CUDA in Frankfurt, GER

Partnering with NVIDIA, this professional four day course is designed for programmers who are looking to develop comprehensive skills in writing and optimizing applications that fully leverage multi-core processing capabilities of GPUs.

Your fee includes

  • Use of a laptop equipped with CUDA capable GPU
  • Choice of Windows and Linux OS
  • Printed manual of all lectures
  • Electronic copy of lab exercises
  • Certificate of Completion
  • Beverages and snacks

Space is limited - Please register early to guarantee your spot

Your Instructor

Kelly Goss - Training Program Manager
Kelly is Acceleware’s passionate and energetic Training Program Manager. She is responsible for the development and management of all training materials. Kelly is also an integral member of our professional services team advising our clients on the best platforms, programming models and languages to meet their needs. Kelly has taught over 35 high performance courses to students from a diverse range of industries and backgrounds. She has also delivered tutorials at a number of conferences including Supercomputing and NVIDIA’s GPU Technology Conference. Kelly has a PhD in Electrical Engineering from the University of Calgary.


Tue-Fri: 9:00AM – 5:00PM (includes a 1 hour break for lunch)


  • Day 1:
    • Overview of GPU computing
    • Data-parallel architectures and the GPU programming model
    • GPU memory model & thread cooperation
    • Hands-on exercises: GPU memory management, simple CUDA kernels and shared memory and constant memory
  • Day 2:
    • Asynchronous operations
    • Advanced CUDA features
    • Libraries
    • Debugging GPU Programs
    • Hands-on-exercises: Asynchronous operations, CUDA features, experience with CUFFT, CUBLAS, Thrust, debugging
  • Day 3:
    • Introduction to optimization
    • Resource management, latency and occupancy
    • Memory performance optimizations
    • Profiling applications
    • Hands-on exercises: Arithmetic optimizations, occupancy calculator, profiling and memory access patterns
  • Day 4:
    • CUDA compiler and user-defined libraries
    • OpenACC
    • Hands-on exercises: Case study exercise and OpenACC
    • Case study: Finite difference stencil algorithm or monte carlo simulations

All lectures are a combination of teaching and hands-on tutorials

NVIDIA’s foundational training material is augmented with Acceleware’s experience over the past 8 years and with examples specific to an HPC audience

Online registration is now closed.

Course details

Date:Sep 24 to Sep 27, 2013
Registration closes:Sep 11, 2013 at 8:00PM (MST)
Location:Frankfurt, Germany (venue TBC)
Cost:$3,250 USD


Click here to see our terms and conditions.