Repository for SeSE course GPU programming for Machine Learning and Data Processing
Zoom room details will only be announced in the Slack channel in the sesegpu workspace.
8.45 Lectures start. GPU vs CPU, deep learning, TensorFlow and Tensorflow contrasted to other frameworks. Ends no later than 12.00 (with breaks).
13.15 Lab 1
8.45 Lectures start. The history of "GPGPU" programming. Current frameworks, focusing on Cuda and OpenMP Target and contrasting those against alternatives. Ends no later than 12.00 (with breaks).
13.15 Lab 2,
TBA
TBA
10.15 Profiling, debugging, how to approach the project. Ends no alter than 12.00.
13.15 Lab time, for exploring project ideas.
15.15 Common brainstorming of project ideas, with feedback from teachers regarding what seems feasible and important aspects to consider.