Atlassian uses cookies to improve your browsing experience, perform analytics and research, and conduct advertising. Accept all cookies to indicate that you agree to our use of cookies on your device. Atlassian cookies and tracking notice, (opens new window)
User Manual
User Manual
Results will update as you type.
  • Application Guide
  • Status of System
  • Usage Guide
  • Compute partitions
    • CPU CLX partition
    • CPU Genoa partition
    • GPU A100 partition
    • GPU PVC partition
      • PVC AI Tools and Frameworks
      • PVC GPU Programming
      • PVC MPI Usage
      • Interactive PVC
    • Next-Gen Technology Pool
  • Software
  • FAQ
  • NHR Community
  • Contact
    You‘re viewing this with anonymous access, so some content might be blocked.
    /
    PVC GPU Programming
    Updated Jan. 31

    PVC GPU Programming

    Programs for Intel GPUs can be written using open industry and cross-platform standards, like:

    1. OpenMP offloading in C/C++ and Fortran, i.e. with the help of compiler directives and a supporting compiler, e.g. Intel’s icpx (C/C++ compiler) and ifx (Fortran compiler) which is available in intel/... environment modules.
      Intel provides an OpenMP Offloading Tuning Guide.

    2. SYCL for C++, i.e. in a data-parallel and explicit fashion. Similar to CUDA but open and cross-platform. See SYCLPreview for more details and code examples.

    Please refer to the oneAPI Programming Guide for further details about programming. Contact NHR@ZIB support to get assistance on getting your application run on Intel GPUs

    The following tools may be useful to check the availability and performance indicators of the GPUs

    • xpu-smi (available without any environment module being loaded) lists the available GPUs from the drivers and selected metrics/properties.

    • sycl-ls [--verbose] (available in intel/... environment modules) shows GPUs and their properties as available to applications.

    {"serverDuration": 11, "requestCorrelationId": "e76bd0849b374656b058d681a0fd69ac"}