Recent Submissions

  • Integrating HPC, AI, and Workflows for Scientific Data Analysis: report from Dagstuhl Seminar 23352 

    Badia Sala, Rosa Maria; Berti-Equille, Laure; Ferreira da Silva, Rafael; Leser, Ulf (2024-03-29)
    Research report
    Open Access
    The Dagstuhl Seminar 23352, titled “Integrating HPC, AI, and Workflows for Scientific Data Analysis,” held from August 27 to September 1, 2023, was a significant event focusing on the synergy between HighPerformance Computing ...
  • ETP4HPC’s SRA 5 strategic research agenda for High-Performance Computing in Europe 2022: European HPC research priorities 2023-2027 

    Carpenter, Paul Matthew; Casas, Marc; Unsal, Osman Sabri; Radojkovic, Petar; Martorell Bofill, Xavier; Miranda, Alberto; Guitart Fernández, Jordi; Corbalán González, Julita; Peña Monferrer, Antonio José; Bautista Gomez, Leonardo Arturo; Vázquez García, Miguel; Beltran Querol, Vicenç; Queralt Calafat, Anna; Nou Castell, Ramon; Borrell Pol, Ricard; Houzeaux, Guillaume; Serradell Maronda, Kim; Carrera Pérez, David; García Sáez, Artur; Puchol García, Carlos (2022-09)
    Research report
    Open Access
    This document feeds research and development priorities devel-oped by the European HPC ecosystem into EuroHPC’s Research and Innovation Advisory Group with an aim to define the HPC Technology research Work Programme and ...
  • Healthy Twitter discussions? Time will tell 

    Gnatyshak, Dmitry; Garcia Gasulla, Dario; Álvarez Napagao, Sergio; Arjona Martínez, Jamie; Venturini, Tommaso (2022-03-21)
    Research report
    Open Access
    Studying misinformation and how to deal with unhealthy behaviours within online discussions has recently become an important field of research within social studies. With the rapid development of social media, and the ...
  • ExaQUte: D5.2 Release of ExaQUte MLMC Python engine 

    Amela Milian, Ramon; Ayoul-Guilmard, Quentin; Ganesh, Sundar; Tosi, Riccardo; Badia Sala, Rosa Maria; Nobile, Fabio; Rossi, Riccardo (2019-05-30)
    Research report
    Open Access
    In this deliverable, the ExaQUte xmc library is introduced. This report is meant to serve as a supplement to the publicly release of the library. In the following sections, the ExaQUte xmc library is described along with ...
  • ExaQUte: D1.4 Final public release of the solver 

    Ayoul-Guilmard, Quentin; Ganesh, Sundar; Nobile, Fabio; Badia Sala, Rosa Maria; Ejarque, Jorge; Cirrottola, Luca; Froehly, Algiane; Keith, Brendan; Kodakkal, Anoop; Núñez Corbacho, Marc; Roig Pina, Carlos Alejandro; Rossi, Riccardo; Tosi, Riccardo; Soriano Ortiz, Cecilia (2020-11-30)
    Research report
    Open Access
    This deliverable presents the final software release of Kratos Multiphysics, together with the XMC library, Hyperloom and PyCOMPSs API definitions [13]. This release also contains the latest developements on MPI parallel ...
  • ExaQUte: D1.3 First public release of the solver 

    Ayoul-Guilmard, Quentin; Badia Sala, Rosa Maria; Ejarque, Jorge; Ganesh, Sundar; Nobile, Fabio; Núñez Corbacho, Marc; Soriano Ortiz, Cecilia; Roig Pina, Carlos Alejandro; Rossi, Riccardo; Tosi, Riccardo (2020-05-29)
    Research report
    Open Access
    This deliverable presents the software release of Kratos Multiphysics, together with the XMC library, Hyperloom and PyCOMPSs API definition [8]. This report is meant to serve as a supplement to the public release of the ...
  • ExaQUte: D4.2 Profiling report of the partner’s tools, complete with performance suggestions 

    Amela Milian, Ramon; Badia Sala, Rosa Maria; Böhm, Stanislav; Tosi, Riccardo; Rossi, Riccardo (2019-05-30)
    Research report
    Open Access
    This deliverable focuses on the proling activities developed in the project with the partner's applications. To perform this proling activities, a couple of benchmarks were dened in collaboration with WP5. The rst benchmark ...
  • Towards resilient EU HPC systems: A blueprint 

    Radojković, Petar; Marazakis, Manolis; Carpenter, Paul Matthew; Jeyapaul, Reiley; Gizopoulos, Dimitris; Schulz, Martin; Armejach Sanosa, Adrià; Ayguadé Parra, Eduard; Canal Corretger, Ramon; Moretó Planas, Miquel; Salami, Behzad; Unsal, Osman Sabri (2020-04)
    Research report
    Open Access
    This document aims to spearhead a Europe-wide discussion on HPC system resilience and to help the European HPC community define best practices for resilience. We analyse a wide range of state-of-the-art resilience mechanisms ...
  • MetH: A family of high-resolution and variable-shape image challenges 

    Parés Pont, Ferran; Garcia Gasulla, Dario; Servat, Harald; Labarta Mancho, Jesús José; Ayguadé Parra, Eduard (2019-11-20)
    Research report
    Open Access
    High-resolution and variable-shape images have not yet been properly addressed by the AI community. The approach of down-sampling data often used with convolutional neural networks is sub-optimal for many tasks, and has ...
  • Optimizing sparse matrix-vector multiplication in NEC SX-Aurora vector engine 

    Gómez Crespo, Constantino; Casas, Marc; Mantovani, Filippo; Focht, Erich (2020-06-26)
    Research report
    Open Access
    Sparse Matrix-Vector multiplication (SpMV) is an essential piece of code used in many High Performance Computing (HPC) applications. As previous literature shows, achieving efficient vectorization and performance in modern ...
  • TCP Proactive Congestion Control for East–West Trffic: the Marking Threshold 

    Fischer e Silva, Renan; Carpenter, Paul Matthew (Elsevier, 2019-03)
    Working paper
    Open Access
    Various extensions of TCP/IP have been proposed to reduce network latency; examples include Explicit Congestion Notification (ECN), Data Center TCP (DCTCP) and several proposals for Active Queue Management (AQM). Combining ...
  • TensorFlow on state-of-the-art HPC clusters: a machine learning use case 

    Ramirez-Gargallo, Guillem; Garcia-Gasulla, Marta; Mantovani, Filippo (IEEE, 2019)
    Conference lecture
    Open Access
    The recent rapid growth of the data-flow programming paradigm enabled the development of specific architectures, e.g., for machine learning. The most known example is the Tensor Processing Unit (TPU) by Google. Standard ...

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