CUDA is a GPU programming language. It is a language that was created by modifying C and C++, so anyone who is a C or C++ developer can easily approach it. However, you must understand the characteristics of GPU machines and CUDA programming.
This course understands GPU machines and writes CUDA to execute matrix multiplication, which is the basic operation of deep learning. Through this course, you will be able to handle GPU programming skillfully.
If the lecture length is short, then it is an advantage ^^*
After taking the course, I felt like I learned what CUDA programming is and that CUDA programming is easy.
One-line summary: A short but powerful CUDA in C lecture.
Can I look forward to follow-up lectures in the future?
5.0
이상우
100% enrolled
It's a good way to get a taste of basic GPU programming languages.
5.0
wikimfw
100% enrolled
It was a time to approach a more diverse field by gaining experience with GPU programming.
What you will gain after the course
Fundamentals of GPU Programming
CUDA Installation and Configuration
GPU implementation of matrix multiplication algorithm
Performing benchmarks using the CUDA API
Various applications of GPU technology
GPU programming language CUDA
With Google's focus on machine learning, GPU programming has become an undeniable trend. Machine learning, cryptocurrency mining, self-driving cars, AI, chatbots, and big data analysis all utilize GPUs. CUDA is the GPU programming language.
Because it's a language derived from C and C++, it's easily accessible to any C or C++ developer. However, understanding the characteristics of GPU machines and CUDA programming is essential. This course will teach you how to understand GPU machines and write CUDA code to execute matrix multiplication, a fundamental operation in deep learning. Through this course, you'll become proficient in GPU programming.
What is a GPU?
A graphics card, which processes a computer's image information and displays it on the screen, is designed to assist the central processing unit's graphics processing tasks. GPUs are widely used in AI and machine learning fields because they can dramatically increase computational speed.
Helpful people
Anyone interested in machine learning.
AI startups
Introduction of knowledge sharers
Choi Gwang-seong
I've been immersed in programming since graduate school. After graduation, I stayed in the lab and worked on developing semiconductor factory prediction simulation software. My primary languages are C++ and CUDA.
If the lecture length is short, then it is an advantage ^^*
After taking the course, I felt like I learned what CUDA programming is and that CUDA programming is easy.
One-line summary: A short but powerful CUDA in C lecture.
Can I look forward to follow-up lectures in the future?
Thank you for your good review. I'm glad it was helpful. If you have any suggestions on what kind of content should be included in the follow-up lecture, please let me know.
Thank you.
I think the tuition is too high compared to the content of the lecture. The lecture progresses too slowly and the content of the lecture seems a bit lacking. I think the tuition is a bit expensive compared to the lecture.
I'm not sure if you actually brought in a developer... the explanation is so frustrating. Is this even supposed to be a lecture?
While writing the matrix multiplication, you're stumbling over your words using just a single piece of pseudocode, and I have to figure out what you're trying to do by looking at the code myself. It's not like you're providing proper comments either.
This is a very disappointing lecture.
The high price is a problem, but considering my habit of not being able to finish reading a thick book, I think it was a really short and thick lecture.
justinlabry
