Fundamentals of Accelerated Computing with Modern CUDA C++ (FACCC)

This workshop provides a comprehensive introduction to general-purpose GPU programming with CUDA. You'll learn how to write, compile, and run GPU-accelerated code, leverage CUDA core libraries to h...

This workshop provides a comprehensive introduction to general-purpose GPU programming with CUDA. You'll learn how to write, compile, and run GPU-accelerated code, leverage CUDA core libraries to harness the power of massive parallelism provided by modern GPU accelerators, optimize memory migration between CPU and GPU, and implement your own algorithms. At the end of the workshop, you'll have access to additional resources to create your own GPU-accelerated applications.

Please note that once a booking has been confirmed, it is non-refundable. This means that after you have confirmed your seat for an event, it cannot be cancelled and no refund will be issued, regardless of attendance.

At the conclusion of the workshop, you'll have an understanding of the fundamental concepts and techniques for accelerating C++ code with CUDA and be able to:



- Write and compile code that runs on the GPU
- Optimize memory migration between CPU and GPU
- Leverage powerful parallel algorithms that simplify adding GPU acceleration to your code
- Implement your own parallel algorithms by directly programming GPUs with CUDA kernels
- Utilize concurrent CUDA streams to overlap memory traffic wi...

Introduction



- Meet the instructor.
- Create an account at courses.nvidia.com/join

CUDA Made Easy: Accelerating Applications with Parallel Algorithms

To make your first steps in GPU programming as easy as possible, this lab teaches you how to leverage powerful parallel algorithms that make GPU acceleration of your code as easy as changing a few lines of code. While doing so, you’ll learn fundamental concepts such as execution space and memory space, parallelism, heterogeneous computing,...