Learn CUDA Programming from absolute scratch
Welcome to the course on CUDA Programming – From Zero to Hero!
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.
Course Content
- Introduction to Parallel Programming –> 5 lectures • 34min.
- Installing CUDA on Nvidia and Non-Nvidia Machines –> 2 lectures • 7min.
- Hello World in CUDA –> 5 lectures • 32min.
- Communicate between GPU and CPU Memory –> 4 lectures • 33min.
- Kernels: Grids, Blocks and Threads –> 4 lectures • 24min.
- CUDA Computation –> 5 lectures • 55min.
- Conclusion –> 0 lectures • 0min.
Requirements
Welcome to the course on CUDA Programming – From Zero to Hero!
Unlock the immense power of parallel computing with our comprehensive CUDA Programming course, designed to take you from absolute beginner to a proficient CUDA developer. Whether you’re a software engineer, data scientist, or enthusiast looking to harness the potential of GPU acceleration, this course is your gateway to mastering the CUDA programming paradigm. In this course, we will learn about GPU Programming and write programs in CUDA in C++. CUDA is an amazing framework developed by NVidia where you can code programs that can run on GPUs. By exploiting data level parallelism techniques, one can solve complex computational tasks and problems in far lesser time compared to the serial counterparts. Serial Programming involves usage of only a single processor core where all the computation happens, but in today’s world with the advent of multi-core architectures, parallel programming is the need of the hour. To add to that, Nvidia offers its wide range of GPUs where you can use this framework to run your algorithms in the GPU in parallel. CUDA also enables you to learn how to code faster for people who have some exposure on serial programming languages like C, C++ and Java. This course would offer you to write programs in C++ utilizing the CUDA framework.
This course will also touch base on the basics of parallel programming and why we do it in the first place. It also reflects on when parallelism can be exploited and what are threads to start your journey! I have tried to build the course as self-contained as possible so that students can find a one-stop solution to becoming a CUDA Programmer from the absolute basics.
If you do not have a Nvidia GPU, don’t worry as in this course, I will show you a way by which you can run CUDA Programs on any machine! Only thing required is an internet connection, that’s it!
By the end of this course, you’ll not only be proficient in CUDA programming but also have the confidence to tackle complex parallel computing challenges. Join us on this journey, and let’s elevate your GPU programming skills from zero to hero!
Prerequisites
- Willingness to Learn
- Some familiarity with C++ language is expected.
What will you learn from this course?
- Basics of Parallel Programming In this section, you will learn more about what is the need of parallel programming and why it is important to learn this skill.
- Installing CUDA on NVidia As Well As Non-Nvidia Machines In this section, we will learn how to install CUDA Toolkit and necessary software before diving deep into CUDA.
- Hello World in CUDA We will start with Programming Hello World in CUDA and learn about certain intricate details about CUDA.
- Communication between GPU And CPU Memory This section will talk more about how a CPU can communicate with the GPU and send data and receive data from it.
- Kernels, Grids, Blocks and Threads This section will form the heart of CUDA where you will learn more about grids, blocks and kernels.
- CUDA Computation This section will share more about using CUDA Programming to do Compute Tasks.
If you are interested to code parallel programs in GPU, enroll this course now.