3.8  56 reviews on Udemy

Learning CUDA 10 Programming

Harness the power of GPUs to speed up your applications
Course from Udemy
 378 students enrolled
 en
Use CUDA to speed up your applications using machine learning, image processing, linear algebra, and more
Learn to debug CUDA programs and handle errors
Use optimization techniques to get the maximum performance from your CUDA programs
Master the fundamentals of concurrency and parallel algorithms on GPUs
Learn about the wide range of GPU-accelerated libraries included with CUDA
Learn the next steps you can take to continue building your CUDA skills

Do you want to write GPU-accelerated applications, but don't know how to get started? With CUDA 10, you can easily add GPU processing to your C and C++ projects. CUDA 10 is the de-facto framework used to develop high-performance, GPU-accelerated applications.

In this course, you will be introduced to CUDA programming through hands-on examples. CUDA provides a general-purpose programming model which gives you access to the tremendous computational power of modern GPUs, as well as powerful libraries for machine learning, image processing, linear algebra, and parallel algorithms.

After working through this course, you will understand the fundamentals of CUDA programming and be able to start using it in your applications right away.

About the Author

Nathan Weston is a software developer and lives in the Boston, USA area. He has worked in the visual effects industry, where he made extensive use of CUDA, and also has experience with software engineering research and scientific applications. He now works as a consultant with local and remote clients.

Learning CUDA 10 Programming
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