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NHR@FAU

  1. Home
  2. Teaching & Training
  3. Tutorials & Courses
  4. Choosing GPU Programming Approaches

Choosing GPU Programming Approaches

In page navigation: Teaching & Training
  • Lectures & Seminars
  • Tutorials & Courses
    • Accelerating CUDA C++ Applications with Multiple GPUs
    • C++ for Beginners
    • Choosing GPU Programming Approaches
    • Core-Level Performance Engineering
    • FAQ about NHR@FAU Trainings
    • From Zero to Multi-Node GPU Programming
    • Fundamentals of Accelerated Computing with CUDA C/C++
    • Fundamentals of Accelerated Computing with CUDA Python
    • Fundamentals of Accelerated Computing with Modern CUDA C++
    • Fundamentals of Accelerated Computing with OpenACC
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    • GPU Performance Engineering
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  • Monthly HPC Café and Beginner's Introduction
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Choosing GPU Programming Approaches

This course provides an overview of the most common GPU programming approaches, including CUDA/ HIP, SYCL, modern C++, Thrust, OpenACC, OpenMP and Kokkos. It helps participants understand the strengths and weaknesses of each approach, enabling them to make informed decisions about which one to use for their specific applications.

Participants will get the most out of this course if they have already have prior experience in at least one GPU programming approach, but participation without any prior knowledge is also possible.

Certification

A digital certificate of attendance will be awarded to all participants who attended the majority of the course.

Prerequisites

Participants should meet the following requirements:

  • Familiarity with (modern) C++ programming

Upcoming Iterations and Additional Courses

You can find dates and registration links for this and other upcoming NHR@FAU courses at https://go-nhr.de/trainings .

Erlangen National High Performance Computing Center (NHR@FAU)
Martensstraße 1
91058 Erlangen
Germany
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