• Adaptive request scheduling for the I/O forwarding layer using reinforcement learning 

      Bez, Jean Luca; Zanon Boito, Francieli; Nou Castell, Ramon; Miranda Bueno, Alberto; Cortés, Toni; Navaux, Philippe O.A. (Elsevier, 2020-11)
      Article
      Accés obert
      In this paper, we propose an approach to adapt the I/O forwarding layer of HPC systems to applications’ access patterns. I/O optimization techniques can improve performance for the access patterns they were designed to ...
    • Auto-tuning of RRM parameters in UMTS networks. Feasibility study. 

      Andújar Linares, Aurora (Universitat Politècnica de Catalunya, 2007-11-22)
      Projecte Final de Màster Oficial
      Accés obert
      The present PFC is located inside the framework of the UMTS networks, and more specifically in the development of new Radio Resource Management (RRM) algorithms capable to maximize the capacity and the performance of the ...
    • sLASs: a fully automatic auto-tuned linear algebra library based on OpenMP extensions implemented in OmpSs (LASs Library) 

      Valero Lara, Pedro; Catalán Pallarés, Sandra; Martorell Bofill, Xavier; Usui, Tetsuzo; Labarta Mancho, Jesús José (Elsevier, 2020-04-01)
      Article
      Accés obert
      In this work we have implemented a novel Linear Algebra Library on top of the task-based runtime OmpSs-2. We have used some of the most advanced OmpSs-2 features; weak dependencies and regions, together with the final ...
    • Towards an auto-tuned and task-based SpMV (LASs Library) 

      Catalán Pallarés, Sandra; Usui, Tetsuzo; Toledo, Leonel; Martorell Bofill, Xavier; Labarta Mancho, Jesús José; Valero Lara, Pedro (Springer, 2020)
      Text en actes de congrés
      Accés obert
      We present a novel approach to parallelize the SpMV kernel included in LASs (Linear Algebra routines on OmpSs) library, after a deep review and analysis of several well-known approaches. LASs is based on OmpSs, a task-based ...