DESCRIPTION
This CVML Web Module focuses on CVML Development and Programming Tools.
First, various such tools, libraries and frameworks are overviewed: Robotic Operating System (ROS), linear algebra libraries (BLAS), DNN libraries (e.g., cuBLAS, cuDNN) and frameworks (e.g., Pytorch, Tensorflow, Keras etc). Distributed computing frameworks (Apache Spark) and collaborative SW development tools are overviewd as well (e.g., GitHub).
Then GPU and Multicore CPU Architectures and Computing are presented, as they are the backbone computing architectures today. Finally, CUDA is presented in detail, as it is essential for GPU programming.
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LECTURE LIST
CVML WEB LECTURE MODULE SCHEDULE
This module has been designed to be mastered within 1 week (or less), if you have proper background (at least early undergraduate student in an EE, ECE, CS, CSE or any Engineering or Exact Sciences Department).
We propose that you follow the above mentioned Lecture order. You may want to skip few Lectures that might not be of immediate interest to you for later study.
On average you can study 4 lectures per week. The related effort is as follows:
Lecture pdf study and filling the related understanding questionnaire: 1-2 hours per lecture (on average, depending on your background).