The Complete Course of CUDA Programming

The Complete Course of CUDA Programming, available at $39.99, has an average rating of 4, with 26 lectures, 1 quizzes, based on 13 reviews, and has 112 subscribers.

You will learn about At the end of the course you will fully master CUDA programming, to be able to execute GPU programming You will be able to build step by step codes from scratch, understanding all the logic and ending with advanced practical examples and a complete project You will become familiar with the development interface, toolbars and basic commands, and you will master all the phases of the configuration process You will learn in a professional way the basics of CUDA programming, writing first lines of code, debugging, profiling and synchronizating threads You will understand the fundamental Memory Management and Memory Optimization Techniques You will master the Advanced Techniques: managing multiple GPUs, libraries for parallel (cuBLAS, cuFFT…), dynamic paralellism, recursive GPU programming… You will learn the CUDA Performance Analysis and Performance Optimization, and above all, understanding their interpretation You will be able to practice the content learned in a practical way by following all the steps in the complete exercises and the final project You will start with the basics and progressively carry out more complex steps until you reach an advanced level and absolute mastery at the end of the course This course is ideal for individuals who are Beginners who have never used CUDA before or Programmers, Developers, Engineers, Students… who want to learn a new way to execute parallel programming on GPUs or Intermediate or advanced CUDA Programming students who want to improve their skills even more! It is particularly useful for Beginners who have never used CUDA before or Programmers, Developers, Engineers, Students… who want to learn a new way to execute parallel programming on GPUs or Intermediate or advanced CUDA Programming students who want to improve their skills even more!.

Enroll now: The Complete Course of CUDA Programming

Summary

Title: The Complete Course of CUDA Programming

Price: $39.99

Average Rating: 4

Number of Lectures: 26

Number of Quizzes: 1

Number of Published Lectures: 26

Number of Published Quizzes: 1

Number of Curriculum Items: 27

Number of Published Curriculum Objects: 27

Original Price: €219.99

Quality Status: approved

Status: Live

What You Will Learn

At the end of the course you will fully master CUDA programming, to be able to execute GPU programming
You will be able to build step by step codes from scratch, understanding all the logic and ending with advanced practical examples and a complete project
You will become familiar with the development interface, toolbars and basic commands, and you will master all the phases of the configuration process
You will learn in a professional way the basics of CUDA programming, writing first lines of code, debugging, profiling and synchronizating threads
You will understand the fundamental Memory Management and Memory Optimization Techniques
You will master the Advanced Techniques: managing multiple GPUs, libraries for parallel (cuBLAS, cuFFT…), dynamic paralellism, recursive GPU programming…
You will learn the CUDA Performance Analysis and Performance Optimization, and above all, understanding their interpretation
You will be able to practice the content learned in a practical way by following all the steps in the complete exercises and the final project
You will start with the basics and progressively carry out more complex steps until you reach an advanced level and absolute mastery at the end of the course

Who Should Attend

Beginners who have never used CUDA before
Programmers, Developers, Engineers, Students… who want to learn a new way to execute parallel programming on GPUs
Intermediate or advanced CUDA Programming students who want to improve their skills even more!

Target Audiences

Beginners who have never used CUDA before
Programmers, Developers, Engineers, Students… who want to learn a new way to execute parallel programming on GPUs
Intermediate or advanced CUDA Programming students who want to improve their skills even more!

Become a CUDA professional and learn one of employer’s most requested skills nowadays!

This comprehensive course is designed so that students, programmers, computer scientists, engineers… can learn CUDA Programming from scratch to use it in a practical and professional way. Never mind if you have no experience in the topic, you will be equally capable of understanding everything and you will finish the course with total mastery of the subject.

After several years working as an Engineer, I have realized that nowadays mastering CUDA for parallel programming on GPUs is very necessary in many programming applications. Learning it can give you many job opportunities and many economic benefits, especially in the world of the programming and development.

The big problem has always been the complexity to perfectly understand CUDA Programing it requires, since its absolute mastery is not easy. In this course I try to facilitate this entire learning and improvement process, so that you will be able to carry out and understand your own projects in a short time, thanks to the step-by-step and detailed examples of every concept.

With almost 8 exclusive hours of video, this comprehensive course leaves no stone unturned! It includes both practical exercises and theoretical examples to master CUDA programming. The course will teach you GPU programming and parallel computing in a practical way, from scratch, and step by step.

We will start with the installation of the needed software and work environment on your computer, regardless of your operating system and computer.

Then, we’ll cover a wide variety of topics, including:

Introduction to CUDA, parallel computing and course dynamics
Download and Install the development environment and needed software, and configuring it
General familiarization with the user interface and CUDA essential commands
CUDA Thread Execution: writing first lines of code, debugging, profiling and thread synchronization
Memory Management and Memory Optimization Techniques
Advanced CUDA Programming Techniques: managing multiple GPUs, libraries for parallel algorithms (cuBLAS, cuFFT…), dynamic paralellism, recursive GPU programming…
Performance Analysis and Performance Optimization
CUDA Applications, case studies and real time project
Mastery and application of absolutely ALL the functionalities of CUDA and parallel and GPU programming
Practical exercises, complete project and much more!

In other words, what I want is to contribute my grain of sand and teach you all those things that I would have liked to know in my beginnings and that nobody explained to me. In this way, you can learn to code a wide variety of projects quickly and make versatile and complete use of CUDA programming. And if that were not enough, you will get lifetime access to any class and I will be at your disposal to answer all the questions you want in the shortest possible time.

Learning CUDA Programming has never been easier. What are you waiting to join?

Course Curriculum

Chapter 1: Introduction to Parallel Computing and CUDA programming

Lecture 1: Course introduction and overview

Lecture 2: Introduction to parallel computing and its relevance

Lecture 3: CUDA programming model

Chapter 2: CUDA Programming Basics

Lecture 1: Understanding threads, blocks, and grids in CUDA

Lecture 2: Installing & Setting the development environment (CUDA toolkit, GPU drivers…)

Lecture 3: The Code in C Programming in a Visual Manner

Lecture 4: C Code Overview

Lecture 5: C Code and Memory Overview

Chapter 3: CUDA Thread Execution

Lecture 1: Writing first lines of code

Lecture 2: Basic Debugging in CUDA programs

Lecture 3: Understanding Profiling

Lecture 4: Thread synchronization and barriers

Chapter 4: Memory Management and Optimization Techniques

Lecture 1: Memory coalescing and access patterns

Lecture 2: Optimizing memory transfers using asynchronous data transfer

Lecture 3: Utilizing constant and texture memory

Lecture 4: Managing large-scale data sets with CUDA

Chapter 5: Advanced CUDA Programming Techniques

Lecture 1: Managing multiple GPUs and multi-GPU communication

Lecture 2: Using CUDA libraries for common parallel algorithms (cuBLAS, cuFFT, etc.)

Lecture 3: Dynamic parallelism and recursive GPU programming

Lecture 4: Advanced optimization techniques (warp divergence, memory access patterns, etc.)

Chapter 6: CUDA Performance Analysis and Optimization

Lecture 1: Profiling CUDA applications using CUDA Profiler and NVIDIA Visual Profiler

Lecture 2: Fine-tuning CUDA kernels & Strategies for maximum parallelism and throughput

Lecture 3: Identifying performance bottlenecks and optimizing code

Chapter 7: CUDA Case Studies & Project

Lecture 1: CUDA Applications and case studies

Lecture 2: Real Time Project

Lecture 3: Course closure

Instructors

The Tech Courses
Group of Engineers and Developers passionate about teaching

Rating Distribution

1 stars: 1 votes
2 stars: 0 votes
3 stars: 5 votes
4 stars: 2 votes
5 stars: 5 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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