• PRACE Training events

  • The PRACE RI is open to all European researchers affiliated with recognized European academic institutions and industries.

    The aim of PRACE RI Training is to provide a sustained, high-quality training and education service for the European HPC community through seasonal schools, workshops and scientific and industrial seminars, in order to effectively exploit the unprecedented capabilities of HPC resources of RI.

    Guiding principle in developing the training and educational programs is the compliance with the educational needs of the researchers, thorough understanding of their existing skills and competencies.

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  • GPU Programming with CUDA @ JSC (Past PATC Courses)

    GPU-accelerated computing drives current scientific research. Writing fast numeric algorithms for GPUs offers high application performance by offloading compute-intensive portions of the code to an NVIDIA GPU. The course will cover basic aspects of GPU…


  • 21st VI-HPS Tuning Workshop @ LRZ (Past PATC Courses)

    Goals

    This workshop organized by VI-HPS for the German PRACE Advanced Training Centre hosted by LRZ will:

    give an overview of the VI-HPS programming tools suite
    explain the functionality of individual tools, and how to use them effectively
    offe…


  • Advanced Threading and Optimization @ CSC (Past PATC Courses)

    Description

    The course includes topics on code optimization for x86 platforms and
    efficient code parallelization using OpenMP threading. Advanced aspects
    of threading and optimization, such as new features of OpenMP 4.0, will
    be covered during the cou…


  • Featured ImageRegistration Open for PDC Summer School at KTH Royal Institute of Technology (Announcements Partners Trainings)

    Are you interested in using one of Europe’s faster supercomputers (and getting university credit points for doing so)?  Would you like to learn how to write programs for parallel supercomputers, such as a Cray or a cluster of Graphics Processing Units? Do you need to optimize already- existing scientific program code for high- performance computing? […]