Cuda Programming – From Zero To Hero

Cuda Programming – From Zero To Hero
Published 12/2023
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz

Learn CUDA Programming from absolute scratch

What you’ll learn

Learn how to build programs in CUDA

Understand the underlying basics of Parallel Programming

Build a Machine Learning Model in CUDA (Future Work for now)

Learn GPU Programming in CUDA as a whole

Requirements

A bit familiarity in C++ is needed, except that the desire to learn.

Description

Overview

Section 1: Introduction to Parallel Programming

Lecture 1 What is Parallel Programming?

Lecture 2 Why do we need Parallel Programming?

Lecture 3 What are threads?

Lecture 4 Benefits and Challenges of Working with Threads

Lecture 5 What went wrong with single processor performance?

Section 2: Installing CUDA on Nvidia and Non-Nvidia Machines

Lecture 6 Installing CUDA on a Non-Nvidia Graphics Card Machine

Lecture 7 Installing CUDA on a Nvidia Graphics Card Machine

Section 3: Hello World in CUDA

Lecture 8 Hello World Program version 1

Lecture 9 Hello World Program version 2

Lecture 10 Hello World Program version 3

Lecture 11 Coding Exercise: Print Your Name N Times

Lecture 12 Bonus Lecture 1 : Time your Programs in CUDA

Section 4: Communicate between GPU and CPU Memory

Lecture 13 Let’s Look at a Code!

Lecture 14 Typical Memory Flow

Lecture 15 Initializing an array in parallel

Lecture 16 Adding a constant c to all elements of an array

Section 5: Kernels: Grids, Blocks and Threads

Lecture 17 How are threads organized in CUDA?

Lecture 18 Accessing Grid Dimensions

Lecture 19 Accessing Block Dimensions

Lecture 20 Problem of changing size to value greater than 1024 in Lecture 16 – Section 4

Section 6: CUDA Computation

Lecture 21 Warps and Thread Divergence

Lecture 22 Finding Thread Divergence in Code

Lecture 23 Exercise Solution

Lecture 24 Finding an element in parallel

Lecture 25 Exercise Solution: Encrypting and Decrypting Messages

Section 7: Conclusion

Any person interested to dive into the field of parallel programming.