182.731 GPU Architectures and Computing
This course is in all assigned curricula part of the STEOP.
This course is in at least 1 assigned curriculum part of the STEOP.

2023S, VU, 4.0h, 6.0EC
TUWEL

Properties

  • Semester hours: 4.0
  • Credits: 6.0
  • Type: VU Lecture and Exercise
  • Format: Presence

Learning outcomes

After successful completion of the course, students are able to master GPU-based architectures and related technologies and to develop efficient parallel algorithms based on many-cores. Through the final assignment, they will also acquire important team working skills.

Subject of course

This is the list of the main topics of the course:

  • GPU Architectures
  • CUDA Programming (Basics)
  • GPU Memories/Access Patterns
  • CUDA Execution
  • CUDA Parallel patterns
  • Thrust Library
  • Dynamic Parallelism
  • CUDA application profiling
  • CUDA Streaming

Registration

The enrollment can be performed using TISS. The enrollment will be close on February 25th, 2023. The max number of students for this course is 20. Please register soon !!!

Teaching methods

In the first month of the course we will present the basic knowledge that is required to do the assignment. In the second part of the course, we will present advance topics that will be useful to further improve their project. We will ask the students to setup a git hub repository where we will monitor the progress and the actual work of the single students in the group. The students will ask to make two presentations. One presentation where the students must to elaborate, before starting the project, a contingency plan where they can still safely achieve some goals and the risk is taken into consideration. The students must write a document explaining the solution adopted for their assignment. At end of the course, the students are asked to make a public final presentation where they present their results.

 

Mode of examination

Immanent

Additional information

ECTS-Breakdown: 6 ECTS = 150 Hours 

  • 1 h - Introduction to the Course
  • 1 h - Group formation
  • x h - Development of project idea and brainstorming
  • 20 h - Lessons on GPU Computing and Architecture
  • 1 h - Workshop 1 - Project proposal presentation
  • 1 h - Workshop 2 - Project results presentation
  • 100 h - Project Work
  •   20 h - Project discussion 

Some Resources:

  • John Cheng, Max Grossman, Ty McKercher, Professional CUDA C Programming, Publisher Wrox
  • Jaegeun Han, Bharatkumar Sharma, Learn CUDA Programming,Publisher  Packt


Lecturers

Institute

Course dates

DayTimeDateLocationDescription
Tue11:00 - 13:0007.03.2023 - 27.06.2023Seminarraum DE0110 GPU Computing and Architecture
GPU Architectures and Computing - Single appointments
DayDateTimeLocationDescription
Tue07.03.202311:00 - 13:00Seminarraum DE0110 GPU Computing and Architecture
Tue21.03.202311:00 - 13:00Seminarraum DE0110 GPU Computing and Architecture
Tue28.03.202311:00 - 13:00Seminarraum DE0110 GPU Computing and Architecture
Tue04.04.202311:00 - 13:00Seminarraum DE0110 GPU Computing and Architecture
Tue11.04.202311:00 - 13:00Seminarraum DE0110 GPU Computing and Architecture
Tue18.04.202311:00 - 13:00Seminarraum DE0110 GPU Computing and Architecture
Tue25.04.202311:00 - 13:00Seminarraum DE0110 GPU Computing and Architecture
Tue02.05.202311:00 - 13:00Seminarraum DE0110 GPU Computing and Architecture
Tue09.05.202311:00 - 13:00Seminarraum DE0110 GPU Computing and Architecture
Tue16.05.202311:00 - 13:00Seminarraum DE0110 GPU Computing and Architecture
Tue23.05.202311:00 - 13:00Seminarraum DE0110 GPU Computing and Architecture
Tue30.05.202311:00 - 13:00Seminarraum DE0110 GPU Computing and Architecture
Tue06.06.202311:00 - 13:00Seminarraum DE0110 GPU Computing and Architecture
Tue13.06.202311:00 - 13:00Seminarraum DE0110 GPU Computing and Architecture
Tue20.06.202311:00 - 13:00Seminarraum DE0110 GPU Computing and Architecture
Tue27.06.202311:00 - 13:00Seminarraum DE0110 GPU Computing and Architecture

Examination modalities

Students will be divided in groups of four people and a project will be assigned to each group. The project consists in solving a very high computationally intensive task, developing efficient GPU-based algorithms. At the end of the semester the students will defend their solution in a public presentation.

Course registration

Begin End Deregistration end
03.02.2023 10:00 24.02.2023 23:59 03.03.2023 23:59

Curricula

Study CodeObligationSemesterPrecon.Info
066 645 Data Science Not specified
066 646 Computational Science and Engineering Not specified
066 932 Visual Computing Mandatory elective
066 937 Software Engineering & Internet Computing Mandatory elective
066 938 Computer Engineering Mandatory elective

Literature

No lecture notes are available.

Previous knowledge

  • VU Algorithmen und Datenstrukturen 1
  • VU Algorithmen und Datenstrukturen 2
  • 182.695 LU Digital Design and Computer Architecture
  • 182.709 UE Operating Systems
  • 351.015 VU Signals and Systems 1
  • 389.055 VU Signals and Systems 2

Preceding courses

Miscellaneous

Language

English