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Home Teaching Summer Semester 2014 Practical Course: GPU Programming in Computer Vision (6h / 10 ECTS)

Practical Course: GPU Programming in Computer Vision (6h / 10 ECTS)

SS 2014, TU München


Please direct ALL questions regarding this course at cuda-ss14@in.tum.de.


Thomas Möllenhoff
Mohamed Souiai
Maria Klodt
Jan Stühmer
Sahand Sharifzadeh



Date and Location

Start: Mo, September 8, 2014, 10:00 – Room 02.09.023



Please send us your top 3 preferences for the final project until Wednesday, September 17, 12:00 CET. Own ideas for the final project are very welcome, but please discuss them first with us!.


The lecture part of the course will take place in our seminar room 02.09.023 and the exercises will be held in our lab 02.05.014. The general time is September 8 – October 10, with the following timeline:

  • 1 week with lectures and exercises (attendance mandatory): September 8 – 12
  • 3 weeks project phase: September 15 – October 3
  • final presentation: between October 6 – 10


Course Registration

The registration for this course has been closed. There are no more places available.

Requirements: Knowledge of C or C++, basic mathematics

Number of participants: up to 21

Course Description

The goal of this course is to provide an introduction to the NVIDIA CUDA framework for massively parallel programming on GPUs. During the implementation of basic computer vision algorithms students will gradually learn more how to harness the power of GPU computing. Although we assume good knowledge of C or C++ and basic mathematics, no further prior knowledge about CUDA, or computer vision topics will be required.

During the course lecture students will learn how to program GPUs with CUDA. Afterwards the students will start to implement more sophisticated computer vision algorithms within a student project. The course finishes with a presentation and a live demo of the project results.

Topics

  • Introduction to Parallel Computing
  • Introduction to CUDA
  • Implementation of basic computer vision algorithms with CUDA (e.g. convolution, diffusion)
  • Student project: Implementation of an advanced computer vision application which uses CUDA acceleration for real-time processing of webcam images.

Layout

  • Lecture (September 8–12): 2–3h lectures each day (attendance mandatory) from 10:00 (Room: 02.09.023), followed by corresponding programming exercises until 18:00 (Room: 02.05.014). The exercises must be done in groups of 2–3 students. The groups must be formed on the first day, September 8 (but you can decide on your team already beforehand, of course). You may leave early once you have finished the day's exercises.
  • Project (September 15–October 3): Implementation of a student project in groups of 2–3 (same groups as in the lecture week). You are free to work from home if you like and all team members agree, but keep in mind that you will require CUDA-capable hardware, and should collaborate within your team. You should also prepare your final presentation during this time.
  • Presentation and demo (October 6–10): Each group will be assigned a time slot on one of these days, to present their results and give a live demo, followed by a Q&A session.

Literature

Slides

Additional material can be downloaded from here.

Last edited 15.09.2014 11:29 by Thomas Möllenhoff