Supplementary Material for Lectures

The PMPP Book: Programming Massively Parallel Processors: A Hands-on Approach (Amazon link)

Lecture 1: Profiling and Integrating CUDA kernels in PyTorch

• Video
• Date: 2024-01-13, Speaker: Mark Saroufim
• Notebook and slides in lecture1 folder

Lecture 2: Recap Ch. 1-3 from the PMPP book

• Video
• Date: 2024-01-20, Speaker: Andreas Koepf
• Slides: The powerpoint file lecture2/cuda_mode_lecture2.pptx can be found in the root directory of this repository. Alternatively here as Google docs presentation.

Lecture 3: Getting Started With CUDA

• Video
• Date: 2024-01-27, Speaker: Jeremy Howard
• Notebook: See the lecture3 folder, or run the Colab version

Lecture 4: Intro to Compute and Memory Architecture

• Video
• Date: 2024-02-03, Speaker: Thomas Viehmann
• Notebook and slides in the lecture4 folder.

Lecture 5: Going Further with CUDA for Python Programmers

• Video
• Date: 2024-02-10, Speaker: Jeremy Howard
• Notebook in the lecture5 folder.

Lecture 6: Optimizing PyTorch Optimizers

• Video
• Date: 2024-02-17, Speaker: Jane Xu
• Slides

Lecture 7: Advanced Quantization

• Video
• Date: 2024-02-25, Speaker: Charles Hernandez
• Slides

Lecture 8: CUDA Performance Checklist

• Video
• Date: 2024-03-09, Speaker: Mark Saroufim
• Code in the lecture8 folder
• Slides

Lecture 9: Reductions

• Video
• Date: 2024-03-09, Speaker: Mark Saroufim
• Code in the lecture9 folder
• Slides

Lecture 10: Build a Prod Ready CUDA Library

• Video
• Date: 2024-03-16, Speaker: Oscar Amoros Huguet
• slides

Lecture 11: Sparsity

• Video
• Date: 2024-03-23, Speaker: Jesse Cai
• Slides

Lecture 12: Flash Attention

• Video
• Date: 2024-03-30, Speaker: Thomas Viehmann

Lecture 13: Ring Attention

• Video
• Date: 2024-04-06, Speaker: Andreas Koepf
• Slides

Lecture 14: Practitioner's Guide to Triton

• Video
• Date: 2024-04-13, Speaker: Umer Adil
• [Notebook](./lecture 14/A_Practitioners_Guide_to_Triton.ipynb)