Numerical Computing on GPUs (CUDA5)

Programming, Programming - other

This course focuses on numerical computing on GPUs, covering CUDA, OpenCL, and general-purpose GPGPU programming. You will learn GPU-aware numerical algorithms, performance considerations and how to map computations to graphics hardware.

The course explains integration with scientific tools like Matlab, R, Octave and CAS systems, and shows real-world examples. It requires a basic programming background and follows a preparatory CUDA/GPU course; taught in Czech or English.

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The course:

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  • Numerical computation issues and challenges
  • GPU and GPGPU overview
  • CUDA: concepts and programming
  • Matlab and GPU integration
  • Mathematica and GPU integration
  • Maple and GPU integration
  • GNU and open-source GPU tools
  • R and GPU integration
  • Octave and GPU integration
  • Examples and practical applications of numerical computing
Assumed knowledge:
Basic programming skills in a structured programming language.
Schedule:
1 day (9:00 AM - 5:00 PM )
Education Partner:
Sprinx Systems
Language: