; Valero Cortés, Mateo (Springer, 2020)
    Conference report
    Open Access
    This paper presents a study showing the benefits of the EfficientNet models compared with heavier Convolutional Neural Networks (CNNs) in the Document Classification task, essential problem in the digitalization process ...
  • LEGaTO: Low-energy, secure, and resilient toolset for heterogeneous computing 

    Salami, Behzad; Parasyris, Konstantinos; Cristal Kestelman, Adrián; Unsal, Osman Sabri; Martorell Bofill, Xavier; Carpenter, Paul Matthew; De la Cruz Martínez, Raul; Bautista Gomez, Leonardo Arturo; Jiménez González, Daniel; Álvarez Martínez, Carlos; Nabavilarimi, Seyed Saber; Madonar Soria, Sergi (Institute of Electrical and Electronics Engineers (IEEE), 2020)
    Conference report
    Open Access
    The LEGaTO project leverages task-based programming models to provide a software ecosystem for Made in-Europe heterogeneous hardware composed of CPUs, GPUs, FPGAs and dataflow engines. The aim is to attain one order of ...
  • Adding tightly-integrated task scheduling acceleration to a RISC-V multi-core processor 

    Morais, Lucas; Silva, Vitor; Goldman, Alfredo; Álvarez Martínez, Carlos; Bosch Pons, Jaume; Frank, Michael; Araujo, Guido (Association for Computing Machinery (ACM), 2019)
    Conference report
    Open Access
    Task Parallelism is a parallel programming model that provides code annotation constructs to outline tasks and describe how their pointer parameters are accessed so that they might be executed in parallel, and asynchronously, ...
  • Enabling hardware randomization across the cache hierarchy in Linux-Class processors 

    Doblas, Max; Kostalabros, Ioannis-Vatistas; Moreto Planas, Miquel; Hernández Luz, Carles (2020)
    Conference report
    Open Access
    The most promising secure-cache design approaches use cache-set randomization to index cache contents thus thwarting cache side-channel attacks. Unfortunately, existing randomization proposals cannot be sucessfully applied ...
  • Workflow environments for advanced cyberinfrastructure platforms 

    Badia Sala, Rosa Maria; Ejarque Artigas, Jorge; Lordan Gomis, Francesc; Lezzi, Daniele; Conejero Bañón, Javier; Álvarez Cid-Fuentes, Javier; Becerra Fontal, Yolanda; Queralt Calafat, Anna (Institute of Electrical and Electronics Engineers (IEEE), 2019)
    Conference report
    Open Access
    Progress in science is deeply bound to the effective use of high-performance computing infrastructures and to the efficient extraction of knowledge from vast amounts of data. Such data comes from different sources that ...
  • Main memory latency simulation: the missing link 

    Sánchez Verdejo, Rommel; Asifuzzaman, Kazi; Radulović, Milan; Radojkovic, Petar; Ayguadé Parra, Eduard; Jacob, Bruce (Association for Computing Machinery (ACM), 2018)
    Conference report
    Open Access
    The community accepted the need for a detailed simulation of main memory. Currently, the CPU simulators are usually coupled with the cycle-accurate main memory simulators. However, coupling CPU and memory simulators is not ...
  • Peachy Parallel Assignments (EduHPC 2018) 

    Ayguadé Parra, Eduard; Álvarez Martí, Lluc; Banchelli Gracia, Fabio; Burtscher, Martin; González Escribano, Arturo; Gutiérrez Monge, Julián; Joiner, David A.; Kaeli, David; Previlon, Fritz; Rodríguez Gutiez, Eduardo; Bunde, David P. (Institute of Electrical and Electronics Engineers (IEEE), 2018)
    Conference report
    Open Access
    Peachy Parallel Assignments are a resource for instructors teaching parallel and distributed programming. These are high-quality assignments, previously tested in class, that are readily adoptable. This collection of ...
  • Tailwind: Fast and atomic RDMA-based replication 

    Taleb, Yacine; Stutsman, Ryan; Antoniu, Gabriel; Cortés, Toni (USENIX Association, 2018)
    Conference report
    Open Access
    Replication is essential for fault-tolerance. However, in in-memory systems, it is a source of high overhead. Remote direct memory access (RDMA) is attractive to create redundant copies of data, since it is low-latency and ...

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