Graphics Processing Units (GPUs) are specialized hardware designed to accelerate the processing of graphics and visualizations. GPUs have become increasingly popular for a variety of non-graphics related tasks, including scientific computing, machine learning, and data analysis. Today, GPUs are also used for CFD (Computational Fluid Dynamics) and FEM (Finite Element Method). The high par-allelization capabilities of GPUs make them well-suited for CFD and FEM.
General information
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. PhD students are welcome.
Course content
Introduction lectures on CUDA programming including two mini-workshops.
Project 1
The student groups 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
More information about the course
Prerequisites
The students should have good knowledge in Python.
How to apply
Apply to all Tracks courses at antagning.se / universityadmissions.se
Search for the course code TRA220
To assess your application, please include a letter explaining your contribution to the project group. The letter of motivation requested is an opportunity for each student to express specific interests and experience that cannot be seen from transcripts only. The purpose of the motivation letter is to assist the teachers in grouping students with respect to background and interests. The motivation letter may be used when prioritizing if we get too many applicants. In addition, it is possible to upload a CV that may provide additional background experience that may be relevant.
Upload the letter of motivation on your account at antagning.se / universityadmissions.se.
More information on how to select courses
For alumni, PhD-students and professionals the course selection follows a different process. See more information on Tracks web page.
Details
Teachers:
Lars Davidson, Rickard Bensow, Fredrik Larsson, Miquel Pericas
Course dates: Study period 2
Credits: 7.5
Level: Advanced
Course code: TRA220