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GPU Computing

GPU Computing
Typ: Praktikum
Semester: WS 2013/2014
Ort:

Room 148, 50.34 

Zeit:

Wed, 11:30-13:00

Kick-off meeting will take place on 23.10.2013 at 11:30 in the room #148.

Dozent:

Prof. Dr.-Ing. Carsten Dachsbacher

Anton S. Kaplanyan

Gregor Mückl

Christoph Schied

SWS: 4
LVNr.: 24283

Exploiting the vast horse power of contemporary GPUs for general purpose applications has become a must for any realtime or interactive application nowadays. Current computer games use the GPUs not only for rendering graphics, but also for collision detection, physics, or artificial intelligence. General purpose computing on GPUs (GPGPU) has also penetrated the field of scientific computing enabling realtime experience of large scale fluid simulations, medical visualization, or signal processing.

This lecture introduces the concepts of programming graphics cards for non-graphical applications, such as data sorting, image filtering (e.g. denoising, sharpening), or physically based simulations. During the course, students familiarize themselves with the architecture of the current GPUs and develop parallel programming skills using the OpenCL and CUDA language.

The practical assignments will cover the following topics:

  • The architecture of contemporary GPUs (execution model, memory model, etc.)
  • Introduction to the OpenCL programming language
  • Reduction, scanning, and sorting parallel algorithms
  • Image filtering via separable convolution kernels
  • Physics simulation (cloth simulation using particles and springs)
  • Introduction to optimization and profiling on the GPU
    Kick-off Slides
    Materials: 
Assignment 1     Introduction
    Deadline:  November 6, 2013, 12:00
    Topics:  Introduction into OpenCL, parallel vector summation and matrix transposition.
    Materials: 
Assignment 3     Image Convolution
    Deadline:  December 11, 2013, 12:00
    Topics:  Image filtering via separable convolution kernels
    Materials: 
Assignment 4     Particle Simulation
    Deadline:  January 15, 2013, 11:30
    Topics:  How to simulate massive particle system with GPU
    Materials: