Enviaments recents

  • Brook GLES Pi: democratising accelerator programming 

    Trompouki, Matina Maria; Kosmidis, Leonidas (Association for Computing Machinery (ACM), 2018-08-10)
    Comunicació de congrés
    Accés obert
    Nowadays computing is heavily-based on accelerators, however, the cost of the hardware equipment prevents equal access to heterogeneous programming. In this work we present Brook GLES Pi, a port of the accelerator programming ...
  • Industrial experiences with resource management under software randomization in ARINC653 avionics environments 

    Kosmidis, Leonidas; Maxim, Cristian; Jegu, Victor; Vatrinet, Francis; Cazorla, Francisco J. (Association for Computing Machinery (ACM), 2018-11-05)
    Comunicació de congrés
    Accés obert
    Injecting randomization in different layers of the computing platform has been shown beneficial for security, resilience to software bugs and timing analysis. In this paper, with focus on the latter, we show our experience ...
  • Exploring the Vision Processing Unit as Co-Processor for Inference 

    Rivas-Gomez, Sergio; Peña, Antonio J.; Moloney, David; Laure, Erwin; Markidis, Stefano (IEEE, 2018-08-06)
    Comunicació de congrés
    Accés obert
    The success of the exascale supercomputer is largely debated to remain dependent on novel breakthroughs in technology that effectively reduce the power consumption and thermal dissipation requirements. In this work, we ...
  • HPC benchmarking: scaling right and looking beyond the average 

    Radulovic, Milan; Asifuzzaman, Kazi; Carpenter, Paul Matthew; Radojkovic, Petar; Ayguadé Parra, Eduard (Springer, 2018)
    Text en actes de congrés
    Accés restringit per política de l'editorial
    Designing a balanced HPC system requires an understanding of the dominant performance bottlenecks. There is as yet no well established methodology for a unified evaluation of HPC systems and workloads that quantifies the ...
  • Performance Characterization of Spark Workloads on Shared NUMA Systems 

    Baig, Shuja-ur-Rehman; Amaral, Marcelo; Polo, Jordà; Carrera, David (IEEE, 2018-07-09)
    Comunicació de congrés
    Accés obert
    As the adoption of Big Data technologies becomes the norm in an increasing number of scenarios, there is also a growing need to optimize them for modern processors. Spark has gained momentum over the last few years among ...
  • LEGaTO: towards energy-efficient, secure, fault-tolerant toolset for heterogeneous computing 

    Cristal, Adrian; Unsal, Osman S.; Martorell, Xavier; Carpenter, Paul; de la Cruz, Raul; Bautista, Leonardo; Jimenez, Daniel; Alvarez, Carlos; Salami, Behzad; Madonar, Sergi; Pericàs, Miquel; Trancoso, Pedro; von dem Berge, Micha; Billung-Meyer, Gunnar; Krupop, Stefan; Christmann, Wolfgang; Klawonn, Frank; Mihklafi, Amani; Becker, Tobias; Gaydadjiev, Georgi; Salomonsson, Hans; Dubhashi, Devdatt; Port, Oron; Etsion, Yoav; Nowack, Vesna; Fetzer, Christof; Hagemeyer, Jens; Jungeblut, Thorsten; Kucza, Nils; Kaiser, Martin; Porrmann, Mario; Pasin, Marcelo; Schiavoni, Valerio; Rocha, Isabelly; Göttel, Christian; Felber, Pascal (Association for Computing Machinery (ACM), 2018-05-08)
    Comunicació de congrés
    Accés obert
    LEGaTO is a three-year EU H2020 project which started in December 2017. The LEGaTO project will leverage task-based programming models to provide a software ecosystem for Made-in-Europe heterogeneous hardware composed of ...
  • RPR: a random replacement policy with limited pathological replacements 

    Benedicte, Pedro; Hernandez, Carles; Abella, Jaume; Cazorla, Francisco J. (Association for Computing Machinery (ACM), 2018-04-13)
    Comunicació de congrés
    Accés obert
    Measurement-Based Probabilistic Timing Analysis (MBPTA) has consolidated as a technique to estimate probabilistic Worst-Case Execution Times (WCET) for critical software running on processors with high-performance hardware ...
  • Computational Fluid and Particle Dynamics Simulations for Respiratory System: Runtime Optimization on an Arm Cluster 

    Garcia-Gasulla, Marta; Josep-Fabrego, Marc; Eguzkitza, Beatriz; Mantovani, Filippo (Association for Computing Machinery (ACM), 2018-08-13)
    Comunicació de congrés
    Accés obert
    Computational fluid and particle dynamics simulations (CFPD) are of paramount importance for studying and improving drug effectiveness. Computational requirements of CFPD codes involves high-performance computing (HPC) ...
  • DROM: Enabling Efficient and Effortless Malleability for Resource Managers 

    D'Amico, Marco; Garcia-Gasulla, Marta; López, Victor; Jokanovic, Ana; Sirvent, Raül; Corbalan, Julita (Association for Computing Machinery (ACM), 2018-08-13)
    Comunicació de congrés
    Accés obert
    In the design of future HPC systems, research in resource management is showing an increasing interest in a more dynamic control of the available resources. It has been proven that enabling the jobs to change the number ...
  • Low-latency multi-threaded ensemble learning for dynamic big data streams 

    Marron, Diego; Ayguadé Parra, Eduard; Herrero Zaragoza, José Ramón; Read, Jesse; Bifet, Albert (Institute of Electrical and Electronics Engineers (IEEE), 2018)
    Text en actes de congrés
    Accés obert
    Real–time mining of evolving data streams involves new challenges when targeting today’s application domains such as the Internet of the Things: increasing volume, velocity and volatility requires data to be processed ...
  • TaskGenX: A Hardware-Software Proposal for Accelerating Task Parallelism 

    Chronaki, Kallia; Casas, Marc; Moreto, Miquel; Bosch, Jaume; Badia, Rosa M. (Springer, 2018-05-29)
    Comunicació de congrés
    Accés obert
    As chip multi-processors (CMPs) are becoming more and more complex, software solutions such as parallel programming models are attracting a lot of attention. Task-based parallel programming models offer an appealing approach ...
  • vMCA: Memory Capacity Aggregation and Management in Cloud Environments 

    Garrido, Luis A.; Carpenter, Paul (IEEE, 2018-05-31)
    Comunicació de congrés
    Accés obert
    In cloud environments, the VMs within the computing nodes generate varying memory demand profiles. When memory utilization reaches its limits due to this, costly (virtual) disk accesses and/or VM migrations can occur. Since ...

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