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lecture 2 - 2024-01-20

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Name		Name	Last commit message	Last commit date
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lecture3		lecture3
mean_filter		mean_filter
rgb_to_grayscale		rgb_to_grayscale
vector_addition		vector_addition
README.md		README.md
cuda_mode_lecture2.pptx		cuda_mode_lecture2.pptx

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Supplementary Material for Lectures 2 & 3

Lecture 2

Recap Ch. 1-3 from the PMPP book
Date: 2024-01-20, Speaker: Andreas Koepf, Book: Programming Massively Parallel Processors: A Hands-on Approach (Amazon link)
Slides: The powerpoint file cuda_mode_lecture2.pptx can be found in the root directory of this repository. Alternatively here as Google docs presentation.
Examples: Please make sure PyTorch (2.1.2) and cuda-toolkit (nvcc compiler) are installed.
- vector_addition: Classic CUDA C example, to compile use make in the vector_addition directory.
- rgb_to_grayscale: Example uses PyTorch's torch.utils.cpp_extension.load_inline feature to compile a custom RGB to grayscale kernel and uses it to convert input image to grayscale and which is saved in as output.png. Run in the rgb_to_grayscale folder python rgb_to_grayscale.py.
- mean_filter: This example also uses the PyTorch's cpp_extension.load_inline feature to compile a mean filter kernel. The kernel read pixel values in the surrounding (square area) of a pixel and computes the average value for each RGB channel individualy. The result is saved to output.png. Run in the mean_filter folder python mean_filter.py.

Lecture 3

Title: Getting Started With CUDA
Date: 2024-01-27, Speaker: Jeremy Howard
Notebook: See the lecture3 folder, or run the Colab version