Course syllabus for GPU-accelerated computational methods using Python and CUDA

The course syllabus contains changes
See changes

Course syllabus adopted 2023-05-02 by Head of Programme (or corresponding).

Overview

  • Swedish nameGPU-accelererade beräkningsmetoder med Python och CUDA
  • CodeTRA220
  • Credits7.5 Credits
  • OwnerTRACKS
  • Education cycleSecond-cycle
  • DepartmentTRACKS
  • GradingTH - Pass with distinction (5), Pass with credit (4), Pass (3), Fail

Course round 1

  • Teaching language English
  • Application code 97147
  • Open for exchange studentsYes

Credit distribution

0123 Project 7.5 c
Grading: TH		 7.5 c

In programmes

Examiner

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Eligibility

General entry requirements for Master's level (second cycle)
Applicants enrolled in a programme at Chalmers where the course is included in the study programme are exempted from fulfilling the requirements above.

Specific entry requirements

English 6 (or by other approved means with the equivalent proficiency level)
Applicants enrolled in a programme at Chalmers where the course is included in the study programme are exempted from fulfilling the requirements above.

Course specific prerequisites

In addition to the general requirements to study at advanced level at Chalmers, necessary subject or project specific prerequisite competences (if any) must be fulfilled. Alternatively, the student must obtain the necessary competences during the course. The examiner will formulate and check these prerequisite competences.

The student will only be admitted in agreement with the examiner.

Aim

The aim of the course is to provide a platform to work and solve challenging cross-disciplinary authentic problems from different stakeholders in society such as the academy, industry or public institutions. Additionally, the aim is that students from different educational programs practice working efficiently in global multidisciplinary development teams.

In this course, the students will learn how to write a simple CFD or FEM code or a Poisson solver. The code should run entirely or partly on the GPU using CUDA,

Learning outcomes (after completion of the course the student should be able to)


Valid for all Tracks courses:
  • critically and creatively identify and/or formulate advanced architectural or engineering problems
  • master problems with open solutions spaces which includes to be able to handle uncertainties and limited information.
  • work in multidisciplinary teams and collaborate in teams with different compositions
  • orally and in writing explain and discuss information, problems, methods, design/development processes and solutions
Course specific:
  • be able to programme numerical solvers in Python
  • be able to programme in CUDA
  • be able to profile the programme


Content

Introduction lectures on CUDA programming including two mini-workshops.

Team project
  • Student teams write a simple CFD/FEM code or Poisson solver in CUDA. Ideally, each group includes students with knowledge in CFD, FEM or Poisson equation and CUDA.
  • Profiling (GPU time, uploading/downloading data to/from the GPU etc)
  • Written and oral presentation of the project
https://www.tfd.chalmers.se/~lada/CUDA-tracks.html

Organisation

The course is run by a teaching team.
The main part of the course is a challenge driven project. The challenge may range from being broad societal to profound research driven. The project task is solved in a group. The course is supplemented by on-demand teaching and learning of the skills necessary for the project. The project team will have one university examiner, one or a pole of university supervisors and one or a pole of external co-supervisors if applicable.

Tracks-theme: Emerging technologies - from science to innovation

The course has a teacher team consisting of teachers from Mechanics & maritime sciences, Industrial & material science, and Computer science and engineering.
The course consists of a few introductory lectures and workshops on CUD programming and a team project with three to four students in each team. The project is supplemented by on-demand teaching and learning of the skills necessary for the project

Literature

Relevant literature is retrieved and acquired by the students as a part of the project.

Examination including compulsory elements

Oral and written presentation of the project.

The course examiner may assess individual students in other ways than what is stated above if there are special reasons for doing so, for example if a student has a decision from Chalmers on educational support due to disability.

The course syllabus contains changes

  • Changes to course:
    • 2023-05-01: Examination Examination changed by UOL
      Adjusted description of examination
    • 2023-05-01: Organization Organization changed by UOL
      Adjusted Swedish name of departments
    • 2023-05-01: Learning outcomes Learning outcomes changed by UOL
      Updated list of learning objectives valid for all Tracks courses
    • 2023-05-01: Aim Aim changed by UOL
      Removed dublicated information
    • 2023-04-19: Content Content changed by UOL
      Added url https://www.tfd.chalmers.se/~lada/CUDA-tracks.html